land reform, poverty reduction, and growth: evidence … · land reform, poverty reduction, and...

42
LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHY BESLEY AND ROBIN BURGESS In recent times there has been a renewed interest in relationships between redistribution, growth, and welfare. Land reforms in developing countries are often aimed at improving the poor’s access to land, although their effectiveness has often been hindered by political constraints on implementation. In this paper we use panel data on the sixteen main Indian states from 1958 to 1992 to consider whether the large volume of legislated land reforms have had an appreciable impact on growth and poverty. We argue that such land reforms have been associated with poverty reduction. I. INTRODUCTION Finding effective means to relieve poverty is a de ning mission for development economics. To this end, a wide range of policy alternatives has been implemented. However, the bene ts of many such efforts have been questioned. Some argue that political constraints on implementation deny the poor the bene ts of redistributive efforts. Others suggest that bene ts to the poor are undermined by disincentives to generate income. Worse still, these disincentives can afflict the nonpoor who try to qualify for assistance. This in turn leads policy analysts to question the wisdom of implementing redistributive policies at all, focusing instead on policies that promote economic growth. Combatting such pessimism requires empirical evidence that some redistribu- tive policies have achieved their stated goals. This paper studies land reform as a redistributive policy. Throughout the postcolonial period, improvement in the asset base of the poor has been viewed as a central strategy to relieve endemic poverty {Chenery et al. 1970}. In a poor agrarian economy, typical of those in many less developed countries, this implies improving the terms on which the poor have access to land. Signi cant political changes, such as decolonization, have sometimes afforded the opportunity to undertake far-reaching land reforms that transfer property rights to the poor. However, * The authors are grateful to Alberto Alesina, Ahbijit Banerjee, Pranab Bardhan, Clive Bell, Francois Bourgignon, Jean Dre `ze, Lawrence Katz, Michael Lipton, Rohini Pande, Martin Ravallion, a number of seminar participants, and two anonymous referees for helpful comments. Timo Henckel and Cecilia Testa provided able research assistance. We also thank STICERD for invaluable nancial support. r 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology. The Quarterly Journal of Economics, May 2000 389

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Page 1: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

LAND REFORM POVERTY REDUCTION AND GROWTHEVIDENCE FROM INDIA

TIMOTHY BESLEY AND ROBIN BURGESS

In recent times there has been a renewed interest in relationships betweenredistribution growth and welfare Land reforms in developing countries areoften aimed at improving the poorrsquos access to land although their effectiveness hasoften been hindered by political constraints on implementation In this paper weuse panel data on the sixteen main Indian states from 1958 to 1992 to considerwhether the large volume of legislated land reforms have had an appreciableimpact on growth and poverty We argue that such land reforms have beenassociated with poverty reduction

I INTRODUCTION

Finding effective means to relieve poverty is a deningmission for development economics To this end a wide range ofpolicy alternatives has been implemented However the benetsof many such efforts have been questioned Some argue thatpolitical constraints on implementation deny the poor the benetsof redistributive efforts Others suggest that benets to the poorare undermined by disincentives to generate income Worse stillthese disincentives can afflict the nonpoor who try to qualify forassistance This in turn leads policy analysts to question thewisdom of implementing redistributive policies at all focusinginstead on policies that promote economic growth Combattingsuch pessimism requires empirical evidence that some redistribu-tive policies have achieved their stated goals

This paper studies land reform as a redistributive policyThroughout the postcolonial period improvement in the assetbase of the poor has been viewed as a central strategy to relieveendemic poverty Chenery et al 1970 In a poor agrarianeconomy typical of those in many less developed countries thisimplies improving the terms on which the poor have access toland Signicant political changes such as decolonization havesometimes afforded the opportunity to undertake far-reachingland reforms that transfer property rights to the poor However

The authors are grateful to Alberto Alesina Ahbijit Banerjee PranabBardhan Clive Bell Francois Bourgignon Jean Dreze Lawrence Katz MichaelLipton Rohini Pande Martin Ravallion a number of seminar participants andtwo anonymous referees for helpful comments Timo Henckel and Cecilia Testaprovided able research assistance We also thank STICERD for invaluablenancial support

r 2000 by the President and Fellows of Harvard College and the Massachusetts Institute ofTechnologyThe Quarterly Journal of Economics May 2000

389

such instances are rare and more incremental measures arecommon This is the case in India where land reforms have beenon the policy agenda since independence These reforms haveinvolved only limited efforts at land redistribution mostly throughlegislated ceilings on landholding Legislation aimed at regulat-ing tenancies for example by improving tenurial security andreducing the power of absentee landlords and intermediaries aremore common While the latter need not change the distributionof landholdings they may improve tenantsrsquo claims to the returnsfrom their land This may also benet the landless by raisingagricultural wages

India is an important case study of land reform It is bothhome to a signicant fraction of the poor in the developing worldand in the postindependence period was subjected to the largestbody of land reform legislation ever to have been passed in soshort a period in any country Thorner 1976 The efficacy of thislegislation has however been much debated The conventionalwisdom following the inuential commentary of Bardhan 1970 isthat while land reform legislation abounds the real impact on theconditions of the poor is muted by unenthusiastic implementationof proposed changes However broad-based quantitative testingof this notion does not appear to have been attempted previouslyThis paper takes advantage of the state level panel data availablefor the sixteen main Indian states from 1958 to 1992 to assessthis The state is the natural unit of analysis for land reform giventhat state governments have jurisdiction over land reform legisla-tion The relatively long time period covered by the data alsoallows respectable efforts to deal with some econometric concernsOur principal nding is that land reforms do appear to have led toreductions in poverty in India This nding is robust to a numberof methods of estimation and the inclusionexclusion of manydifferent controls

We also use our data to investigate the relationship betweenland reform and growth This relates to more general debatesabout how inequality and growth interact Alesina and Rodrik1994 and Persson and Tabellini 1995 have argued that initialinequality is bad for economic growth The link is through thepolitical systemmdashgreater inequality encourages redistributiveactivities that blunt accumulation incentives However Hoff andLyon 1995 Banerjee and Newman 1993 and Benabou 1996among others have emphasized that when markets are incom-plete then redistribution can alter the terms of agency problems

QUARTERLY JOURNAL OF ECONOMICS390

in credit markets and foster accumulation decisions thus under-mining the standard equity efficiency trade-off If accumulation isenhanced by redistribution along the growth path then we wouldexpect to nd a positive relationship between redistributiveefforts and economic growth The existing literature has focusedpredominantly on scal redistributions By affecting access toland land reform may have a more lasting effect on poverty Thisview is consistent with the literature that points to early redistri-butions of land leading to relatively egalitarian access as being animportant precondition for high growth in East Asia (see forexample Rodrik 1995)

Most existing empirical evidence on the links between redis-tribution and growth comes from cross-country data (see Perotti1996 for a careful review) While informative there are insur-mountable problems of comparability of data across countries anddealing with concerns about endogeneity The fact that our datacome from one country with similar data collection strategies ineach state and the relatively long time period allow us to makeprogress on this

Empirical studies of the impact of land reform are rare sincereliable estimation requires data from the pre- and postreformperiods In India there are numerous case studies of land reform(reviewed below) but few attempts to look at the overall pictureDiscussion of the theoretical impact of land reform has beendominated by the frequently found inverse farm size-productivityrelationship whence small farmers are supposed to achievehigher yields (see Binswanger et al 1995) This suggests thatnding means of evening the distribution of landholding shouldlead to productivity gains in addition to redistributive benetsHowever land reforms in India are rarely of a form that coulddirectly exploit this possibility Moreover careful analyses suchas Banerjee and Ghatak 1997 show that the theoretical effectson productivity are inherently ambiguous when assessing theimpact of tenancy reforms that allow tenants greater security

Our main nding is that there is a robust link between landreform and poverty reduction Closer scrutiny reveals that in anIndian context this is due primarily to land reforms that changethe terms of land contracts rather than actually redistributingland Consistent with the antipoverty impact we nd that landreform has raised agricultural wages The impact of land reformon growth also depends upon the type of land reform Overallthere is some evidence that the gain in poverty reduction did come

LAND POVERTY AND GROWTH INDIA 391

at the expense of lower income per capita We show that all ofthese results are consistent with a simple model of agriculturalcontracting

The remainder of the paper is organized as follows The nextsection discusses background and data issues Section III exam-ines the impact that land reforms have had on poverty and dealswith potential problems in interpreting the basic results SectionIV addresses the issue as to whether land reforms can havegeneral equilibrium effects by examining their impact on agricul-tural wages Section V then turns to the issue of how land reformshave affected economic growth In Section VI we examine theextent to which land reforms have been redistributive in terms oftheir effect on the distribution of land and income In Section VIIwe develop a theoretical framework that allows us to interpret ourresults in the light of the literature on agricultural contractingSection VIII concludes A Data Appendix details the constructionand sources of the key variables used in the analysis

II BACKGROUND AND DATA

Under the 1949 Indian Constitution states were granted thepowers to enact (and implement) land reforms This autonomyensures that there has been signicant variation across statesand time in terms of the number and types of land reforms thathave been enacted (see Table I) We classify land reform acts intofour main categories according to their main purpose (see Mearns1998) The rst category is acts related to tenancy reform Theseinclude attempts to regulate tenancy contracts both via registra-tion and stipulation of contractual terms such as shares in sharetenancy contracts as well as attempts to abolish tenancy andtransfer ownership to tenants The second category of land reformacts are attempts to abolish intermediaries These intermediarieswho worked under feudal lords (Zamandari) to collect rent for theBritish were reputed to allow a larger share of the surplus fromthe land to be extracted from tenants Most states had passedlegislation to abolish intermediaries prior to 1958 However ve(Gujarat Kerala Orissa Rajasthan and Uttar Pradesh) did soduring our data period The third category of land reform actsconcerned efforts to implement ceilings on landholdings with aview to redistributing surplus land to the landless Finally wehave acts that attempted to allow consolidation of disparatelandholdings Although these reforms in particular the latter

QUARTERLY JOURNAL OF ECONOMICS392

TAB

LE

IS

UM

MA

RY

OF

MA

INVA

RIA

BL

ES

Sta

te

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Agr

icu

ltu

ral

wag

es

Sta

tein

com

epe

rca

pita

Agr

icu

l-tu

ral

yiel

d

Cu

mu

lati

veto

tall

and

refo

rmle

gisl

atio

n

Cu

mu

lati

vete

nan

cyre

form

legi

slat

ion

Cu

mu

lati

veab

olit

ion

inte

rmed

iari

esle

gisl

atio

n

Cum

ula

tive

land

ceil

ings

legi

slat

ion

Cu

mu

lati

vela

nd

con

soli

dati

onle

gisl

atio

n

And

raP

rade

sh14

87

505

94

5310

0433

40

152

80

528

100

00

0(5

11)

(11

61)

(11

0)(2

60)

(33

11)

(05

06)

(05

06)

(0)

(0)

(0)

Ass

am10

69

489

15

3590

350

54

200

00

611

00

472

091

6(2

67)

(91

6)(1

04)

(196

)(3

759

)(1

069

)(0

494

)(0

)(0

506

)(0

280

)B

ihar

208

864

65

407

633

426

44

305

263

90

166

70

(46

7)(6

40)

(10

1)(1

10)

(39

95)

(19

24)

(09

30)

(0)

(10

42)

(0)

Gu

jara

t15

81

534

94

3911

7625

21

305

61

472

066

70

917

0(4

94)

(99

9)(0

78)

(272

)(2

384

)(1

264

)(0

654

)(0

478

)(0

280

)(0

)H

arya

na7

1130

00

mdash14

4423

22

00

00

0(2

15)

(69

0)(3

57)

(20

46)

(0)

(0)

(0)

(0)

(0)

Jam

mu

and

720

345

5mdash

1021

515

31

333

047

20

00

861

Kas

hm

ir(2

59)

(81

3)(2

28)

(43

28)

(07

17)

(05

06)

(0)

(0)

(03

51)

Kar

nat

aka

169

954

46

385

1037

252

62

833

141

70

141

70

(38

6)(8

08)

(06

6)(2

16)

(24

26)

(13

84)

(06

92)

(0)

(06

92)

(0)

Ker

ala

197

056

92

624

864

657

55

444

241

71

972

105

60

(79

8)(1

453

)(1

56)

(182

)(6

026

)(3

376

)(1

556

)(1

000

)(0

860

)(0

)M

adh

ya18

03

572

63

8184

317

01

280

60

944

00

917

094

4P

rade

sh(4

11)

(74

5)(0

83)

(190

)(1

607

)(0

710

)(0

232

)(0

)(0

280

)(0

232

)M

ahar

ash

tra

197

163

82

355

1288

208

41

861

097

20

088

90

(43

8)(9

64)

(07

1)(3

31)

(20

57)

(04

24)

(16

67)

(0)

(03

19)

(0)

Ori

ssa

174

256

63

407

873

250

65

056

194

40

583

194

40

583

(46

2)(9

53)

(08

5)(1

86)

(20

23)

(31

16)

(10

93)

(05

00)

(10

93)

(05

00)

Pu

nja

b6

1426

22

816

1732

345

50

583

058

30

00

(28

8)(8

23)

(10

9)(3

84)

(29

70)

(05

00)

(05

00)

(0)

(0)

(0)

Raj

asth

an16

96

534

15

1278

516

27

094

40

094

40

0(3

81)

(74

8)(0

68)

(136

)(1

575

)(0

232

)(0

)(0

232

)(0

)(0

)Ta

mil

Nad

u18

58

580

43

9210

1536

59

491

74

028

00

889

0(4

40)

(85

6)(0

52)

(272

)(3

266

)(2

545

)(2

336

)(0

)(0

319

)(0

)U

ttar

Pra

desh

128

446

70

471

874

464

375

01

417

141

70

917

0(3

14)

(76

8)(1

38)

(140

)(3

823

)(1

251

)(0

554

)(0

554

)(0

280

)(0

)W

est

Ben

gal

149

251

48

612

1173

605

96

139

383

30

061

11

694

(53

2)(1

242

)(1

81)

(191

)(5

720

)(5

581

)(3

476

)(0

)(0

993

)(1

369

)T

OTA

L15

01

507

94

799

1030

354

92

910

145

50

411

073

10

312

(62

8)(1

408

)(1

584

)(3

46)

(37

36)

(27

49)

(17

07)

(06

92)

(08

25)

(06

35)

Sta

nda

rdd

evia

tion

sar

ein

pare

nth

eses

mdashde

not

esa

mis

sin

gva

riab

leS

eeth

eD

ata

App

end

ixfo

rd

etai

lson

con

stru

ctio

nan

dso

urc

esof

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

H

arya

na

spli

tfr

omth

est

ate

ofP

un

jab

in19

65F

rom

this

dat

eon

we

incl

ud

ese

para

teob

serv

atio

ns

for

Pu

nja

ban

dH

arya

na

Th

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cep

tion

isru

ral

wag

esw

her

eth

ere

isn

ose

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ries

for

Har

yan

aor

for

Jam

mu

and

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hm

irS

tate

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me

per

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ita

isob

tain

edby

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ress

ing

esti

mat

esof

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edo

mes

tic

prod

uct

inre

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pit

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rms

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icu

ltu

raly

ield

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sure

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ton

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wn

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din

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tare

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he

wag

ed

ata

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rto

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rate

for

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eag

ricu

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rall

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ers

and

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pres

sed

inre

alte

rms

LAND POVERTY AND GROWTH INDIA 393

were justied partly in terms of achieving efficiency gains inagriculture it is clear from the acts themselves and from thepolitical manifestos supporting the acts that the main impetusdriving the rst three reforms was poverty reduction It istherefore interesting to assess whether these reforms were effec-tive in achieving their stated aims

Existing assessments of the effectiveness of these differentreforms are highly mixed Although promoted by the center invarious Five Year Plans the fact that land reforms were a statesubject under the 1949 Constitution meant that enactment andimplementation was dependent on the political will of stategovernments Bandyopadhyay 1986 Radhakrishnan 1990 Appu1996 Behuria 1997 Mearns 1998 The perceived oppressivecharacter of the Zamandari (and their intermediaries) and theirclose alliance with the British galvanized broad political supportfor the abolition of intermediaries and led to widespread implemen-tation of these reforms most of which were complete by the early1960s Appu 1996 Mearns 19981 Centre-state alignment on theissue of tenancy reforms was much less pronounced2 With manystate legislatures controlled by the landlord class reforms thatharmed this class tended to be blocked although where tenantshad substantial political representation notable successes inimplementation were recorded Despite the considerable publicityattached to their enactment political failure to implement wasmost complete in the case of land ceiling legislation Hereambivalence in the formulation of policy and numerous loopholesallowed the bulk of landowners to avoid expropriation by distrib-uting surplus land to relations friends and dependents Appu1996 Mearns 1998 As a result of these problems implementa-tion of both tenancy reform and land ceiling legislation tended tolag well behind the targets set in the Five Year Plans Bandy-opadhyay 1986 Radhakrishnan 19903 Land consolidation legis-lation was enacted less than the other reforms and owing partly

1 There were nonetheless some major design aws most notably the failureto limit the size of home farms of Zamindars or to protect short-term tenants

2 Warriner 1969 commented that the Congress party (the main politicalforce for most of our period) lsquolsquoprovided both the motivation for land reform and theopposition to it as a socialist head with a conservative bodyrsquorsquo

3 The Fifth Plan gives a frank assessmentof the situation which is directly inline with that of Bardhan 1970 lsquolsquoA broad assessment of the programme of landreform adopted since Independence is that the laws for the abolition of intermedi-ary tenures have been implemented fairly efficiently whilst in the elds of tenancyreforms and ceilings on holdings legislation has fallen short of the desiredobjectives and implementation of the enacted laws has been inadequatersquorsquo FifthFive Year Plan 1974ndash79 2 43

QUARTERLY JOURNAL OF ECONOMICS394

to the sparseness of land records implementation has beenconsidered to be both sporadic and patchy only affecting a fewstates in any signicant way Radhakrishnan 1990 Appu 1996Behuria 1997 Mearns 1998

Village level studies also offer a very mixed assessment of thepoverty impact of different land reforms (see Jayaraman andLanjouw 1997) Similar reforms seemed to have produced differ-ent effects in different areas leaving overall impact indeterminateThere is some consensus that the abolition of intermediariesachieved a limited and variable success both in redistributingland toward the poor and increasing the security of smallholders(see eg Wadley and Derr 1990) For tenancy reform howeverwhereas successes have been recorded in particular wheretenants are well organized there has also been a range ofdocumented cases of imminent legislation prompting landlords toengage in mass evictions of tenants and of the de jure banning oflandlord-tenant relationships pushing tenancy underground andtherefore paradoxically reducing tenurial security (see egGough 1989) Land ceiling legislation in a variety of villagestudies is also perceived to have had neutral or negative effects onpoverty by inducing landowners from joint families to evict theirtenants and to separate their holdings into smaller proprietaryunits among family members as a means of avoiding expropria-tion (see eg Chattopadhyay 1994) Land consolidation is alsoon the whole judged not to have been progressive in its redistribu-tive impact given that richer farmers tend to use their power toobtain improved holdings (see eg Dreze Lanjouw and Sharma1998)

Table II gives a complete picture of land reform legislationand its classication during our data period Our empiricalanalysis aggregates reforms within each category If land reformshave any effect then we doubt that this would be instantaneousThus we cumulate land reforms over time generating a variablethat aggregates the number of legislative reforms to date in anyparticular state While crude we believe that it provides asensible rst pass at analyzing the quantitative effects of landreform The mean of that variable aggregated across the fourcategories of land reform is given in column 6 of Table I Similarmeans for the different categories of reform are given in columns7ndash10 The table demonstrates considerable variation in overallland reform activity across states with states such as Uttar

LAND POVERTY AND GROWTH INDIA 395

TA

BL

EII

IMP

OR

TA

NT

EV

EN

TS

INL

AN

DR

EF

OR

MS

ININ

DIA

NS

TA

TE

SS

INC

E19

50

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

And

hra

Pra

desh

1950 (a

men

ded

1954

)

(Tel

enga

na

Are

a)Te

nanc

yan

dA

gri-

cult

ura

lLan

dsA

ctTe

nan

tsre

ceiv

edpr

otec

ted

ten

ancy

stat

ust

enan

tsto

hav

em

inim

um

term

ofle

ase

righ

tof

purc

hase

ofn

onre

sum

able

lan

dst

rans

fer

ofow

ner

ship

topr

otec

ted

ten

ants

inre

spec

tof

non

resu

mab

lela

nds

as

are

sult

136

11pr

otec

ted

ten

ants

decl

ared

own

ers

1

1952

Hyd

erab

adA

boli

tion

ofC

ash

Gra

nts

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tele

nga

na

2

1954

Inam

Abo

liti

onA

ct(a

bsor

bed)

encl

aves

Abo

liti

onof

inam

s(w

ith

few

exce

ptio

ns)

2

1955

(Hyd

erab

adJa

gird

ars)

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tal

enga

na

219

56In

am(A

boli

tion

and

Con

vers

ion

into

Ryo

twar

i)A

ctA

cqu

isit

ion

of11

137

esta

tes

abol

itio

nof

106

mil

lion

min

orin

ams

2

1956 (a

men

ded

1974

)

Ten

ancy

Act

Ten

ancy

con

tin

ues

up

to2

3of

ceil

ing

area

law

does

not

prov

ide

for

con

fer-

men

tof

own

ersh

ipri

ght

onte

nant

sex

cept

thro

ugh

righ

tto

purc

has

eco

nfe

rsco

ntin

uou

sri

ght

ofre

sum

ptio

non

lan

dow

ner

s

1

1957

Inam

Abo

liti

onA

ctA

boli

tion

ofin

ams

(wit

hfe

wex

cept

ions

)st

ruck

dow

nby

the

Hig

hC

ourt

in19

70

2

Ass

am19

51S

tate

Acq

uis

itio

nof

Zam

inda

riA

ctA

boli

tion

ofin

term

edia

ryri

ghts

invo

lvin

g0

67m

illi

onh

ecta

res

219

54L

ush

aiH

ills

Dis

tric

t(A

cqu

isit

ion

ofC

hie

fsR

igh

ts)A

ctS

ame

asab

ove

2

1956 (a

men

ded

1976

)

Fix

atio

nof

Cei

lin

gon

Lan

dH

oldi

ngs

Act

Sel

f-ex

plan

ator

y3

1960

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1971

Ten

ancy

Act

Cla

ssi

este

nan

tsin

tooc

cupa

ncy

and

non

occu

pan

cyte

nan

tsf

orm

erh

asse

curi

tyof

ten

ure

may

acqu

ire

lan

dlor

drsquos

righ

tof

hol

din

gby

payi

ng

50ti

mes

the

lan

dre

ven

ue

subl

etti

ngis

disa

llow

ed

1

QUARTERLY JOURNAL OF ECONOMICS396

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

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Act

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1953

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ates

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1972

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hom

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are

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1975

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and

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Act

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LAND POVERTY AND GROWTH INDIA 401

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(CO

NT

INU

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)

Sta

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1986

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QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

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IND

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Mod

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Ru

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Pov

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(1)

(2)

(3)

(4)

(5)

(6)

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SA

R(1

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LS

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(1)

GL

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R(1

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20

378

(37

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20

539

(46

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129

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179

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81)

23

14(2

48)

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035

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121

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Pop

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297

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11

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for

the

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for

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twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

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Agr

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ruct

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een

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ates

For

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eda

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vest

ates

for

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nja

ban

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arya

na

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ich

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tin

1965

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hav

eda

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mu

and

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ar19

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sor

For

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ates

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rP

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jab

1969

ndash199

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arya

na

1970

ndash197

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992

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Jam

mu

and

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for

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aran

dG

uja

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1964

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am19

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1964

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Th

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433

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roce

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see

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atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 2: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

such instances are rare and more incremental measures arecommon This is the case in India where land reforms have beenon the policy agenda since independence These reforms haveinvolved only limited efforts at land redistribution mostly throughlegislated ceilings on landholding Legislation aimed at regulat-ing tenancies for example by improving tenurial security andreducing the power of absentee landlords and intermediaries aremore common While the latter need not change the distributionof landholdings they may improve tenantsrsquo claims to the returnsfrom their land This may also benet the landless by raisingagricultural wages

India is an important case study of land reform It is bothhome to a signicant fraction of the poor in the developing worldand in the postindependence period was subjected to the largestbody of land reform legislation ever to have been passed in soshort a period in any country Thorner 1976 The efficacy of thislegislation has however been much debated The conventionalwisdom following the inuential commentary of Bardhan 1970 isthat while land reform legislation abounds the real impact on theconditions of the poor is muted by unenthusiastic implementationof proposed changes However broad-based quantitative testingof this notion does not appear to have been attempted previouslyThis paper takes advantage of the state level panel data availablefor the sixteen main Indian states from 1958 to 1992 to assessthis The state is the natural unit of analysis for land reform giventhat state governments have jurisdiction over land reform legisla-tion The relatively long time period covered by the data alsoallows respectable efforts to deal with some econometric concernsOur principal nding is that land reforms do appear to have led toreductions in poverty in India This nding is robust to a numberof methods of estimation and the inclusionexclusion of manydifferent controls

We also use our data to investigate the relationship betweenland reform and growth This relates to more general debatesabout how inequality and growth interact Alesina and Rodrik1994 and Persson and Tabellini 1995 have argued that initialinequality is bad for economic growth The link is through thepolitical systemmdashgreater inequality encourages redistributiveactivities that blunt accumulation incentives However Hoff andLyon 1995 Banerjee and Newman 1993 and Benabou 1996among others have emphasized that when markets are incom-plete then redistribution can alter the terms of agency problems

QUARTERLY JOURNAL OF ECONOMICS390

in credit markets and foster accumulation decisions thus under-mining the standard equity efficiency trade-off If accumulation isenhanced by redistribution along the growth path then we wouldexpect to nd a positive relationship between redistributiveefforts and economic growth The existing literature has focusedpredominantly on scal redistributions By affecting access toland land reform may have a more lasting effect on poverty Thisview is consistent with the literature that points to early redistri-butions of land leading to relatively egalitarian access as being animportant precondition for high growth in East Asia (see forexample Rodrik 1995)

Most existing empirical evidence on the links between redis-tribution and growth comes from cross-country data (see Perotti1996 for a careful review) While informative there are insur-mountable problems of comparability of data across countries anddealing with concerns about endogeneity The fact that our datacome from one country with similar data collection strategies ineach state and the relatively long time period allow us to makeprogress on this

Empirical studies of the impact of land reform are rare sincereliable estimation requires data from the pre- and postreformperiods In India there are numerous case studies of land reform(reviewed below) but few attempts to look at the overall pictureDiscussion of the theoretical impact of land reform has beendominated by the frequently found inverse farm size-productivityrelationship whence small farmers are supposed to achievehigher yields (see Binswanger et al 1995) This suggests thatnding means of evening the distribution of landholding shouldlead to productivity gains in addition to redistributive benetsHowever land reforms in India are rarely of a form that coulddirectly exploit this possibility Moreover careful analyses suchas Banerjee and Ghatak 1997 show that the theoretical effectson productivity are inherently ambiguous when assessing theimpact of tenancy reforms that allow tenants greater security

Our main nding is that there is a robust link between landreform and poverty reduction Closer scrutiny reveals that in anIndian context this is due primarily to land reforms that changethe terms of land contracts rather than actually redistributingland Consistent with the antipoverty impact we nd that landreform has raised agricultural wages The impact of land reformon growth also depends upon the type of land reform Overallthere is some evidence that the gain in poverty reduction did come

LAND POVERTY AND GROWTH INDIA 391

at the expense of lower income per capita We show that all ofthese results are consistent with a simple model of agriculturalcontracting

The remainder of the paper is organized as follows The nextsection discusses background and data issues Section III exam-ines the impact that land reforms have had on poverty and dealswith potential problems in interpreting the basic results SectionIV addresses the issue as to whether land reforms can havegeneral equilibrium effects by examining their impact on agricul-tural wages Section V then turns to the issue of how land reformshave affected economic growth In Section VI we examine theextent to which land reforms have been redistributive in terms oftheir effect on the distribution of land and income In Section VIIwe develop a theoretical framework that allows us to interpret ourresults in the light of the literature on agricultural contractingSection VIII concludes A Data Appendix details the constructionand sources of the key variables used in the analysis

II BACKGROUND AND DATA

Under the 1949 Indian Constitution states were granted thepowers to enact (and implement) land reforms This autonomyensures that there has been signicant variation across statesand time in terms of the number and types of land reforms thathave been enacted (see Table I) We classify land reform acts intofour main categories according to their main purpose (see Mearns1998) The rst category is acts related to tenancy reform Theseinclude attempts to regulate tenancy contracts both via registra-tion and stipulation of contractual terms such as shares in sharetenancy contracts as well as attempts to abolish tenancy andtransfer ownership to tenants The second category of land reformacts are attempts to abolish intermediaries These intermediarieswho worked under feudal lords (Zamandari) to collect rent for theBritish were reputed to allow a larger share of the surplus fromthe land to be extracted from tenants Most states had passedlegislation to abolish intermediaries prior to 1958 However ve(Gujarat Kerala Orissa Rajasthan and Uttar Pradesh) did soduring our data period The third category of land reform actsconcerned efforts to implement ceilings on landholdings with aview to redistributing surplus land to the landless Finally wehave acts that attempted to allow consolidation of disparatelandholdings Although these reforms in particular the latter

QUARTERLY JOURNAL OF ECONOMICS392

TAB

LE

IS

UM

MA

RY

OF

MA

INVA

RIA

BL

ES

Sta

te

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Agr

icu

ltu

ral

wag

es

Sta

tein

com

epe

rca

pita

Agr

icu

l-tu

ral

yiel

d

Cu

mu

lati

veto

tall

and

refo

rmle

gisl

atio

n

Cu

mu

lati

vete

nan

cyre

form

legi

slat

ion

Cu

mu

lati

veab

olit

ion

inte

rmed

iari

esle

gisl

atio

n

Cum

ula

tive

land

ceil

ings

legi

slat

ion

Cu

mu

lati

vela

nd

con

soli

dati

onle

gisl

atio

n

And

raP

rade

sh14

87

505

94

5310

0433

40

152

80

528

100

00

0(5

11)

(11

61)

(11

0)(2

60)

(33

11)

(05

06)

(05

06)

(0)

(0)

(0)

Ass

am10

69

489

15

3590

350

54

200

00

611

00

472

091

6(2

67)

(91

6)(1

04)

(196

)(3

759

)(1

069

)(0

494

)(0

)(0

506

)(0

280

)B

ihar

208

864

65

407

633

426

44

305

263

90

166

70

(46

7)(6

40)

(10

1)(1

10)

(39

95)

(19

24)

(09

30)

(0)

(10

42)

(0)

Gu

jara

t15

81

534

94

3911

7625

21

305

61

472

066

70

917

0(4

94)

(99

9)(0

78)

(272

)(2

384

)(1

264

)(0

654

)(0

478

)(0

280

)(0

)H

arya

na7

1130

00

mdash14

4423

22

00

00

0(2

15)

(69

0)(3

57)

(20

46)

(0)

(0)

(0)

(0)

(0)

Jam

mu

and

720

345

5mdash

1021

515

31

333

047

20

00

861

Kas

hm

ir(2

59)

(81

3)(2

28)

(43

28)

(07

17)

(05

06)

(0)

(0)

(03

51)

Kar

nat

aka

169

954

46

385

1037

252

62

833

141

70

141

70

(38

6)(8

08)

(06

6)(2

16)

(24

26)

(13

84)

(06

92)

(0)

(06

92)

(0)

Ker

ala

197

056

92

624

864

657

55

444

241

71

972

105

60

(79

8)(1

453

)(1

56)

(182

)(6

026

)(3

376

)(1

556

)(1

000

)(0

860

)(0

)M

adh

ya18

03

572

63

8184

317

01

280

60

944

00

917

094

4P

rade

sh(4

11)

(74

5)(0

83)

(190

)(1

607

)(0

710

)(0

232

)(0

)(0

280

)(0

232

)M

ahar

ash

tra

197

163

82

355

1288

208

41

861

097

20

088

90

(43

8)(9

64)

(07

1)(3

31)

(20

57)

(04

24)

(16

67)

(0)

(03

19)

(0)

Ori

ssa

174

256

63

407

873

250

65

056

194

40

583

194

40

583

(46

2)(9

53)

(08

5)(1

86)

(20

23)

(31

16)

(10

93)

(05

00)

(10

93)

(05

00)

Pu

nja

b6

1426

22

816

1732

345

50

583

058

30

00

(28

8)(8

23)

(10

9)(3

84)

(29

70)

(05

00)

(05

00)

(0)

(0)

(0)

Raj

asth

an16

96

534

15

1278

516

27

094

40

094

40

0(3

81)

(74

8)(0

68)

(136

)(1

575

)(0

232

)(0

)(0

232

)(0

)(0

)Ta

mil

Nad

u18

58

580

43

9210

1536

59

491

74

028

00

889

0(4

40)

(85

6)(0

52)

(272

)(3

266

)(2

545

)(2

336

)(0

)(0

319

)(0

)U

ttar

Pra

desh

128

446

70

471

874

464

375

01

417

141

70

917

0(3

14)

(76

8)(1

38)

(140

)(3

823

)(1

251

)(0

554

)(0

554

)(0

280

)(0

)W

est

Ben

gal

149

251

48

612

1173

605

96

139

383

30

061

11

694

(53

2)(1

242

)(1

81)

(191

)(5

720

)(5

581

)(3

476

)(0

)(0

993

)(1

369

)T

OTA

L15

01

507

94

799

1030

354

92

910

145

50

411

073

10

312

(62

8)(1

408

)(1

584

)(3

46)

(37

36)

(27

49)

(17

07)

(06

92)

(08

25)

(06

35)

Sta

nda

rdd

evia

tion

sar

ein

pare

nth

eses

mdashde

not

esa

mis

sin

gva

riab

leS

eeth

eD

ata

App

end

ixfo

rd

etai

lson

con

stru

ctio

nan

dso

urc

esof

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

H

arya

na

spli

tfr

omth

est

ate

ofP

un

jab

in19

65F

rom

this

dat

eon

we

incl

ud

ese

para

teob

serv

atio

ns

for

Pu

nja

ban

dH

arya

na

Th

eex

cep

tion

isru

ral

wag

esw

her

eth

ere

isn

ose

para

tese

ries

for

Har

yan

aor

for

Jam

mu

and

Kas

hm

irS

tate

inco

me

per

cap

ita

isob

tain

edby

exp

ress

ing

esti

mat

esof

stat

edo

mes

tic

prod

uct

inre

alpe

rca

pit

ate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pre

sen

tth

era

tio

ofre

alag

ricu

ltu

ral

stat

edo

mes

tic

pro

duct

ton

etso

wn

area

mea

sure

din

thou

san

dsof

hec

tare

sT

he

wag

ed

ata

refe

rto

the

dail

yw

age

rate

for

mal

eag

ricu

ltu

rall

abor

ers

and

isex

pres

sed

inre

alte

rms

LAND POVERTY AND GROWTH INDIA 393

were justied partly in terms of achieving efficiency gains inagriculture it is clear from the acts themselves and from thepolitical manifestos supporting the acts that the main impetusdriving the rst three reforms was poverty reduction It istherefore interesting to assess whether these reforms were effec-tive in achieving their stated aims

Existing assessments of the effectiveness of these differentreforms are highly mixed Although promoted by the center invarious Five Year Plans the fact that land reforms were a statesubject under the 1949 Constitution meant that enactment andimplementation was dependent on the political will of stategovernments Bandyopadhyay 1986 Radhakrishnan 1990 Appu1996 Behuria 1997 Mearns 1998 The perceived oppressivecharacter of the Zamandari (and their intermediaries) and theirclose alliance with the British galvanized broad political supportfor the abolition of intermediaries and led to widespread implemen-tation of these reforms most of which were complete by the early1960s Appu 1996 Mearns 19981 Centre-state alignment on theissue of tenancy reforms was much less pronounced2 With manystate legislatures controlled by the landlord class reforms thatharmed this class tended to be blocked although where tenantshad substantial political representation notable successes inimplementation were recorded Despite the considerable publicityattached to their enactment political failure to implement wasmost complete in the case of land ceiling legislation Hereambivalence in the formulation of policy and numerous loopholesallowed the bulk of landowners to avoid expropriation by distrib-uting surplus land to relations friends and dependents Appu1996 Mearns 1998 As a result of these problems implementa-tion of both tenancy reform and land ceiling legislation tended tolag well behind the targets set in the Five Year Plans Bandy-opadhyay 1986 Radhakrishnan 19903 Land consolidation legis-lation was enacted less than the other reforms and owing partly

1 There were nonetheless some major design aws most notably the failureto limit the size of home farms of Zamindars or to protect short-term tenants

2 Warriner 1969 commented that the Congress party (the main politicalforce for most of our period) lsquolsquoprovided both the motivation for land reform and theopposition to it as a socialist head with a conservative bodyrsquorsquo

3 The Fifth Plan gives a frank assessmentof the situation which is directly inline with that of Bardhan 1970 lsquolsquoA broad assessment of the programme of landreform adopted since Independence is that the laws for the abolition of intermedi-ary tenures have been implemented fairly efficiently whilst in the elds of tenancyreforms and ceilings on holdings legislation has fallen short of the desiredobjectives and implementation of the enacted laws has been inadequatersquorsquo FifthFive Year Plan 1974ndash79 2 43

QUARTERLY JOURNAL OF ECONOMICS394

to the sparseness of land records implementation has beenconsidered to be both sporadic and patchy only affecting a fewstates in any signicant way Radhakrishnan 1990 Appu 1996Behuria 1997 Mearns 1998

Village level studies also offer a very mixed assessment of thepoverty impact of different land reforms (see Jayaraman andLanjouw 1997) Similar reforms seemed to have produced differ-ent effects in different areas leaving overall impact indeterminateThere is some consensus that the abolition of intermediariesachieved a limited and variable success both in redistributingland toward the poor and increasing the security of smallholders(see eg Wadley and Derr 1990) For tenancy reform howeverwhereas successes have been recorded in particular wheretenants are well organized there has also been a range ofdocumented cases of imminent legislation prompting landlords toengage in mass evictions of tenants and of the de jure banning oflandlord-tenant relationships pushing tenancy underground andtherefore paradoxically reducing tenurial security (see egGough 1989) Land ceiling legislation in a variety of villagestudies is also perceived to have had neutral or negative effects onpoverty by inducing landowners from joint families to evict theirtenants and to separate their holdings into smaller proprietaryunits among family members as a means of avoiding expropria-tion (see eg Chattopadhyay 1994) Land consolidation is alsoon the whole judged not to have been progressive in its redistribu-tive impact given that richer farmers tend to use their power toobtain improved holdings (see eg Dreze Lanjouw and Sharma1998)

Table II gives a complete picture of land reform legislationand its classication during our data period Our empiricalanalysis aggregates reforms within each category If land reformshave any effect then we doubt that this would be instantaneousThus we cumulate land reforms over time generating a variablethat aggregates the number of legislative reforms to date in anyparticular state While crude we believe that it provides asensible rst pass at analyzing the quantitative effects of landreform The mean of that variable aggregated across the fourcategories of land reform is given in column 6 of Table I Similarmeans for the different categories of reform are given in columns7ndash10 The table demonstrates considerable variation in overallland reform activity across states with states such as Uttar

LAND POVERTY AND GROWTH INDIA 395

TA

BL

EII

IMP

OR

TA

NT

EV

EN

TS

INL

AN

DR

EF

OR

MS

ININ

DIA

NS

TA

TE

SS

INC

E19

50

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

And

hra

Pra

desh

1950 (a

men

ded

1954

)

(Tel

enga

na

Are

a)Te

nanc

yan

dA

gri-

cult

ura

lLan

dsA

ctTe

nan

tsre

ceiv

edpr

otec

ted

ten

ancy

stat

ust

enan

tsto

hav

em

inim

um

term

ofle

ase

righ

tof

purc

hase

ofn

onre

sum

able

lan

dst

rans

fer

ofow

ner

ship

topr

otec

ted

ten

ants

inre

spec

tof

non

resu

mab

lela

nds

as

are

sult

136

11pr

otec

ted

ten

ants

decl

ared

own

ers

1

1952

Hyd

erab

adA

boli

tion

ofC

ash

Gra

nts

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tele

nga

na

2

1954

Inam

Abo

liti

onA

ct(a

bsor

bed)

encl

aves

Abo

liti

onof

inam

s(w

ith

few

exce

ptio

ns)

2

1955

(Hyd

erab

adJa

gird

ars)

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tal

enga

na

219

56In

am(A

boli

tion

and

Con

vers

ion

into

Ryo

twar

i)A

ctA

cqu

isit

ion

of11

137

esta

tes

abol

itio

nof

106

mil

lion

min

orin

ams

2

1956 (a

men

ded

1974

)

Ten

ancy

Act

Ten

ancy

con

tin

ues

up

to2

3of

ceil

ing

area

law

does

not

prov

ide

for

con

fer-

men

tof

own

ersh

ipri

ght

onte

nant

sex

cept

thro

ugh

righ

tto

purc

has

eco

nfe

rsco

ntin

uou

sri

ght

ofre

sum

ptio

non

lan

dow

ner

s

1

1957

Inam

Abo

liti

onA

ctA

boli

tion

ofin

ams

(wit

hfe

wex

cept

ions

)st

ruck

dow

nby

the

Hig

hC

ourt

in19

70

2

Ass

am19

51S

tate

Acq

uis

itio

nof

Zam

inda

riA

ctA

boli

tion

ofin

term

edia

ryri

ghts

invo

lvin

g0

67m

illi

onh

ecta

res

219

54L

ush

aiH

ills

Dis

tric

t(A

cqu

isit

ion

ofC

hie

fsR

igh

ts)A

ctS

ame

asab

ove

2

1956 (a

men

ded

1976

)

Fix

atio

nof

Cei

lin

gon

Lan

dH

oldi

ngs

Act

Sel

f-ex

plan

ator

y3

1960

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1971

Ten

ancy

Act

Cla

ssi

este

nan

tsin

tooc

cupa

ncy

and

non

occu

pan

cyte

nan

tsf

orm

erh

asse

curi

tyof

ten

ure

may

acqu

ire

lan

dlor

drsquos

righ

tof

hol

din

gby

payi

ng

50ti

mes

the

lan

dre

ven

ue

subl

etti

ngis

disa

llow

ed

1

QUARTERLY JOURNAL OF ECONOMICS396

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

tB

enga

l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

ace

ilin

gpr

ovid

edfo

rab

olit

ion

ofal

lin

term

edia

ryte

nur

es

12

3

1955 (a

men

ded

1970

197

119

77)

Lan

dR

efor

ms

Act

Pro

vide

sth

atla

ndow

ner

can

resu

me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

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ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

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isio

ns

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ith

-dr

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evio

us

exem

ptio

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rovi

ded

for

regu

lato

rym

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res

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indi

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min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

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ries

(15

ten

ancy

refo

rm

25

abol

itio

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iari

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35

ceil

ings

onla

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wh

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ion

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ryot

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stem

sdi

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ize

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rmed

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ough

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san

dm

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ave

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gan

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ders

and

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into

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and

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nd

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ure

syst

ems

QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 3: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

in credit markets and foster accumulation decisions thus under-mining the standard equity efficiency trade-off If accumulation isenhanced by redistribution along the growth path then we wouldexpect to nd a positive relationship between redistributiveefforts and economic growth The existing literature has focusedpredominantly on scal redistributions By affecting access toland land reform may have a more lasting effect on poverty Thisview is consistent with the literature that points to early redistri-butions of land leading to relatively egalitarian access as being animportant precondition for high growth in East Asia (see forexample Rodrik 1995)

Most existing empirical evidence on the links between redis-tribution and growth comes from cross-country data (see Perotti1996 for a careful review) While informative there are insur-mountable problems of comparability of data across countries anddealing with concerns about endogeneity The fact that our datacome from one country with similar data collection strategies ineach state and the relatively long time period allow us to makeprogress on this

Empirical studies of the impact of land reform are rare sincereliable estimation requires data from the pre- and postreformperiods In India there are numerous case studies of land reform(reviewed below) but few attempts to look at the overall pictureDiscussion of the theoretical impact of land reform has beendominated by the frequently found inverse farm size-productivityrelationship whence small farmers are supposed to achievehigher yields (see Binswanger et al 1995) This suggests thatnding means of evening the distribution of landholding shouldlead to productivity gains in addition to redistributive benetsHowever land reforms in India are rarely of a form that coulddirectly exploit this possibility Moreover careful analyses suchas Banerjee and Ghatak 1997 show that the theoretical effectson productivity are inherently ambiguous when assessing theimpact of tenancy reforms that allow tenants greater security

Our main nding is that there is a robust link between landreform and poverty reduction Closer scrutiny reveals that in anIndian context this is due primarily to land reforms that changethe terms of land contracts rather than actually redistributingland Consistent with the antipoverty impact we nd that landreform has raised agricultural wages The impact of land reformon growth also depends upon the type of land reform Overallthere is some evidence that the gain in poverty reduction did come

LAND POVERTY AND GROWTH INDIA 391

at the expense of lower income per capita We show that all ofthese results are consistent with a simple model of agriculturalcontracting

The remainder of the paper is organized as follows The nextsection discusses background and data issues Section III exam-ines the impact that land reforms have had on poverty and dealswith potential problems in interpreting the basic results SectionIV addresses the issue as to whether land reforms can havegeneral equilibrium effects by examining their impact on agricul-tural wages Section V then turns to the issue of how land reformshave affected economic growth In Section VI we examine theextent to which land reforms have been redistributive in terms oftheir effect on the distribution of land and income In Section VIIwe develop a theoretical framework that allows us to interpret ourresults in the light of the literature on agricultural contractingSection VIII concludes A Data Appendix details the constructionand sources of the key variables used in the analysis

II BACKGROUND AND DATA

Under the 1949 Indian Constitution states were granted thepowers to enact (and implement) land reforms This autonomyensures that there has been signicant variation across statesand time in terms of the number and types of land reforms thathave been enacted (see Table I) We classify land reform acts intofour main categories according to their main purpose (see Mearns1998) The rst category is acts related to tenancy reform Theseinclude attempts to regulate tenancy contracts both via registra-tion and stipulation of contractual terms such as shares in sharetenancy contracts as well as attempts to abolish tenancy andtransfer ownership to tenants The second category of land reformacts are attempts to abolish intermediaries These intermediarieswho worked under feudal lords (Zamandari) to collect rent for theBritish were reputed to allow a larger share of the surplus fromthe land to be extracted from tenants Most states had passedlegislation to abolish intermediaries prior to 1958 However ve(Gujarat Kerala Orissa Rajasthan and Uttar Pradesh) did soduring our data period The third category of land reform actsconcerned efforts to implement ceilings on landholdings with aview to redistributing surplus land to the landless Finally wehave acts that attempted to allow consolidation of disparatelandholdings Although these reforms in particular the latter

QUARTERLY JOURNAL OF ECONOMICS392

TAB

LE

IS

UM

MA

RY

OF

MA

INVA

RIA

BL

ES

Sta

te

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Agr

icu

ltu

ral

wag

es

Sta

tein

com

epe

rca

pita

Agr

icu

l-tu

ral

yiel

d

Cu

mu

lati

veto

tall

and

refo

rmle

gisl

atio

n

Cu

mu

lati

vete

nan

cyre

form

legi

slat

ion

Cu

mu

lati

veab

olit

ion

inte

rmed

iari

esle

gisl

atio

n

Cum

ula

tive

land

ceil

ings

legi

slat

ion

Cu

mu

lati

vela

nd

con

soli

dati

onle

gisl

atio

n

And

raP

rade

sh14

87

505

94

5310

0433

40

152

80

528

100

00

0(5

11)

(11

61)

(11

0)(2

60)

(33

11)

(05

06)

(05

06)

(0)

(0)

(0)

Ass

am10

69

489

15

3590

350

54

200

00

611

00

472

091

6(2

67)

(91

6)(1

04)

(196

)(3

759

)(1

069

)(0

494

)(0

)(0

506

)(0

280

)B

ihar

208

864

65

407

633

426

44

305

263

90

166

70

(46

7)(6

40)

(10

1)(1

10)

(39

95)

(19

24)

(09

30)

(0)

(10

42)

(0)

Gu

jara

t15

81

534

94

3911

7625

21

305

61

472

066

70

917

0(4

94)

(99

9)(0

78)

(272

)(2

384

)(1

264

)(0

654

)(0

478

)(0

280

)(0

)H

arya

na7

1130

00

mdash14

4423

22

00

00

0(2

15)

(69

0)(3

57)

(20

46)

(0)

(0)

(0)

(0)

(0)

Jam

mu

and

720

345

5mdash

1021

515

31

333

047

20

00

861

Kas

hm

ir(2

59)

(81

3)(2

28)

(43

28)

(07

17)

(05

06)

(0)

(0)

(03

51)

Kar

nat

aka

169

954

46

385

1037

252

62

833

141

70

141

70

(38

6)(8

08)

(06

6)(2

16)

(24

26)

(13

84)

(06

92)

(0)

(06

92)

(0)

Ker

ala

197

056

92

624

864

657

55

444

241

71

972

105

60

(79

8)(1

453

)(1

56)

(182

)(6

026

)(3

376

)(1

556

)(1

000

)(0

860

)(0

)M

adh

ya18

03

572

63

8184

317

01

280

60

944

00

917

094

4P

rade

sh(4

11)

(74

5)(0

83)

(190

)(1

607

)(0

710

)(0

232

)(0

)(0

280

)(0

232

)M

ahar

ash

tra

197

163

82

355

1288

208

41

861

097

20

088

90

(43

8)(9

64)

(07

1)(3

31)

(20

57)

(04

24)

(16

67)

(0)

(03

19)

(0)

Ori

ssa

174

256

63

407

873

250

65

056

194

40

583

194

40

583

(46

2)(9

53)

(08

5)(1

86)

(20

23)

(31

16)

(10

93)

(05

00)

(10

93)

(05

00)

Pu

nja

b6

1426

22

816

1732

345

50

583

058

30

00

(28

8)(8

23)

(10

9)(3

84)

(29

70)

(05

00)

(05

00)

(0)

(0)

(0)

Raj

asth

an16

96

534

15

1278

516

27

094

40

094

40

0(3

81)

(74

8)(0

68)

(136

)(1

575

)(0

232

)(0

)(0

232

)(0

)(0

)Ta

mil

Nad

u18

58

580

43

9210

1536

59

491

74

028

00

889

0(4

40)

(85

6)(0

52)

(272

)(3

266

)(2

545

)(2

336

)(0

)(0

319

)(0

)U

ttar

Pra

desh

128

446

70

471

874

464

375

01

417

141

70

917

0(3

14)

(76

8)(1

38)

(140

)(3

823

)(1

251

)(0

554

)(0

554

)(0

280

)(0

)W

est

Ben

gal

149

251

48

612

1173

605

96

139

383

30

061

11

694

(53

2)(1

242

)(1

81)

(191

)(5

720

)(5

581

)(3

476

)(0

)(0

993

)(1

369

)T

OTA

L15

01

507

94

799

1030

354

92

910

145

50

411

073

10

312

(62

8)(1

408

)(1

584

)(3

46)

(37

36)

(27

49)

(17

07)

(06

92)

(08

25)

(06

35)

Sta

nda

rdd

evia

tion

sar

ein

pare

nth

eses

mdashde

not

esa

mis

sin

gva

riab

leS

eeth

eD

ata

App

end

ixfo

rd

etai

lson

con

stru

ctio

nan

dso

urc

esof

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

H

arya

na

spli

tfr

omth

est

ate

ofP

un

jab

in19

65F

rom

this

dat

eon

we

incl

ud

ese

para

teob

serv

atio

ns

for

Pu

nja

ban

dH

arya

na

Th

eex

cep

tion

isru

ral

wag

esw

her

eth

ere

isn

ose

para

tese

ries

for

Har

yan

aor

for

Jam

mu

and

Kas

hm

irS

tate

inco

me

per

cap

ita

isob

tain

edby

exp

ress

ing

esti

mat

esof

stat

edo

mes

tic

prod

uct

inre

alpe

rca

pit

ate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pre

sen

tth

era

tio

ofre

alag

ricu

ltu

ral

stat

edo

mes

tic

pro

duct

ton

etso

wn

area

mea

sure

din

thou

san

dsof

hec

tare

sT

he

wag

ed

ata

refe

rto

the

dail

yw

age

rate

for

mal

eag

ricu

ltu

rall

abor

ers

and

isex

pres

sed

inre

alte

rms

LAND POVERTY AND GROWTH INDIA 393

were justied partly in terms of achieving efficiency gains inagriculture it is clear from the acts themselves and from thepolitical manifestos supporting the acts that the main impetusdriving the rst three reforms was poverty reduction It istherefore interesting to assess whether these reforms were effec-tive in achieving their stated aims

Existing assessments of the effectiveness of these differentreforms are highly mixed Although promoted by the center invarious Five Year Plans the fact that land reforms were a statesubject under the 1949 Constitution meant that enactment andimplementation was dependent on the political will of stategovernments Bandyopadhyay 1986 Radhakrishnan 1990 Appu1996 Behuria 1997 Mearns 1998 The perceived oppressivecharacter of the Zamandari (and their intermediaries) and theirclose alliance with the British galvanized broad political supportfor the abolition of intermediaries and led to widespread implemen-tation of these reforms most of which were complete by the early1960s Appu 1996 Mearns 19981 Centre-state alignment on theissue of tenancy reforms was much less pronounced2 With manystate legislatures controlled by the landlord class reforms thatharmed this class tended to be blocked although where tenantshad substantial political representation notable successes inimplementation were recorded Despite the considerable publicityattached to their enactment political failure to implement wasmost complete in the case of land ceiling legislation Hereambivalence in the formulation of policy and numerous loopholesallowed the bulk of landowners to avoid expropriation by distrib-uting surplus land to relations friends and dependents Appu1996 Mearns 1998 As a result of these problems implementa-tion of both tenancy reform and land ceiling legislation tended tolag well behind the targets set in the Five Year Plans Bandy-opadhyay 1986 Radhakrishnan 19903 Land consolidation legis-lation was enacted less than the other reforms and owing partly

1 There were nonetheless some major design aws most notably the failureto limit the size of home farms of Zamindars or to protect short-term tenants

2 Warriner 1969 commented that the Congress party (the main politicalforce for most of our period) lsquolsquoprovided both the motivation for land reform and theopposition to it as a socialist head with a conservative bodyrsquorsquo

3 The Fifth Plan gives a frank assessmentof the situation which is directly inline with that of Bardhan 1970 lsquolsquoA broad assessment of the programme of landreform adopted since Independence is that the laws for the abolition of intermedi-ary tenures have been implemented fairly efficiently whilst in the elds of tenancyreforms and ceilings on holdings legislation has fallen short of the desiredobjectives and implementation of the enacted laws has been inadequatersquorsquo FifthFive Year Plan 1974ndash79 2 43

QUARTERLY JOURNAL OF ECONOMICS394

to the sparseness of land records implementation has beenconsidered to be both sporadic and patchy only affecting a fewstates in any signicant way Radhakrishnan 1990 Appu 1996Behuria 1997 Mearns 1998

Village level studies also offer a very mixed assessment of thepoverty impact of different land reforms (see Jayaraman andLanjouw 1997) Similar reforms seemed to have produced differ-ent effects in different areas leaving overall impact indeterminateThere is some consensus that the abolition of intermediariesachieved a limited and variable success both in redistributingland toward the poor and increasing the security of smallholders(see eg Wadley and Derr 1990) For tenancy reform howeverwhereas successes have been recorded in particular wheretenants are well organized there has also been a range ofdocumented cases of imminent legislation prompting landlords toengage in mass evictions of tenants and of the de jure banning oflandlord-tenant relationships pushing tenancy underground andtherefore paradoxically reducing tenurial security (see egGough 1989) Land ceiling legislation in a variety of villagestudies is also perceived to have had neutral or negative effects onpoverty by inducing landowners from joint families to evict theirtenants and to separate their holdings into smaller proprietaryunits among family members as a means of avoiding expropria-tion (see eg Chattopadhyay 1994) Land consolidation is alsoon the whole judged not to have been progressive in its redistribu-tive impact given that richer farmers tend to use their power toobtain improved holdings (see eg Dreze Lanjouw and Sharma1998)

Table II gives a complete picture of land reform legislationand its classication during our data period Our empiricalanalysis aggregates reforms within each category If land reformshave any effect then we doubt that this would be instantaneousThus we cumulate land reforms over time generating a variablethat aggregates the number of legislative reforms to date in anyparticular state While crude we believe that it provides asensible rst pass at analyzing the quantitative effects of landreform The mean of that variable aggregated across the fourcategories of land reform is given in column 6 of Table I Similarmeans for the different categories of reform are given in columns7ndash10 The table demonstrates considerable variation in overallland reform activity across states with states such as Uttar

LAND POVERTY AND GROWTH INDIA 395

TA

BL

EII

IMP

OR

TA

NT

EV

EN

TS

INL

AN

DR

EF

OR

MS

ININ

DIA

NS

TA

TE

SS

INC

E19

50

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

And

hra

Pra

desh

1950 (a

men

ded

1954

)

(Tel

enga

na

Are

a)Te

nanc

yan

dA

gri-

cult

ura

lLan

dsA

ctTe

nan

tsre

ceiv

edpr

otec

ted

ten

ancy

stat

ust

enan

tsto

hav

em

inim

um

term

ofle

ase

righ

tof

purc

hase

ofn

onre

sum

able

lan

dst

rans

fer

ofow

ner

ship

topr

otec

ted

ten

ants

inre

spec

tof

non

resu

mab

lela

nds

as

are

sult

136

11pr

otec

ted

ten

ants

decl

ared

own

ers

1

1952

Hyd

erab

adA

boli

tion

ofC

ash

Gra

nts

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tele

nga

na

2

1954

Inam

Abo

liti

onA

ct(a

bsor

bed)

encl

aves

Abo

liti

onof

inam

s(w

ith

few

exce

ptio

ns)

2

1955

(Hyd

erab

adJa

gird

ars)

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tal

enga

na

219

56In

am(A

boli

tion

and

Con

vers

ion

into

Ryo

twar

i)A

ctA

cqu

isit

ion

of11

137

esta

tes

abol

itio

nof

106

mil

lion

min

orin

ams

2

1956 (a

men

ded

1974

)

Ten

ancy

Act

Ten

ancy

con

tin

ues

up

to2

3of

ceil

ing

area

law

does

not

prov

ide

for

con

fer-

men

tof

own

ersh

ipri

ght

onte

nant

sex

cept

thro

ugh

righ

tto

purc

has

eco

nfe

rsco

ntin

uou

sri

ght

ofre

sum

ptio

non

lan

dow

ner

s

1

1957

Inam

Abo

liti

onA

ctA

boli

tion

ofin

ams

(wit

hfe

wex

cept

ions

)st

ruck

dow

nby

the

Hig

hC

ourt

in19

70

2

Ass

am19

51S

tate

Acq

uis

itio

nof

Zam

inda

riA

ctA

boli

tion

ofin

term

edia

ryri

ghts

invo

lvin

g0

67m

illi

onh

ecta

res

219

54L

ush

aiH

ills

Dis

tric

t(A

cqu

isit

ion

ofC

hie

fsR

igh

ts)A

ctS

ame

asab

ove

2

1956 (a

men

ded

1976

)

Fix

atio

nof

Cei

lin

gon

Lan

dH

oldi

ngs

Act

Sel

f-ex

plan

ator

y3

1960

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1971

Ten

ancy

Act

Cla

ssi

este

nan

tsin

tooc

cupa

ncy

and

non

occu

pan

cyte

nan

tsf

orm

erh

asse

curi

tyof

ten

ure

may

acqu

ire

lan

dlor

drsquos

righ

tof

hol

din

gby

payi

ng

50ti

mes

the

lan

dre

ven

ue

subl

etti

ngis

disa

llow

ed

1

QUARTERLY JOURNAL OF ECONOMICS396

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

tB

enga

l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

ace

ilin

gpr

ovid

edfo

rab

olit

ion

ofal

lin

term

edia

ryte

nur

es

12

3

1955 (a

men

ded

1970

197

119

77)

Lan

dR

efor

ms

Act

Pro

vide

sth

atla

ndow

ner

can

resu

me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

ceil

ing

prov

isio

ns

byw

ith

-dr

awin

gpr

evio

us

exem

ptio

nsp

rovi

ded

for

regu

lato

rym

easu

res

toch

eck

indi

scri

min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

tego

ries

(15

ten

ancy

refo

rm

25

abol

itio

nof

inte

rmed

iari

es

35

ceil

ings

onla

ndh

oldi

ngs

4

5co

nso

lida

tion

ofla

nd

hol

din

gs)

wh

ere

itis

poss

ible

for

agi

ven

act

tobe

lon

gto

mor

eth

anon

eca

tego

ryI

nth

eza

man

dar

ilan

dte

nu

resy

stem

wh

ich

cove

red

56p

erce

nt

ofpr

ivat

ely

own

edla

nd

inB

riti

shIn

dia

the

lan

dw

asve

sted

inth

ela

nd

lord

know

nas

Zam

inda

rB

etw

een

him

and

the

real

cult

ivat

orth

ere

wer

ese

vera

llay

ers

ofre

ntr

ecei

vin

gin

term

edia

ries

Jag

irs

and

inam

sw

ere

free

gran

tsof

subg

ran

tsfr

omth

est

ate

wit

hth

eri

ght

toco

llec

tan

dap

prop

riat

ela

nd

reve

nu

eth

ough

wit

hth

epa

ssag

eof

tim

eja

gird

ars

and

inam

dars

beca

me

the

virt

ual

own

ers

Inth

eir

con

cept

ion

the

ryot

war

ian

dm

ahal

war

ilan

dte

nu

resy

stem

sdi

dn

otre

cogn

ize

any

inte

rmed

iary

betw

een

the

stat

ean

dth

ecu

ltiv

ator

(th

ough

ryot

san

dm

ahal

sdi

dh

ave

full

righ

tsto

sale

le

asin

gan

dtr

ansf

erof

lan

d)I

n

ltra

tion

ofm

oney

len

ders

and

trad

ers

into

agri

cult

ure

and

the

leas

eof

them

tote

nan

tsle

dto

crea

tion

ofan

inte

rmed

iary

clas

sev

enin

area

sty

pi

edby

thes

ela

nd

ten

ure

syst

ems

QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 4: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

at the expense of lower income per capita We show that all ofthese results are consistent with a simple model of agriculturalcontracting

The remainder of the paper is organized as follows The nextsection discusses background and data issues Section III exam-ines the impact that land reforms have had on poverty and dealswith potential problems in interpreting the basic results SectionIV addresses the issue as to whether land reforms can havegeneral equilibrium effects by examining their impact on agricul-tural wages Section V then turns to the issue of how land reformshave affected economic growth In Section VI we examine theextent to which land reforms have been redistributive in terms oftheir effect on the distribution of land and income In Section VIIwe develop a theoretical framework that allows us to interpret ourresults in the light of the literature on agricultural contractingSection VIII concludes A Data Appendix details the constructionand sources of the key variables used in the analysis

II BACKGROUND AND DATA

Under the 1949 Indian Constitution states were granted thepowers to enact (and implement) land reforms This autonomyensures that there has been signicant variation across statesand time in terms of the number and types of land reforms thathave been enacted (see Table I) We classify land reform acts intofour main categories according to their main purpose (see Mearns1998) The rst category is acts related to tenancy reform Theseinclude attempts to regulate tenancy contracts both via registra-tion and stipulation of contractual terms such as shares in sharetenancy contracts as well as attempts to abolish tenancy andtransfer ownership to tenants The second category of land reformacts are attempts to abolish intermediaries These intermediarieswho worked under feudal lords (Zamandari) to collect rent for theBritish were reputed to allow a larger share of the surplus fromthe land to be extracted from tenants Most states had passedlegislation to abolish intermediaries prior to 1958 However ve(Gujarat Kerala Orissa Rajasthan and Uttar Pradesh) did soduring our data period The third category of land reform actsconcerned efforts to implement ceilings on landholdings with aview to redistributing surplus land to the landless Finally wehave acts that attempted to allow consolidation of disparatelandholdings Although these reforms in particular the latter

QUARTERLY JOURNAL OF ECONOMICS392

TAB

LE

IS

UM

MA

RY

OF

MA

INVA

RIA

BL

ES

Sta

te

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Agr

icu

ltu

ral

wag

es

Sta

tein

com

epe

rca

pita

Agr

icu

l-tu

ral

yiel

d

Cu

mu

lati

veto

tall

and

refo

rmle

gisl

atio

n

Cu

mu

lati

vete

nan

cyre

form

legi

slat

ion

Cu

mu

lati

veab

olit

ion

inte

rmed

iari

esle

gisl

atio

n

Cum

ula

tive

land

ceil

ings

legi

slat

ion

Cu

mu

lati

vela

nd

con

soli

dati

onle

gisl

atio

n

And

raP

rade

sh14

87

505

94

5310

0433

40

152

80

528

100

00

0(5

11)

(11

61)

(11

0)(2

60)

(33

11)

(05

06)

(05

06)

(0)

(0)

(0)

Ass

am10

69

489

15

3590

350

54

200

00

611

00

472

091

6(2

67)

(91

6)(1

04)

(196

)(3

759

)(1

069

)(0

494

)(0

)(0

506

)(0

280

)B

ihar

208

864

65

407

633

426

44

305

263

90

166

70

(46

7)(6

40)

(10

1)(1

10)

(39

95)

(19

24)

(09

30)

(0)

(10

42)

(0)

Gu

jara

t15

81

534

94

3911

7625

21

305

61

472

066

70

917

0(4

94)

(99

9)(0

78)

(272

)(2

384

)(1

264

)(0

654

)(0

478

)(0

280

)(0

)H

arya

na7

1130

00

mdash14

4423

22

00

00

0(2

15)

(69

0)(3

57)

(20

46)

(0)

(0)

(0)

(0)

(0)

Jam

mu

and

720

345

5mdash

1021

515

31

333

047

20

00

861

Kas

hm

ir(2

59)

(81

3)(2

28)

(43

28)

(07

17)

(05

06)

(0)

(0)

(03

51)

Kar

nat

aka

169

954

46

385

1037

252

62

833

141

70

141

70

(38

6)(8

08)

(06

6)(2

16)

(24

26)

(13

84)

(06

92)

(0)

(06

92)

(0)

Ker

ala

197

056

92

624

864

657

55

444

241

71

972

105

60

(79

8)(1

453

)(1

56)

(182

)(6

026

)(3

376

)(1

556

)(1

000

)(0

860

)(0

)M

adh

ya18

03

572

63

8184

317

01

280

60

944

00

917

094

4P

rade

sh(4

11)

(74

5)(0

83)

(190

)(1

607

)(0

710

)(0

232

)(0

)(0

280

)(0

232

)M

ahar

ash

tra

197

163

82

355

1288

208

41

861

097

20

088

90

(43

8)(9

64)

(07

1)(3

31)

(20

57)

(04

24)

(16

67)

(0)

(03

19)

(0)

Ori

ssa

174

256

63

407

873

250

65

056

194

40

583

194

40

583

(46

2)(9

53)

(08

5)(1

86)

(20

23)

(31

16)

(10

93)

(05

00)

(10

93)

(05

00)

Pu

nja

b6

1426

22

816

1732

345

50

583

058

30

00

(28

8)(8

23)

(10

9)(3

84)

(29

70)

(05

00)

(05

00)

(0)

(0)

(0)

Raj

asth

an16

96

534

15

1278

516

27

094

40

094

40

0(3

81)

(74

8)(0

68)

(136

)(1

575

)(0

232

)(0

)(0

232

)(0

)(0

)Ta

mil

Nad

u18

58

580

43

9210

1536

59

491

74

028

00

889

0(4

40)

(85

6)(0

52)

(272

)(3

266

)(2

545

)(2

336

)(0

)(0

319

)(0

)U

ttar

Pra

desh

128

446

70

471

874

464

375

01

417

141

70

917

0(3

14)

(76

8)(1

38)

(140

)(3

823

)(1

251

)(0

554

)(0

554

)(0

280

)(0

)W

est

Ben

gal

149

251

48

612

1173

605

96

139

383

30

061

11

694

(53

2)(1

242

)(1

81)

(191

)(5

720

)(5

581

)(3

476

)(0

)(0

993

)(1

369

)T

OTA

L15

01

507

94

799

1030

354

92

910

145

50

411

073

10

312

(62

8)(1

408

)(1

584

)(3

46)

(37

36)

(27

49)

(17

07)

(06

92)

(08

25)

(06

35)

Sta

nda

rdd

evia

tion

sar

ein

pare

nth

eses

mdashde

not

esa

mis

sin

gva

riab

leS

eeth

eD

ata

App

end

ixfo

rd

etai

lson

con

stru

ctio

nan

dso

urc

esof

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

H

arya

na

spli

tfr

omth

est

ate

ofP

un

jab

in19

65F

rom

this

dat

eon

we

incl

ud

ese

para

teob

serv

atio

ns

for

Pu

nja

ban

dH

arya

na

Th

eex

cep

tion

isru

ral

wag

esw

her

eth

ere

isn

ose

para

tese

ries

for

Har

yan

aor

for

Jam

mu

and

Kas

hm

irS

tate

inco

me

per

cap

ita

isob

tain

edby

exp

ress

ing

esti

mat

esof

stat

edo

mes

tic

prod

uct

inre

alpe

rca

pit

ate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pre

sen

tth

era

tio

ofre

alag

ricu

ltu

ral

stat

edo

mes

tic

pro

duct

ton

etso

wn

area

mea

sure

din

thou

san

dsof

hec

tare

sT

he

wag

ed

ata

refe

rto

the

dail

yw

age

rate

for

mal

eag

ricu

ltu

rall

abor

ers

and

isex

pres

sed

inre

alte

rms

LAND POVERTY AND GROWTH INDIA 393

were justied partly in terms of achieving efficiency gains inagriculture it is clear from the acts themselves and from thepolitical manifestos supporting the acts that the main impetusdriving the rst three reforms was poverty reduction It istherefore interesting to assess whether these reforms were effec-tive in achieving their stated aims

Existing assessments of the effectiveness of these differentreforms are highly mixed Although promoted by the center invarious Five Year Plans the fact that land reforms were a statesubject under the 1949 Constitution meant that enactment andimplementation was dependent on the political will of stategovernments Bandyopadhyay 1986 Radhakrishnan 1990 Appu1996 Behuria 1997 Mearns 1998 The perceived oppressivecharacter of the Zamandari (and their intermediaries) and theirclose alliance with the British galvanized broad political supportfor the abolition of intermediaries and led to widespread implemen-tation of these reforms most of which were complete by the early1960s Appu 1996 Mearns 19981 Centre-state alignment on theissue of tenancy reforms was much less pronounced2 With manystate legislatures controlled by the landlord class reforms thatharmed this class tended to be blocked although where tenantshad substantial political representation notable successes inimplementation were recorded Despite the considerable publicityattached to their enactment political failure to implement wasmost complete in the case of land ceiling legislation Hereambivalence in the formulation of policy and numerous loopholesallowed the bulk of landowners to avoid expropriation by distrib-uting surplus land to relations friends and dependents Appu1996 Mearns 1998 As a result of these problems implementa-tion of both tenancy reform and land ceiling legislation tended tolag well behind the targets set in the Five Year Plans Bandy-opadhyay 1986 Radhakrishnan 19903 Land consolidation legis-lation was enacted less than the other reforms and owing partly

1 There were nonetheless some major design aws most notably the failureto limit the size of home farms of Zamindars or to protect short-term tenants

2 Warriner 1969 commented that the Congress party (the main politicalforce for most of our period) lsquolsquoprovided both the motivation for land reform and theopposition to it as a socialist head with a conservative bodyrsquorsquo

3 The Fifth Plan gives a frank assessmentof the situation which is directly inline with that of Bardhan 1970 lsquolsquoA broad assessment of the programme of landreform adopted since Independence is that the laws for the abolition of intermedi-ary tenures have been implemented fairly efficiently whilst in the elds of tenancyreforms and ceilings on holdings legislation has fallen short of the desiredobjectives and implementation of the enacted laws has been inadequatersquorsquo FifthFive Year Plan 1974ndash79 2 43

QUARTERLY JOURNAL OF ECONOMICS394

to the sparseness of land records implementation has beenconsidered to be both sporadic and patchy only affecting a fewstates in any signicant way Radhakrishnan 1990 Appu 1996Behuria 1997 Mearns 1998

Village level studies also offer a very mixed assessment of thepoverty impact of different land reforms (see Jayaraman andLanjouw 1997) Similar reforms seemed to have produced differ-ent effects in different areas leaving overall impact indeterminateThere is some consensus that the abolition of intermediariesachieved a limited and variable success both in redistributingland toward the poor and increasing the security of smallholders(see eg Wadley and Derr 1990) For tenancy reform howeverwhereas successes have been recorded in particular wheretenants are well organized there has also been a range ofdocumented cases of imminent legislation prompting landlords toengage in mass evictions of tenants and of the de jure banning oflandlord-tenant relationships pushing tenancy underground andtherefore paradoxically reducing tenurial security (see egGough 1989) Land ceiling legislation in a variety of villagestudies is also perceived to have had neutral or negative effects onpoverty by inducing landowners from joint families to evict theirtenants and to separate their holdings into smaller proprietaryunits among family members as a means of avoiding expropria-tion (see eg Chattopadhyay 1994) Land consolidation is alsoon the whole judged not to have been progressive in its redistribu-tive impact given that richer farmers tend to use their power toobtain improved holdings (see eg Dreze Lanjouw and Sharma1998)

Table II gives a complete picture of land reform legislationand its classication during our data period Our empiricalanalysis aggregates reforms within each category If land reformshave any effect then we doubt that this would be instantaneousThus we cumulate land reforms over time generating a variablethat aggregates the number of legislative reforms to date in anyparticular state While crude we believe that it provides asensible rst pass at analyzing the quantitative effects of landreform The mean of that variable aggregated across the fourcategories of land reform is given in column 6 of Table I Similarmeans for the different categories of reform are given in columns7ndash10 The table demonstrates considerable variation in overallland reform activity across states with states such as Uttar

LAND POVERTY AND GROWTH INDIA 395

TA

BL

EII

IMP

OR

TA

NT

EV

EN

TS

INL

AN

DR

EF

OR

MS

ININ

DIA

NS

TA

TE

SS

INC

E19

50

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

And

hra

Pra

desh

1950 (a

men

ded

1954

)

(Tel

enga

na

Are

a)Te

nanc

yan

dA

gri-

cult

ura

lLan

dsA

ctTe

nan

tsre

ceiv

edpr

otec

ted

ten

ancy

stat

ust

enan

tsto

hav

em

inim

um

term

ofle

ase

righ

tof

purc

hase

ofn

onre

sum

able

lan

dst

rans

fer

ofow

ner

ship

topr

otec

ted

ten

ants

inre

spec

tof

non

resu

mab

lela

nds

as

are

sult

136

11pr

otec

ted

ten

ants

decl

ared

own

ers

1

1952

Hyd

erab

adA

boli

tion

ofC

ash

Gra

nts

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tele

nga

na

2

1954

Inam

Abo

liti

onA

ct(a

bsor

bed)

encl

aves

Abo

liti

onof

inam

s(w

ith

few

exce

ptio

ns)

2

1955

(Hyd

erab

adJa

gird

ars)

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tal

enga

na

219

56In

am(A

boli

tion

and

Con

vers

ion

into

Ryo

twar

i)A

ctA

cqu

isit

ion

of11

137

esta

tes

abol

itio

nof

106

mil

lion

min

orin

ams

2

1956 (a

men

ded

1974

)

Ten

ancy

Act

Ten

ancy

con

tin

ues

up

to2

3of

ceil

ing

area

law

does

not

prov

ide

for

con

fer-

men

tof

own

ersh

ipri

ght

onte

nant

sex

cept

thro

ugh

righ

tto

purc

has

eco

nfe

rsco

ntin

uou

sri

ght

ofre

sum

ptio

non

lan

dow

ner

s

1

1957

Inam

Abo

liti

onA

ctA

boli

tion

ofin

ams

(wit

hfe

wex

cept

ions

)st

ruck

dow

nby

the

Hig

hC

ourt

in19

70

2

Ass

am19

51S

tate

Acq

uis

itio

nof

Zam

inda

riA

ctA

boli

tion

ofin

term

edia

ryri

ghts

invo

lvin

g0

67m

illi

onh

ecta

res

219

54L

ush

aiH

ills

Dis

tric

t(A

cqu

isit

ion

ofC

hie

fsR

igh

ts)A

ctS

ame

asab

ove

2

1956 (a

men

ded

1976

)

Fix

atio

nof

Cei

lin

gon

Lan

dH

oldi

ngs

Act

Sel

f-ex

plan

ator

y3

1960

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1971

Ten

ancy

Act

Cla

ssi

este

nan

tsin

tooc

cupa

ncy

and

non

occu

pan

cyte

nan

tsf

orm

erh

asse

curi

tyof

ten

ure

may

acqu

ire

lan

dlor

drsquos

righ

tof

hol

din

gby

payi

ng

50ti

mes

the

lan

dre

ven

ue

subl

etti

ngis

disa

llow

ed

1

QUARTERLY JOURNAL OF ECONOMICS396

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

tB

enga

l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

ace

ilin

gpr

ovid

edfo

rab

olit

ion

ofal

lin

term

edia

ryte

nur

es

12

3

1955 (a

men

ded

1970

197

119

77)

Lan

dR

efor

ms

Act

Pro

vide

sth

atla

ndow

ner

can

resu

me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

ceil

ing

prov

isio

ns

byw

ith

-dr

awin

gpr

evio

us

exem

ptio

nsp

rovi

ded

for

regu

lato

rym

easu

res

toch

eck

indi

scri

min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

tego

ries

(15

ten

ancy

refo

rm

25

abol

itio

nof

inte

rmed

iari

es

35

ceil

ings

onla

ndh

oldi

ngs

4

5co

nso

lida

tion

ofla

nd

hol

din

gs)

wh

ere

itis

poss

ible

for

agi

ven

act

tobe

lon

gto

mor

eth

anon

eca

tego

ryI

nth

eza

man

dar

ilan

dte

nu

resy

stem

wh

ich

cove

red

56p

erce

nt

ofpr

ivat

ely

own

edla

nd

inB

riti

shIn

dia

the

lan

dw

asve

sted

inth

ela

nd

lord

know

nas

Zam

inda

rB

etw

een

him

and

the

real

cult

ivat

orth

ere

wer

ese

vera

llay

ers

ofre

ntr

ecei

vin

gin

term

edia

ries

Jag

irs

and

inam

sw

ere

free

gran

tsof

subg

ran

tsfr

omth

est

ate

wit

hth

eri

ght

toco

llec

tan

dap

prop

riat

ela

nd

reve

nu

eth

ough

wit

hth

epa

ssag

eof

tim

eja

gird

ars

and

inam

dars

beca

me

the

virt

ual

own

ers

Inth

eir

con

cept

ion

the

ryot

war

ian

dm

ahal

war

ilan

dte

nu

resy

stem

sdi

dn

otre

cogn

ize

any

inte

rmed

iary

betw

een

the

stat

ean

dth

ecu

ltiv

ator

(th

ough

ryot

san

dm

ahal

sdi

dh

ave

full

righ

tsto

sale

le

asin

gan

dtr

ansf

erof

lan

d)I

n

ltra

tion

ofm

oney

len

ders

and

trad

ers

into

agri

cult

ure

and

the

leas

eof

them

tote

nan

tsle

dto

crea

tion

ofan

inte

rmed

iary

clas

sev

enin

area

sty

pi

edby

thes

ela

nd

ten

ure

syst

ems

QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

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tpe

riod

sIV

2In

stru

men

tsfo

rth

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dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

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nd

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form

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ssed

inge

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phic

ally

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ous

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gged

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men

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nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

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gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 5: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TAB

LE

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UM

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RY

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RIA

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ES

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Sta

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rmle

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n

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Cum

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ings

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Cu

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nd

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soli

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atio

n

And

raP

rade

sh14

87

505

94

5310

0433

40

152

80

528

100

00

0(5

11)

(11

61)

(11

0)(2

60)

(33

11)

(05

06)

(05

06)

(0)

(0)

(0)

Ass

am10

69

489

15

3590

350

54

200

00

611

00

472

091

6(2

67)

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6)(1

04)

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)(3

759

)(1

069

)(0

494

)(0

)(0

506

)(0

280

)B

ihar

208

864

65

407

633

426

44

305

263

90

166

70

(46

7)(6

40)

(10

1)(1

10)

(39

95)

(19

24)

(09

30)

(0)

(10

42)

(0)

Gu

jara

t15

81

534

94

3911

7625

21

305

61

472

066

70

917

0(4

94)

(99

9)(0

78)

(272

)(2

384

)(1

264

)(0

654

)(0

478

)(0

280

)(0

)H

arya

na7

1130

00

mdash14

4423

22

00

00

0(2

15)

(69

0)(3

57)

(20

46)

(0)

(0)

(0)

(0)

(0)

Jam

mu

and

720

345

5mdash

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515

31

333

047

20

00

861

Kas

hm

ir(2

59)

(81

3)(2

28)

(43

28)

(07

17)

(05

06)

(0)

(0)

(03

51)

Kar

nat

aka

169

954

46

385

1037

252

62

833

141

70

141

70

(38

6)(8

08)

(06

6)(2

16)

(24

26)

(13

84)

(06

92)

(0)

(06

92)

(0)

Ker

ala

197

056

92

624

864

657

55

444

241

71

972

105

60

(79

8)(1

453

)(1

56)

(182

)(6

026

)(3

376

)(1

556

)(1

000

)(0

860

)(0

)M

adh

ya18

03

572

63

8184

317

01

280

60

944

00

917

094

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rade

sh(4

11)

(74

5)(0

83)

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607

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710

)(0

232

)(0

)(0

280

)(0

232

)M

ahar

ash

tra

197

163

82

355

1288

208

41

861

097

20

088

90

(43

8)(9

64)

(07

1)(3

31)

(20

57)

(04

24)

(16

67)

(0)

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19)

(0)

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ssa

174

256

63

407

873

250

65

056

194

40

583

194

40

583

(46

2)(9

53)

(08

5)(1

86)

(20

23)

(31

16)

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(05

00)

(10

93)

(05

00)

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nja

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1426

22

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50

583

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30

00

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(10

9)(3

84)

(29

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(05

00)

(05

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(0)

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asth

an16

96

534

15

1278

516

27

094

40

094

40

0(3

81)

(74

8)(0

68)

(136

)(1

575

)(0

232

)(0

)(0

232

)(0

)(0

)Ta

mil

Nad

u18

58

580

43

9210

1536

59

491

74

028

00

889

0(4

40)

(85

6)(0

52)

(272

)(3

266

)(2

545

)(2

336

)(0

)(0

319

)(0

)U

ttar

Pra

desh

128

446

70

471

874

464

375

01

417

141

70

917

0(3

14)

(76

8)(1

38)

(140

)(3

823

)(1

251

)(0

554

)(0

554

)(0

280

)(0

)W

est

Ben

gal

149

251

48

612

1173

605

96

139

383

30

061

11

694

(53

2)(1

242

)(1

81)

(191

)(5

720

)(5

581

)(3

476

)(0

)(0

993

)(1

369

)T

OTA

L15

01

507

94

799

1030

354

92

910

145

50

411

073

10

312

(62

8)(1

408

)(1

584

)(3

46)

(37

36)

(27

49)

(17

07)

(06

92)

(08

25)

(06

35)

Sta

nda

rdd

evia

tion

sar

ein

pare

nth

eses

mdashde

not

esa

mis

sin

gva

riab

leS

eeth

eD

ata

App

end

ixfo

rd

etai

lson

con

stru

ctio

nan

dso

urc

esof

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

H

arya

na

spli

tfr

omth

est

ate

ofP

un

jab

in19

65F

rom

this

dat

eon

we

incl

ud

ese

para

teob

serv

atio

ns

for

Pu

nja

ban

dH

arya

na

Th

eex

cep

tion

isru

ral

wag

esw

her

eth

ere

isn

ose

para

tese

ries

for

Har

yan

aor

for

Jam

mu

and

Kas

hm

irS

tate

inco

me

per

cap

ita

isob

tain

edby

exp

ress

ing

esti

mat

esof

stat

edo

mes

tic

prod

uct

inre

alpe

rca

pit

ate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pre

sen

tth

era

tio

ofre

alag

ricu

ltu

ral

stat

edo

mes

tic

pro

duct

ton

etso

wn

area

mea

sure

din

thou

san

dsof

hec

tare

sT

he

wag

ed

ata

refe

rto

the

dail

yw

age

rate

for

mal

eag

ricu

ltu

rall

abor

ers

and

isex

pres

sed

inre

alte

rms

LAND POVERTY AND GROWTH INDIA 393

were justied partly in terms of achieving efficiency gains inagriculture it is clear from the acts themselves and from thepolitical manifestos supporting the acts that the main impetusdriving the rst three reforms was poverty reduction It istherefore interesting to assess whether these reforms were effec-tive in achieving their stated aims

Existing assessments of the effectiveness of these differentreforms are highly mixed Although promoted by the center invarious Five Year Plans the fact that land reforms were a statesubject under the 1949 Constitution meant that enactment andimplementation was dependent on the political will of stategovernments Bandyopadhyay 1986 Radhakrishnan 1990 Appu1996 Behuria 1997 Mearns 1998 The perceived oppressivecharacter of the Zamandari (and their intermediaries) and theirclose alliance with the British galvanized broad political supportfor the abolition of intermediaries and led to widespread implemen-tation of these reforms most of which were complete by the early1960s Appu 1996 Mearns 19981 Centre-state alignment on theissue of tenancy reforms was much less pronounced2 With manystate legislatures controlled by the landlord class reforms thatharmed this class tended to be blocked although where tenantshad substantial political representation notable successes inimplementation were recorded Despite the considerable publicityattached to their enactment political failure to implement wasmost complete in the case of land ceiling legislation Hereambivalence in the formulation of policy and numerous loopholesallowed the bulk of landowners to avoid expropriation by distrib-uting surplus land to relations friends and dependents Appu1996 Mearns 1998 As a result of these problems implementa-tion of both tenancy reform and land ceiling legislation tended tolag well behind the targets set in the Five Year Plans Bandy-opadhyay 1986 Radhakrishnan 19903 Land consolidation legis-lation was enacted less than the other reforms and owing partly

1 There were nonetheless some major design aws most notably the failureto limit the size of home farms of Zamindars or to protect short-term tenants

2 Warriner 1969 commented that the Congress party (the main politicalforce for most of our period) lsquolsquoprovided both the motivation for land reform and theopposition to it as a socialist head with a conservative bodyrsquorsquo

3 The Fifth Plan gives a frank assessmentof the situation which is directly inline with that of Bardhan 1970 lsquolsquoA broad assessment of the programme of landreform adopted since Independence is that the laws for the abolition of intermedi-ary tenures have been implemented fairly efficiently whilst in the elds of tenancyreforms and ceilings on holdings legislation has fallen short of the desiredobjectives and implementation of the enacted laws has been inadequatersquorsquo FifthFive Year Plan 1974ndash79 2 43

QUARTERLY JOURNAL OF ECONOMICS394

to the sparseness of land records implementation has beenconsidered to be both sporadic and patchy only affecting a fewstates in any signicant way Radhakrishnan 1990 Appu 1996Behuria 1997 Mearns 1998

Village level studies also offer a very mixed assessment of thepoverty impact of different land reforms (see Jayaraman andLanjouw 1997) Similar reforms seemed to have produced differ-ent effects in different areas leaving overall impact indeterminateThere is some consensus that the abolition of intermediariesachieved a limited and variable success both in redistributingland toward the poor and increasing the security of smallholders(see eg Wadley and Derr 1990) For tenancy reform howeverwhereas successes have been recorded in particular wheretenants are well organized there has also been a range ofdocumented cases of imminent legislation prompting landlords toengage in mass evictions of tenants and of the de jure banning oflandlord-tenant relationships pushing tenancy underground andtherefore paradoxically reducing tenurial security (see egGough 1989) Land ceiling legislation in a variety of villagestudies is also perceived to have had neutral or negative effects onpoverty by inducing landowners from joint families to evict theirtenants and to separate their holdings into smaller proprietaryunits among family members as a means of avoiding expropria-tion (see eg Chattopadhyay 1994) Land consolidation is alsoon the whole judged not to have been progressive in its redistribu-tive impact given that richer farmers tend to use their power toobtain improved holdings (see eg Dreze Lanjouw and Sharma1998)

Table II gives a complete picture of land reform legislationand its classication during our data period Our empiricalanalysis aggregates reforms within each category If land reformshave any effect then we doubt that this would be instantaneousThus we cumulate land reforms over time generating a variablethat aggregates the number of legislative reforms to date in anyparticular state While crude we believe that it provides asensible rst pass at analyzing the quantitative effects of landreform The mean of that variable aggregated across the fourcategories of land reform is given in column 6 of Table I Similarmeans for the different categories of reform are given in columns7ndash10 The table demonstrates considerable variation in overallland reform activity across states with states such as Uttar

LAND POVERTY AND GROWTH INDIA 395

TA

BL

EII

IMP

OR

TA

NT

EV

EN

TS

INL

AN

DR

EF

OR

MS

ININ

DIA

NS

TA

TE

SS

INC

E19

50

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

And

hra

Pra

desh

1950 (a

men

ded

1954

)

(Tel

enga

na

Are

a)Te

nanc

yan

dA

gri-

cult

ura

lLan

dsA

ctTe

nan

tsre

ceiv

edpr

otec

ted

ten

ancy

stat

ust

enan

tsto

hav

em

inim

um

term

ofle

ase

righ

tof

purc

hase

ofn

onre

sum

able

lan

dst

rans

fer

ofow

ner

ship

topr

otec

ted

ten

ants

inre

spec

tof

non

resu

mab

lela

nds

as

are

sult

136

11pr

otec

ted

ten

ants

decl

ared

own

ers

1

1952

Hyd

erab

adA

boli

tion

ofC

ash

Gra

nts

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tele

nga

na

2

1954

Inam

Abo

liti

onA

ct(a

bsor

bed)

encl

aves

Abo

liti

onof

inam

s(w

ith

few

exce

ptio

ns)

2

1955

(Hyd

erab

adJa

gird

ars)

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tal

enga

na

219

56In

am(A

boli

tion

and

Con

vers

ion

into

Ryo

twar

i)A

ctA

cqu

isit

ion

of11

137

esta

tes

abol

itio

nof

106

mil

lion

min

orin

ams

2

1956 (a

men

ded

1974

)

Ten

ancy

Act

Ten

ancy

con

tin

ues

up

to2

3of

ceil

ing

area

law

does

not

prov

ide

for

con

fer-

men

tof

own

ersh

ipri

ght

onte

nant

sex

cept

thro

ugh

righ

tto

purc

has

eco

nfe

rsco

ntin

uou

sri

ght

ofre

sum

ptio

non

lan

dow

ner

s

1

1957

Inam

Abo

liti

onA

ctA

boli

tion

ofin

ams

(wit

hfe

wex

cept

ions

)st

ruck

dow

nby

the

Hig

hC

ourt

in19

70

2

Ass

am19

51S

tate

Acq

uis

itio

nof

Zam

inda

riA

ctA

boli

tion

ofin

term

edia

ryri

ghts

invo

lvin

g0

67m

illi

onh

ecta

res

219

54L

ush

aiH

ills

Dis

tric

t(A

cqu

isit

ion

ofC

hie

fsR

igh

ts)A

ctS

ame

asab

ove

2

1956 (a

men

ded

1976

)

Fix

atio

nof

Cei

lin

gon

Lan

dH

oldi

ngs

Act

Sel

f-ex

plan

ator

y3

1960

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1971

Ten

ancy

Act

Cla

ssi

este

nan

tsin

tooc

cupa

ncy

and

non

occu

pan

cyte

nan

tsf

orm

erh

asse

curi

tyof

ten

ure

may

acqu

ire

lan

dlor

drsquos

righ

tof

hol

din

gby

payi

ng

50ti

mes

the

lan

dre

ven

ue

subl

etti

ngis

disa

llow

ed

1

QUARTERLY JOURNAL OF ECONOMICS396

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

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ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

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ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

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ppu)

Act

Sam

eas

abov

e1

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arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

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tion

and

Lan

dR

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ms

Act

All

ten

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are

give

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ete

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rity

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mpt

ion

for

the

lan

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ses

inge

ner

ala

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law

pro-

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inda

ries

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min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

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lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

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mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

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l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

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ner

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ldch

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any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

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ilin

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olit

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lin

term

edia

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es

12

3

1955 (a

men

ded

1970

197

119

77)

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dR

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ms

Act

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vide

sth

atla

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ner

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me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

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enga

l(c

ont

)

1977

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dR

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ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

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ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

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prov

isio

ns

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ith

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rovi

ded

for

regu

lato

rym

easu

res

toch

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indi

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min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

tego

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(15

ten

ancy

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rm

25

abol

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rmed

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35

ceil

ings

onla

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act

tobe

lon

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eth

anon

eca

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erce

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inB

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the

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sted

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him

and

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orth

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wer

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and

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sw

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ate

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hth

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rmed

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ator

(th

ough

ryot

san

dm

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sdi

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ave

full

righ

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gan

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ansf

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d)I

n

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tion

ofm

oney

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ders

and

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into

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cult

ure

and

the

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eof

them

tote

nan

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tion

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inte

rmed

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clas

sev

enin

area

sty

pi

edby

thes

ela

nd

ten

ure

syst

ems

QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

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gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

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mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

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045

(12

5)2

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2(3

53)

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422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

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70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 6: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

were justied partly in terms of achieving efficiency gains inagriculture it is clear from the acts themselves and from thepolitical manifestos supporting the acts that the main impetusdriving the rst three reforms was poverty reduction It istherefore interesting to assess whether these reforms were effec-tive in achieving their stated aims

Existing assessments of the effectiveness of these differentreforms are highly mixed Although promoted by the center invarious Five Year Plans the fact that land reforms were a statesubject under the 1949 Constitution meant that enactment andimplementation was dependent on the political will of stategovernments Bandyopadhyay 1986 Radhakrishnan 1990 Appu1996 Behuria 1997 Mearns 1998 The perceived oppressivecharacter of the Zamandari (and their intermediaries) and theirclose alliance with the British galvanized broad political supportfor the abolition of intermediaries and led to widespread implemen-tation of these reforms most of which were complete by the early1960s Appu 1996 Mearns 19981 Centre-state alignment on theissue of tenancy reforms was much less pronounced2 With manystate legislatures controlled by the landlord class reforms thatharmed this class tended to be blocked although where tenantshad substantial political representation notable successes inimplementation were recorded Despite the considerable publicityattached to their enactment political failure to implement wasmost complete in the case of land ceiling legislation Hereambivalence in the formulation of policy and numerous loopholesallowed the bulk of landowners to avoid expropriation by distrib-uting surplus land to relations friends and dependents Appu1996 Mearns 1998 As a result of these problems implementa-tion of both tenancy reform and land ceiling legislation tended tolag well behind the targets set in the Five Year Plans Bandy-opadhyay 1986 Radhakrishnan 19903 Land consolidation legis-lation was enacted less than the other reforms and owing partly

1 There were nonetheless some major design aws most notably the failureto limit the size of home farms of Zamindars or to protect short-term tenants

2 Warriner 1969 commented that the Congress party (the main politicalforce for most of our period) lsquolsquoprovided both the motivation for land reform and theopposition to it as a socialist head with a conservative bodyrsquorsquo

3 The Fifth Plan gives a frank assessmentof the situation which is directly inline with that of Bardhan 1970 lsquolsquoA broad assessment of the programme of landreform adopted since Independence is that the laws for the abolition of intermedi-ary tenures have been implemented fairly efficiently whilst in the elds of tenancyreforms and ceilings on holdings legislation has fallen short of the desiredobjectives and implementation of the enacted laws has been inadequatersquorsquo FifthFive Year Plan 1974ndash79 2 43

QUARTERLY JOURNAL OF ECONOMICS394

to the sparseness of land records implementation has beenconsidered to be both sporadic and patchy only affecting a fewstates in any signicant way Radhakrishnan 1990 Appu 1996Behuria 1997 Mearns 1998

Village level studies also offer a very mixed assessment of thepoverty impact of different land reforms (see Jayaraman andLanjouw 1997) Similar reforms seemed to have produced differ-ent effects in different areas leaving overall impact indeterminateThere is some consensus that the abolition of intermediariesachieved a limited and variable success both in redistributingland toward the poor and increasing the security of smallholders(see eg Wadley and Derr 1990) For tenancy reform howeverwhereas successes have been recorded in particular wheretenants are well organized there has also been a range ofdocumented cases of imminent legislation prompting landlords toengage in mass evictions of tenants and of the de jure banning oflandlord-tenant relationships pushing tenancy underground andtherefore paradoxically reducing tenurial security (see egGough 1989) Land ceiling legislation in a variety of villagestudies is also perceived to have had neutral or negative effects onpoverty by inducing landowners from joint families to evict theirtenants and to separate their holdings into smaller proprietaryunits among family members as a means of avoiding expropria-tion (see eg Chattopadhyay 1994) Land consolidation is alsoon the whole judged not to have been progressive in its redistribu-tive impact given that richer farmers tend to use their power toobtain improved holdings (see eg Dreze Lanjouw and Sharma1998)

Table II gives a complete picture of land reform legislationand its classication during our data period Our empiricalanalysis aggregates reforms within each category If land reformshave any effect then we doubt that this would be instantaneousThus we cumulate land reforms over time generating a variablethat aggregates the number of legislative reforms to date in anyparticular state While crude we believe that it provides asensible rst pass at analyzing the quantitative effects of landreform The mean of that variable aggregated across the fourcategories of land reform is given in column 6 of Table I Similarmeans for the different categories of reform are given in columns7ndash10 The table demonstrates considerable variation in overallland reform activity across states with states such as Uttar

LAND POVERTY AND GROWTH INDIA 395

TA

BL

EII

IMP

OR

TA

NT

EV

EN

TS

INL

AN

DR

EF

OR

MS

ININ

DIA

NS

TA

TE

SS

INC

E19

50

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

And

hra

Pra

desh

1950 (a

men

ded

1954

)

(Tel

enga

na

Are

a)Te

nanc

yan

dA

gri-

cult

ura

lLan

dsA

ctTe

nan

tsre

ceiv

edpr

otec

ted

ten

ancy

stat

ust

enan

tsto

hav

em

inim

um

term

ofle

ase

righ

tof

purc

hase

ofn

onre

sum

able

lan

dst

rans

fer

ofow

ner

ship

topr

otec

ted

ten

ants

inre

spec

tof

non

resu

mab

lela

nds

as

are

sult

136

11pr

otec

ted

ten

ants

decl

ared

own

ers

1

1952

Hyd

erab

adA

boli

tion

ofC

ash

Gra

nts

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tele

nga

na

2

1954

Inam

Abo

liti

onA

ct(a

bsor

bed)

encl

aves

Abo

liti

onof

inam

s(w

ith

few

exce

ptio

ns)

2

1955

(Hyd

erab

adJa

gird

ars)

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tal

enga

na

219

56In

am(A

boli

tion

and

Con

vers

ion

into

Ryo

twar

i)A

ctA

cqu

isit

ion

of11

137

esta

tes

abol

itio

nof

106

mil

lion

min

orin

ams

2

1956 (a

men

ded

1974

)

Ten

ancy

Act

Ten

ancy

con

tin

ues

up

to2

3of

ceil

ing

area

law

does

not

prov

ide

for

con

fer-

men

tof

own

ersh

ipri

ght

onte

nant

sex

cept

thro

ugh

righ

tto

purc

has

eco

nfe

rsco

ntin

uou

sri

ght

ofre

sum

ptio

non

lan

dow

ner

s

1

1957

Inam

Abo

liti

onA

ctA

boli

tion

ofin

ams

(wit

hfe

wex

cept

ions

)st

ruck

dow

nby

the

Hig

hC

ourt

in19

70

2

Ass

am19

51S

tate

Acq

uis

itio

nof

Zam

inda

riA

ctA

boli

tion

ofin

term

edia

ryri

ghts

invo

lvin

g0

67m

illi

onh

ecta

res

219

54L

ush

aiH

ills

Dis

tric

t(A

cqu

isit

ion

ofC

hie

fsR

igh

ts)A

ctS

ame

asab

ove

2

1956 (a

men

ded

1976

)

Fix

atio

nof

Cei

lin

gon

Lan

dH

oldi

ngs

Act

Sel

f-ex

plan

ator

y3

1960

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1971

Ten

ancy

Act

Cla

ssi

este

nan

tsin

tooc

cupa

ncy

and

non

occu

pan

cyte

nan

tsf

orm

erh

asse

curi

tyof

ten

ure

may

acqu

ire

lan

dlor

drsquos

righ

tof

hol

din

gby

payi

ng

50ti

mes

the

lan

dre

ven

ue

subl

etti

ngis

disa

llow

ed

1

QUARTERLY JOURNAL OF ECONOMICS396

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

tB

enga

l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

ace

ilin

gpr

ovid

edfo

rab

olit

ion

ofal

lin

term

edia

ryte

nur

es

12

3

1955 (a

men

ded

1970

197

119

77)

Lan

dR

efor

ms

Act

Pro

vide

sth

atla

ndow

ner

can

resu

me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

ceil

ing

prov

isio

ns

byw

ith

-dr

awin

gpr

evio

us

exem

ptio

nsp

rovi

ded

for

regu

lato

rym

easu

res

toch

eck

indi

scri

min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

tego

ries

(15

ten

ancy

refo

rm

25

abol

itio

nof

inte

rmed

iari

es

35

ceil

ings

onla

ndh

oldi

ngs

4

5co

nso

lida

tion

ofla

nd

hol

din

gs)

wh

ere

itis

poss

ible

for

agi

ven

act

tobe

lon

gto

mor

eth

anon

eca

tego

ryI

nth

eza

man

dar

ilan

dte

nu

resy

stem

wh

ich

cove

red

56p

erce

nt

ofpr

ivat

ely

own

edla

nd

inB

riti

shIn

dia

the

lan

dw

asve

sted

inth

ela

nd

lord

know

nas

Zam

inda

rB

etw

een

him

and

the

real

cult

ivat

orth

ere

wer

ese

vera

llay

ers

ofre

ntr

ecei

vin

gin

term

edia

ries

Jag

irs

and

inam

sw

ere

free

gran

tsof

subg

ran

tsfr

omth

est

ate

wit

hth

eri

ght

toco

llec

tan

dap

prop

riat

ela

nd

reve

nu

eth

ough

wit

hth

epa

ssag

eof

tim

eja

gird

ars

and

inam

dars

beca

me

the

virt

ual

own

ers

Inth

eir

con

cept

ion

the

ryot

war

ian

dm

ahal

war

ilan

dte

nu

resy

stem

sdi

dn

otre

cogn

ize

any

inte

rmed

iary

betw

een

the

stat

ean

dth

ecu

ltiv

ator

(th

ough

ryot

san

dm

ahal

sdi

dh

ave

full

righ

tsto

sale

le

asin

gan

dtr

ansf

erof

lan

d)I

n

ltra

tion

ofm

oney

len

ders

and

trad

ers

into

agri

cult

ure

and

the

leas

eof

them

tote

nan

tsle

dto

crea

tion

ofan

inte

rmed

iary

clas

sev

enin

area

sty

pi

edby

thes

ela

nd

ten

ure

syst

ems

QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

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bly

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pie

dby

Con

gres

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ard

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gged

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men

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licy

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able

(cu

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vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

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dle

ftan

dso

ftle

ftp

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riod

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dla

nd

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rmva

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les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 7: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

to the sparseness of land records implementation has beenconsidered to be both sporadic and patchy only affecting a fewstates in any signicant way Radhakrishnan 1990 Appu 1996Behuria 1997 Mearns 1998

Village level studies also offer a very mixed assessment of thepoverty impact of different land reforms (see Jayaraman andLanjouw 1997) Similar reforms seemed to have produced differ-ent effects in different areas leaving overall impact indeterminateThere is some consensus that the abolition of intermediariesachieved a limited and variable success both in redistributingland toward the poor and increasing the security of smallholders(see eg Wadley and Derr 1990) For tenancy reform howeverwhereas successes have been recorded in particular wheretenants are well organized there has also been a range ofdocumented cases of imminent legislation prompting landlords toengage in mass evictions of tenants and of the de jure banning oflandlord-tenant relationships pushing tenancy underground andtherefore paradoxically reducing tenurial security (see egGough 1989) Land ceiling legislation in a variety of villagestudies is also perceived to have had neutral or negative effects onpoverty by inducing landowners from joint families to evict theirtenants and to separate their holdings into smaller proprietaryunits among family members as a means of avoiding expropria-tion (see eg Chattopadhyay 1994) Land consolidation is alsoon the whole judged not to have been progressive in its redistribu-tive impact given that richer farmers tend to use their power toobtain improved holdings (see eg Dreze Lanjouw and Sharma1998)

Table II gives a complete picture of land reform legislationand its classication during our data period Our empiricalanalysis aggregates reforms within each category If land reformshave any effect then we doubt that this would be instantaneousThus we cumulate land reforms over time generating a variablethat aggregates the number of legislative reforms to date in anyparticular state While crude we believe that it provides asensible rst pass at analyzing the quantitative effects of landreform The mean of that variable aggregated across the fourcategories of land reform is given in column 6 of Table I Similarmeans for the different categories of reform are given in columns7ndash10 The table demonstrates considerable variation in overallland reform activity across states with states such as Uttar

LAND POVERTY AND GROWTH INDIA 395

TA

BL

EII

IMP

OR

TA

NT

EV

EN

TS

INL

AN

DR

EF

OR

MS

ININ

DIA

NS

TA

TE

SS

INC

E19

50

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

And

hra

Pra

desh

1950 (a

men

ded

1954

)

(Tel

enga

na

Are

a)Te

nanc

yan

dA

gri-

cult

ura

lLan

dsA

ctTe

nan

tsre

ceiv

edpr

otec

ted

ten

ancy

stat

ust

enan

tsto

hav

em

inim

um

term

ofle

ase

righ

tof

purc

hase

ofn

onre

sum

able

lan

dst

rans

fer

ofow

ner

ship

topr

otec

ted

ten

ants

inre

spec

tof

non

resu

mab

lela

nds

as

are

sult

136

11pr

otec

ted

ten

ants

decl

ared

own

ers

1

1952

Hyd

erab

adA

boli

tion

ofC

ash

Gra

nts

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tele

nga

na

2

1954

Inam

Abo

liti

onA

ct(a

bsor

bed)

encl

aves

Abo

liti

onof

inam

s(w

ith

few

exce

ptio

ns)

2

1955

(Hyd

erab

adJa

gird

ars)

Act

Abo

liti

onof

allt

he

975

jagi

rsin

Tal

enga

na

219

56In

am(A

boli

tion

and

Con

vers

ion

into

Ryo

twar

i)A

ctA

cqu

isit

ion

of11

137

esta

tes

abol

itio

nof

106

mil

lion

min

orin

ams

2

1956 (a

men

ded

1974

)

Ten

ancy

Act

Ten

ancy

con

tin

ues

up

to2

3of

ceil

ing

area

law

does

not

prov

ide

for

con

fer-

men

tof

own

ersh

ipri

ght

onte

nant

sex

cept

thro

ugh

righ

tto

purc

has

eco

nfe

rsco

ntin

uou

sri

ght

ofre

sum

ptio

non

lan

dow

ner

s

1

1957

Inam

Abo

liti

onA

ctA

boli

tion

ofin

ams

(wit

hfe

wex

cept

ions

)st

ruck

dow

nby

the

Hig

hC

ourt

in19

70

2

Ass

am19

51S

tate

Acq

uis

itio

nof

Zam

inda

riA

ctA

boli

tion

ofin

term

edia

ryri

ghts

invo

lvin

g0

67m

illi

onh

ecta

res

219

54L

ush

aiH

ills

Dis

tric

t(A

cqu

isit

ion

ofC

hie

fsR

igh

ts)A

ctS

ame

asab

ove

2

1956 (a

men

ded

1976

)

Fix

atio

nof

Cei

lin

gon

Lan

dH

oldi

ngs

Act

Sel

f-ex

plan

ator

y3

1960

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1971

Ten

ancy

Act

Cla

ssi

este

nan

tsin

tooc

cupa

ncy

and

non

occu

pan

cyte

nan

tsf

orm

erh

asse

curi

tyof

ten

ure

may

acqu

ire

lan

dlor

drsquos

righ

tof

hol

din

gby

payi

ng

50ti

mes

the

lan

dre

ven

ue

subl

etti

ngis

disa

llow

ed

1

QUARTERLY JOURNAL OF ECONOMICS396

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

tB

enga

l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

ace

ilin

gpr

ovid

edfo

rab

olit

ion

ofal

lin

term

edia

ryte

nur

es

12

3

1955 (a

men

ded

1970

197

119

77)

Lan

dR

efor

ms

Act

Pro

vide

sth

atla

ndow

ner

can

resu

me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

ceil

ing

prov

isio

ns

byw

ith

-dr

awin

gpr

evio

us

exem

ptio

nsp

rovi

ded

for

regu

lato

rym

easu

res

toch

eck

indi

scri

min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

tego

ries

(15

ten

ancy

refo

rm

25

abol

itio

nof

inte

rmed

iari

es

35

ceil

ings

onla

ndh

oldi

ngs

4

5co

nso

lida

tion

ofla

nd

hol

din

gs)

wh

ere

itis

poss

ible

for

agi

ven

act

tobe

lon

gto

mor

eth

anon

eca

tego

ryI

nth

eza

man

dar

ilan

dte

nu

resy

stem

wh

ich

cove

red

56p

erce

nt

ofpr

ivat

ely

own

edla

nd

inB

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QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

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PO

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IND

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gap

diff

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cou

nt

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ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

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LS

AR

(1)

GL

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R(1

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(1)

GL

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R(1

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(1)

Fou

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cum

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form

legi

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20

378

(37

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037

(00

42)

20

539

(46

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129

8(5

04)

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cum

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tena

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refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

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mul

ativ

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olit

ion

inte

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iari

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n2

179

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81)

23

14(2

48)

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cum

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lan

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ilin

gle

gisl

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035

2(0

82)

20

121

(01

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our-

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lagg

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ativ

ela

nd

con

soli

dati

onle

gisl

atio

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164

(03

2)2

100

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Pop

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grow

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906

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297

99

(12

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(12

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(09

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per

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1(1

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(08

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(09

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072

(07

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83)

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8(1

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002

0(2

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7(2

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(04

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our-

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20

142

(29

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036

4(3

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20

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(12

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53)

20

422

(32

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11

(29

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(00

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(04

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(14

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3(0

30)

Sta

teef

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sY

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YE

SY

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SY

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aref

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sY

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YE

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um

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436

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436

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ren

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end

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son

con

stru

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nan

dso

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the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

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ates

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we

hav

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992

for

Har

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lit

from

the

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1965

we

hav

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975

and

1978

ndash199

2fo

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mm

uan

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ash

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1968

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1fo

rB

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and

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975

and

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ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

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pd

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ren

ceis

the

diff

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cebe

twee

nth

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ral

and

urb

anpo

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yga

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colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

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R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

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edis

trib

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xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 8: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TA

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EII

IMP

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TA

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EN

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AN

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MS

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DIA

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ear

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leD

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ipti

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hra

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ded

1954

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spec

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mab

lela

nds

as

are

sult

136

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ted

ten

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decl

ared

own

ers

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1952

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erab

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rsin

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nga

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bsor

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aves

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onof

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ith

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ptio

ns)

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1955

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erab

adJa

gird

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liti

onof

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he

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rsin

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enga

na

219

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boli

tion

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vers

ion

into

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ion

of11

137

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tes

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itio

nof

106

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lion

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orin

ams

2

1956 (a

men

ded

1974

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Ten

ancy

Act

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ancy

con

tin

ues

up

to2

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ing

area

law

does

not

prov

ide

for

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fer-

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tof

own

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ipri

ght

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nant

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cept

thro

ugh

righ

tto

purc

has

eco

nfe

rsco

ntin

uou

sri

ght

ofre

sum

ptio

non

lan

dow

ner

s

1

1957

Inam

Abo

liti

onA

ctA

boli

tion

ofin

ams

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hfe

wex

cept

ions

)st

ruck

dow

nby

the

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hC

ourt

in19

70

2

Ass

am19

51S

tate

Acq

uis

itio

nof

Zam

inda

riA

ctA

boli

tion

ofin

term

edia

ryri

ghts

invo

lvin

g0

67m

illi

onh

ecta

res

219

54L

ush

aiH

ills

Dis

tric

t(A

cqu

isit

ion

ofC

hie

fsR

igh

ts)A

ctS

ame

asab

ove

2

1956 (a

men

ded

1976

)

Fix

atio

nof

Cei

lin

gon

Lan

dH

oldi

ngs

Act

Sel

f-ex

plan

ator

y3

1960

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1971

Ten

ancy

Act

Cla

ssi

este

nan

tsin

tooc

cupa

ncy

and

non

occu

pan

cyte

nan

tsf

orm

erh

asse

curi

tyof

ten

ure

may

acqu

ire

lan

dlor

drsquos

righ

tof

hol

din

gby

payi

ng

50ti

mes

the

lan

dre

ven

ue

subl

etti

ngis

disa

llow

ed

1

QUARTERLY JOURNAL OF ECONOMICS396

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

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ner

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and

vest

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ish

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2m

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(ou

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726

mil

-li

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res)

12

1953

Con

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Hol

din

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tion

4

1960

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Cei

lin

gson

Lan

dhol

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ctIm

posi

tion

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ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

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res

(aft

er19

72)

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Act

Sti

pula

ted

that

the

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the

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or-

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them

1

1953

Est

ates

Acq

uis

itio

nA

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olde

rsli

mit

edto

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ilin

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olit

ion

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term

edia

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es

12

3

1955 (a

men

ded

1970

197

119

77)

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ms

Act

Pro

vide

sth

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ner

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me

land

for

pers

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ion

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that

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left

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hat

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sh

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ropp

ing

not

con

side

red

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ancy

(in

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tte

nan

tsar

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ers)

pro

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olid

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orm

ore

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ner

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ree

14

1972

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itio

nan

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ead

Lan

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men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

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ople

wer

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ven

hom

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nd

(abo

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ght

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tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

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l(c

ont

)

1977

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(Am

endm

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Act

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ses

pres

um

ptio

nin

favo

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pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

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ms

(Am

endm

ent)

Act

Des

ign

edto

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elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

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ms

(Am

endm

ent)

Act

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ith

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conv

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onof

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1990

Lan

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(Am

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Act

Sam

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Th

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35

ceil

ings

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ough

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ave

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oney

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ders

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ela

nd

ten

ure

syst

ems

QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

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lagg

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raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

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YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

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nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 9: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

Bih

ar19

50L

and

Ref

orm

sA

ctA

boli

tion

ofza

min

dari

im

plem

enta

tion

ofth

isac

tve

rysl

ow

219

57H

omes

tead

Ten

ancy

Act

Con

fers

righ

tsof

perm

anen

tte

nan

cyin

hom

este

adla

nds

onpe

rson

sh

oldi

ng

less

than

one

acre

ofla

nd

1

1961 (a

men

ded

1973

)

Lan

dR

efor

ms

Act

Pro

hibi

tssu

blet

tin

gpr

even

tin

gsu

bles

see

from

acqu

irin

gri

ght

ofoc

cu-

pan

cy

1

1961

Lan

dC

eili

ng

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of9

71ndash2

914

hec

tare

s(1

960ndash

1972

)an

dof

607

ndash18

21h

ecta

re(a

fter

1972

)3

1973 (a

men

ded

1982

)

Act

12(a

men

dmen

tto

Lan

dR

efor

ms

Act

)In

trod

uce

dpr

ovis

ion

sre

lati

ng

toth

evo

lun

tary

surr

ende

rof

surp

lus

lan

d3

1976

Act

55P

rovi

ded

for

the

subs

titu

tion

ofle

galh

eir

ceil

ing

area

shal

lbe

rede

ter-

min

edw

hen

clas

sic

atio

nof

land

chan

ges

orde

red

that

the

lan

dhol

der

nec

essa

rily

reta

inla

ndtr

ansf

erre

din

con

trav

enti

onof

the

Act

3

1986

Ten

ancy

(Am

endm

ent)

Act

Pro

vide

sde

nit

ion

ofpe

rson

alcu

ltiv

atio

np

rovi

des

for

acqu

isit

ion

ofoc

cu-

pan

cyri

ghts

byu

nde

rrai

yats

1

Gu

jara

t19

48 (am

ende

d19

55an

d19

60)

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

ands

Act

Ten

ants

enti

tled

toac

quir

eri

ght

ofow

ners

hip

afte

rex

piry

ofon

eye

aru

pto

ceil

ing

area

con

fers

own

ersh

ipri

ght

onte

nan

tsin

poss

essi

onof

dwel

lin

gsi

teon

paym

ent

of20

tim

esan

nu

alre

nt

law

does

not

con

fer

any

righ

tson

subt

enan

ts

1

1960

Agr

icu

ltur

alL

ands

Cei

lin

gA

ctIm

pose

dce

ilin

gon

lan

dhol

din

gsof

405

ndash53

14he

ctar

es(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

1969

Dev

asth

anIn

ams

Abo

liti

onA

ctA

boli

shes

allg

rade

sof

inte

rmed

iary

ten

ure

sbu

tla

ww

aspa

rtia

lly

inju

nct

edfr

omim

plem

enta

tion

byor

der

ofS

upr

eme

Cou

rt

2

1973

Am

endi

ng

Act

Pro

vide

sop

port

un

ity

toac

quir

eow

ner

ship

ofho

ldin

gsbu

tla

rgel

yov

er-

ridd

enby

nu

mer

ous

prov

isio

ns

1

Har

yan

a19

53P

un

jab

Sec

uri

tyof

Lan

dTe

nu

res

Act

Pro

vide

sco

mpl

ete

secu

rity

ofte

nure

for

ten

ants

inco

nti

nu

ous

poss

essi

onof

lan

d(

15ac

res)

for

12ye

ars

gran

tste

nan

tsop

tion

alri

ght

ofpu

r-ch

ase

ofow

ner

ship

ofn

onre

sum

able

lan

dn

oba

ron

futu

rele

asin

g

1

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 397

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

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pro-

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and

vest

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ish

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2m

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res

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726

mil

-li

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res)

12

1953

Con

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Hol

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tion

4

1960

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lin

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Lan

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ctIm

posi

tion

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gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

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res

(aft

er19

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Act

Sti

pula

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that

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or-

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them

1

1953

Est

ates

Acq

uis

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olde

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mit

edto

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ilin

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ion

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term

edia

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es

12

3

1955 (a

men

ded

1970

197

119

77)

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ms

Act

Pro

vide

sth

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ner

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me

land

for

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that

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left

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hat

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sh

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ing

not

con

side

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ancy

(in

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tte

nan

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ers)

pro

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olid

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ore

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ner

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ree

14

1972

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nan

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Hom

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ead

Lan

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men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

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men

Act

Ove

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ople

wer

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ven

hom

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nd

(abo

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ght

cen

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ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

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l(c

ont

)

1977

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(Am

endm

ent)

Act

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ses

pres

um

ptio

nin

favo

rof

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pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

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ms

(Am

endm

ent)

Act

Des

ign

edto

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elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

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ms

(Am

endm

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Act

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ith

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conv

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onof

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one

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3

1990

Lan

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(Am

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Act

Sam

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Th

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35

ceil

ings

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ough

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ave

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ders

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ela

nd

ten

ure

syst

ems

QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

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lagg

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ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

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nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 10: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Jam

mu

1962

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

and

Kas

hm

ir19

76A

grar

ian

Ref

orm

sA

ctA

llri

ghts

tit

les

and

inte

rest

sin

land

ofan

ype

rson

not

cult

ivat

ing

itpe

r-so

nal

lyin

1971

are

exti

ngu

ish

edan

dtr

ansf

erre

dto

the

stat

epr

ovid

esfo

rco

nfe

rmen

tof

own

ersh

ipri

ghts

onte

nan

tsaf

ter

allo

win

gre

side

ntla

ndl

ord

tore

sum

ela

nd

for

pers

onal

cult

ivat

ion

1

Kar

nat

aka

1954

Mys

ore

(Per

son

alan

dM

isce

llan

eous

)In

ams

Abo

liti

onA

ctA

boli

shed

allt

hela

rge

inam

dari

inte

rmed

iari

esp

roce

ssof

impl

emen

ta-

tion

very

slow

2

1955

Mys

ore

(Rel

igio

usan

dC

har

itab

le)

Inam

sA

boli

tion

Act

Sam

eas

abov

e2

1961

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

resu

bjec

tto

lan

dlor

drsquos

righ

tto

resu

me

12

leas

edar

eag

ran

tste

nant

sop

tion

alri

ght

topu

rcha

seow

ner

ship

onpa

ymen

tof

15ndash2

0ti

mes

the

net

rent

im

posi

tion

ofce

ilin

gon

lan

dhol

din

gs

13

1974

Lan

dR

efor

ms

(Am

endm

ent)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of4

05ndash2

185

hec

tare

s(a

fter

1972

)re

mov

alof

allb

uton

eof

the

exem

ptio

ns

from

tena

ncy

legi

slat

ion

1

3

Ker

ala

1960

Agr

aria

nR

elat

ion

sA

ctA

boli

shes

inte

rmed

iari

esb

ut

law

stru

ckdo

wn

byS

upr

eme

Cou

rt

219

63L

and

Ref

orm

sA

ctC

once

des

ten

antrsquos

righ

tto

purc

hase

the

lan

dfr

omla

ndow

ner

s1

1969 (a

men

ded

1979

)

Lan

dR

efor

ms

(Am

endm

ent)

Act

Con

ferm

ent

offu

llow

ner

ship

righ

tson

ten

ants

25

mil

lion

ten

ants

cou

ldbe

com

ela

ndo

wn

ers

righ

tof

resu

mpt

ion

expi

res

alth

ough

far-

reac

hin

gon

pape

rla

wlsquolsquon

otco

ndu

cive

toso

cial

just

icersquo

rsquobec

ause

ofco

nce

aled

ten

-an

cyi

mpo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of6

07ndash1

518

hec

tare

s(1

960ndash

1972

)an

dof

486

ndash60

7h

ecta

res

(aft

er19

72)

abol

itio

nof

inte

rme-

diar

yri

ghts

12

3

1974

Agr

icu

ltur

alW

ork

ers

Act

Cal

led

for

empl

oym

ent

secu

rity

xe

dh

ours

min

imu

mw

ages

etc

1

Mad

hya

Pra

desh

1950

Abo

liti

onof

Pro

prie

tary

Rig

hts

(Est

ates

Mah

als

Ali

enat

edL

ands

)Act

Abo

liti

onof

inte

rmed

iary

righ

ts

2

1951

Un

ited

Sta

tes

ofG

wal

ior

Indo

re

and

Mal

wa

Zam

inda

riA

boli

tion

Act

Sam

eas

abov

e2

QUARTERLY JOURNAL OF ECONOMICS398

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

toow

ner

ship

righ

tsof

non

-re

sum

able

area

onpa

ymen

tof

15ti

mes

the

lan

dre

ven

ue

impl

emen

ta-

tion

ofre

form

inef

fici

ent

one

reas

onbe

ing

that

shar

ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

tB

enga

l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

ace

ilin

gpr

ovid

edfo

rab

olit

ion

ofal

lin

term

edia

ryte

nur

es

12

3

1955 (a

men

ded

1970

197

119

77)

Lan

dR

efor

ms

Act

Pro

vide

sth

atla

ndow

ner

can

resu

me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

ceil

ing

prov

isio

ns

byw

ith

-dr

awin

gpr

evio

us

exem

ptio

nsp

rovi

ded

for

regu

lato

rym

easu

res

toch

eck

indi

scri

min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

tego

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QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

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Mod

el

Ru

ral

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gap

Ru

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gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

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R(1

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LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

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lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

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gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

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mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

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gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

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mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

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32

(12

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81

(09

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145

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per

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uca

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006

3(2

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007

0(2

24)

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6(1

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1(1

73)

007

7(2

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003

4(0

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Fou

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per

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pend

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038

(08

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(09

1)0

072

(07

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000

3(0

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2(0

83)

021

8(1

76)

Fou

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per

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her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

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2(2

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000

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20

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(04

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our-

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stri

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vest

ate

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s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

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our-

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11

(29

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43

(09

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(01

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000

1(0

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20

003

(00

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20

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(04

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031

(14

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3(0

30)

Sta

teef

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sY

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YE

SY

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SY

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aref

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sY

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YE

SY

ES

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SY

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um

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ofob

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atio

ns

436

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436

436

436

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z-st

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tics

are

inpa

ren

thes

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ata

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end

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tail

son

con

stru

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nan

dso

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esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

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1968

ndash199

1fo

rB

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and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

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pd

iffe

ren

ceis

the

diff

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cebe

twee

nth

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ral

and

urb

anpo

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yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

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iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

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edis

trib

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xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 11: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

1951

Abo

liti

onof

Jagi

rA

ctS

ame

asab

ove

219

52V

indh

yaP

rade

shA

boli

tion

ofJa

girs

and

Lan

dR

efor

ms

Act

Sam

eas

abov

e2

1959

Lan

dR

even

ueC

ode

Lea

sin

gpr

ohib

ited

en

titl

esoc

cupa

ncy

tena

nts

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ner

ship

righ

tsof

non

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sum

able

area

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ymen

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mes

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dre

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ue

impl

emen

ta-

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ofre

form

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fici

ent

one

reas

onbe

ing

that

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ecro

pper

san

dte

n-an

tsar

en

otre

cord

ed

1

1959

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Cei

lin

gon

Agr

icu

ltu

ralH

oldi

ngs

Act

Impo

sed

ceil

ing

onla

ndh

oldi

ngs

of10

12

hec

tare

s(1

960ndash

1972

)an

dof

405

ndash21

85h

ecta

res

(aft

er19

72)

3

Mah

aras

htr

a19

50H

yder

abad

Tena

ncy

and

Agr

icu

ltu

ral

Lan

dsA

ctP

rovi

des

for

suo

mot

totr

ansf

erof

owne

rsh

ipto

ten

ants

ofno

nre

sum

able

lan

ds(a

ppli

esto

Mar

atha

wad

are

gion

)1

1958

Bom

bay

Ten

ancy

and

Agr

icu

ltur

alL

and

Act

Pro

vide

sfo

rtr

ansf

erof

owne

rsh

ipto

ten

ants

wit

hn

onre

sum

able

land

s(w

ith

effe

ctfr

om1-

4-96

)1

1961

Agr

icu

ltur

alL

and

(Cei

lin

gon

Hol

d-in

gs)A

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gs

3

Ori

ssa

1951

Est

ate

Abo

liti

onA

ctA

imed

atab

olis

hin

gal

lin

term

edia

ryin

tere

sts

219

72L

and

Ref

orm

sA

ctE

nti

tled

ten

ants

toac

quir

ery

otir

igh

tsov

eren

tire

lan

dh

eld

byth

em

219

60 (am

ende

d19

73an

d19

76)

Lan

dR

efor

ms

Act

Pro

vide

sfo

r

xity

ofte

nu

reof

non

resu

mab

lear

eap

roh

ibit

ssu

blet

ting

im

plem

enta

tion

poor

n

anci

alhe

lpfo

rpu

rch

ase

ofow

ners

hip

righ

tla

ckin

gm

ost

leas

esin

form

ofsh

arec

ropp

ing

but

shar

ecro

pper

sno

tre

cord

edas

ten

ants

im

posi

tion

ofce

ilin

gon

lan

dhol

ding

sof

809

ndash32

37h

ecta

res

(196

0ndash19

72)a

nd

of4

05ndash1

821

hect

ares

(aft

er19

72)

13

1972

Con

soli

dati

onof

Hol

din

gsan

dP

re-

ven

tion

ofF

ragm

enta

tion

ofL

and

Act

Intr

odu

ctio

nof

com

puls

ory

con

soli

dati

on

4

Pu

njab

1953

Pu

nja

bS

ecu

rity

ofL

and

Ten

ure

sA

ctP

rovi

des

com

plet

ese

curi

tyof

tenu

refo

rte

nan

tsin

con

tin

uou

spo

sses

sion

ofla

nd

( 15

acre

s)fo

r12

year

sgr

ants

ten

ants

opti

onal

righ

tof

pur-

chas

eof

own

ersh

ipof

non

resu

mab

lela

nd

no

bar

onfu

ture

leas

ing

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 399

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

dA

gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

)is

7h

ecta

res

5ac

res

ofla

nd

are

secu

red

the

rest

may

bere

sum

edo

ptio

nal

righ

tof

purc

has

eof

own

ersh

ips

har

e-cr

oppi

ng

not

con

side

red

ten

ancy

ten

ants

ofte

nco

erce

dto

lsquolsquovol

unta

rily

surr

ende

rrsquorsquol

and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

52L

and

Ref

orm

san

dR

esu

mpt

ion

ofJa

gir

Act

Abo

lish

esal

lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

agir

Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

and

Pre

ven

-ti

onof

Fra

gmen

tati

on)A

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

boli

tion

ofIn

term

edia

ries

and

Lan

dR

efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

secu

rity

ofte

nu

reto

tena

nts

and

subt

enan

tso

wn

ersh

ipri

ghts

can

betr

ansf

erre

dpr

ovis

ions

ofvo

lun

tary

surr

ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

isw

edar

iAbo

liti

onA

ctA

boli

shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

2

Tam

ilN

adu

1948

Est

ates

(Abo

liti

onan

dC

onve

rsio

nin

toR

yotw

ari)

Act

XX

VI

Ase

ries

ofla

ws

enac

ted

(th

roug

hlo

ng

inte

rval

s)fo

rth

eab

olit

ion

ofva

riou

sty

pes

ofin

term

edia

ries

2

1952

Th

anja

vur

Tena

nts

and

Pan

naiy

alP

rote

ctio

nA

ctP

rovi

des

grea

ter

secu

rity

ofte

nu

re

1

1955 (a

men

ded

1965

)

Mad

ras

Cu

ltiv

atin

gTe

nant

sP

rote

c-ti

onA

ctP

rohi

bits

any

cult

ivat

ing

ten

ant

from

bein

gev

icte

dbu

tal

low

sfo

rre

sum

p-ti

onu

pto

12

ofla

nds

leas

edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

cult

ivat

ing

tena

nts

119

61L

and

Ref

orm

s(F

ixat

ion

ofC

eili

ng

onL

and)

Act

Impo

siti

onof

ceil

ing

onla

ndh

oldi

ngs

of12

14ndash

485

6h

ecta

res

(196

0ndash19

72)

and

of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

ctP

rovi

des

for

prep

arat

ion

and

mai

nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

boli

tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

secu

rity

ofte

nu

rew

itho

ut

any

righ

tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

tB

enga

l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

ace

ilin

gpr

ovid

edfo

rab

olit

ion

ofal

lin

term

edia

ryte

nur

es

12

3

1955 (a

men

ded

1970

197

119

77)

Lan

dR

efor

ms

Act

Pro

vide

sth

atla

ndow

ner

can

resu

me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

ceil

ing

prov

isio

ns

byw

ith

-dr

awin

gpr

evio

us

exem

ptio

nsp

rovi

ded

for

regu

lato

rym

easu

res

toch

eck

indi

scri

min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

tego

ries

(15

ten

ancy

refo

rm

25

abol

itio

nof

inte

rmed

iari

es

35

ceil

ings

onla

ndh

oldi

ngs

4

5co

nso

lida

tion

ofla

nd

hol

din

gs)

wh

ere

itis

poss

ible

for

agi

ven

act

tobe

lon

gto

mor

eth

anon

eca

tego

ryI

nth

eza

man

dar

ilan

dte

nu

resy

stem

wh

ich

cove

red

56p

erce

nt

ofpr

ivat

ely

own

edla

nd

inB

riti

shIn

dia

the

lan

dw

asve

sted

inth

ela

nd

lord

know

nas

Zam

inda

rB

etw

een

him

and

the

real

cult

ivat

orth

ere

wer

ese

vera

llay

ers

ofre

ntr

ecei

vin

gin

term

edia

ries

Jag

irs

and

inam

sw

ere

free

gran

tsof

subg

ran

tsfr

omth

est

ate

wit

hth

eri

ght

toco

llec

tan

dap

prop

riat

ela

nd

reve

nu

eth

ough

wit

hth

epa

ssag

eof

tim

eja

gird

ars

and

inam

dars

beca

me

the

virt

ual

own

ers

Inth

eir

con

cept

ion

the

ryot

war

ian

dm

ahal

war

ilan

dte

nu

resy

stem

sdi

dn

otre

cogn

ize

any

inte

rmed

iary

betw

een

the

stat

ean

dth

ecu

ltiv

ator

(th

ough

ryot

san

dm

ahal

sdi

dh

ave

full

righ

tsto

sale

le

asin

gan

dtr

ansf

erof

lan

d)I

n

ltra

tion

ofm

oney

len

ders

and

trad

ers

into

agri

cult

ure

and

the

leas

eof

them

tote

nan

tsle

dto

crea

tion

ofan

inte

rmed

iary

clas

sev

enin

area

sty

pi

edby

thes

ela

nd

ten

ure

syst

ems

QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

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gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 12: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

1955

Pep

suTe

nan

cyan

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gric

ult

ura

lL

and

Act

Sam

eas

abov

e1

1972

Lan

dR

efor

ms

Act

Per

mis

sibl

eli

mit

(cei

ling

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ecta

res

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res

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nd

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red

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rest

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ptio

nal

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ips

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ng

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red

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ancy

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erce

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rily

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and

lan

dle

ases

not

regi

ster

edu

nde

rpr

ovis

ion

ofte

nanc

yla

ws

1

Raj

asth

an19

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and

Ref

orm

san

dR

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mpt

ion

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gir

Act

Abo

lish

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lin

term

edia

ryri

ghts

2

1953

Bom

bay

Mer

ged

Terr

itor

ies

and

Are

a(J

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Abo

liti

on)A

ctS

ame

asab

ove

2

1954

Hol

ding

s(C

onso

lida

tion

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Pre

ven

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onof

Fra

gmen

tati

on)A

ctIn

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uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1955

Ajm

erA

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tion

ofIn

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edia

ries

and

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efor

ms

Act

Abo

lish

esin

term

edia

ryin

tere

sts

inot

her

area

s2

1955

Ten

ancy

Act

Con

fers

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rity

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reto

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nts

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enan

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wn

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ipri

ghts

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erre

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ovis

ions

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tary

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ende

rm

ade

legi

slat

ion

lsquolsquomer

efa

rce

rsquorsquo

1

1959

Zam

inda

rian

dB

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edar

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liti

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shes

inte

rmed

iary

inte

rest

sin

oth

erar

eas

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ilN

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1948

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ates

(Abo

liti

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ari)

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XX

VI

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ries

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olit

ion

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sty

pes

ofin

term

edia

ries

2

1952

Th

anja

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Tena

nts

and

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ter

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rity

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nu

re

1

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men

ded

1965

)

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ras

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ltiv

atin

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rote

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bits

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ivat

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ant

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tal

low

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onu

pto

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ofla

nds

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edou

tto

tena

nt

1

1956

Cu

ltiv

atin

gTe

nan

ts(P

aym

ent

ofF

air

Ren

t)A

ctA

boli

shes

usu

ryan

dra

ck-r

enti

ng

1

QUARTERLY JOURNAL OF ECONOMICS400

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

tru

stca

nev

ict

its

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ivat

ing

tena

nts

119

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and

Ref

orm

s(F

ixat

ion

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eili

ng

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and)

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Impo

siti

onof

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ing

onla

ndh

oldi

ngs

of12

14ndash

485

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ecta

res

(196

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of4

86ndash2

428

hec

tare

s(a

fter

1972

)3

1969

Agr

icu

ltur

alL

and-

Rec

ords

ofTe

n-

ancy

Rig

htA

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des

for

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arat

ion

and

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nte

nan

ceof

com

plet

ere

cord

ofte

nan

cyri

ghts

1

1971

Occ

upa

nts

ofK

udi

yiru

ppu

Act

Pro

vide

sfo

rac

quis

itio

nan

dco

nfe

rmen

tof

owne

rsh

ipri

ghts

onag

ricu

ltu

r-is

tsa

gric

ultu

rall

abor

ers

and

rura

lart

isan

s1

1976

Ru

ralA

rtis

ans

(Con

ferm

ent

ofO

wn

-er

ship

ofK

udi

yiru

ppu)

Act

Sam

eas

abov

e1

Utt

arP

rade

sh19

50 (am

ende

d19

521

954

1956

195

819

77)

Zam

inda

riA

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tion

and

Lan

dR

efor

ms

Act

All

ten

ants

are

give

nco

mpl

ete

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rity

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nu

rew

itho

ut

any

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tof

resu

mpt

ion

for

the

lan

dow

ner

lea

ses

inge

ner

ala

reba

nned

law

pro-

vide

dfo

rtr

ansf

erri

ng

and

vest

ing

ofal

lzam

inda

ries

tate

sza

min

dari

was

abol

ish

edov

er60

2m

illi

onac

res

(ou

tof

tota

lsta

tear

eaof

726

mil

-li

onac

res)

12

1953

Con

soli

dati

onof

Hol

din

gsA

ctIn

trod

uct

ion

ofco

mpu

lsor

yco

nso

lida

tion

4

1960

Impo

siti

onof

Cei

lin

gson

Lan

dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

gon

land

hol

din

gsof

161

9ndash32

37

hec

tare

s(1

960ndash

1972

)an

dof

730

ndash18

25h

ecta

res

(aft

er19

72)

3

Wes

tB

enga

l19

50B

arga

dars

Act

Sti

pula

ted

that

the

barg

adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

uis

itio

nA

ctL

andh

olde

rsli

mit

edto

ace

ilin

gpr

ovid

edfo

rab

olit

ion

ofal

lin

term

edia

ryte

nur

es

12

3

1955 (a

men

ded

1970

197

119

77)

Lan

dR

efor

ms

Act

Pro

vide

sth

atla

ndow

ner

can

resu

me

land

for

pers

onal

cult

ivat

ion

such

that

tena

ntis

left

wit

hat

leas

t1

hec

tare

sh

arec

ropp

ing

not

con

side

red

ten

ancy

(in

Wes

tB

enga

lmos

tte

nan

tsar

esh

arec

ropp

ers)

pro

vide

sfo

rla

nd

cons

olid

atio

nif

two

orm

ore

lan

dow

ner

sag

ree

14

1972

Acq

uis

itio

nan

dS

ettl

emen

tof

Hom

e-st

ead

Lan

d(A

men

dmen

t)A

ctTe

nan

tsof

hom

este

adla

nds

are

give

nfu

llri

ghts

1

1975

Acq

uis

itio

nof

Hom

este

adL

and

for

Agr

icul

tura

lLab

orer

sA

rtis

ans

and

Fis

her

men

Act

Ove

r25

000

0pe

ople

wer

egi

ven

hom

este

adla

nd

(abo

utei

ght

cen

tsea

ch)

up

toJa

nu

ary

1991

1

(con

tin

ued

onne

xtpa

ge)

LAND POVERTY AND GROWTH INDIA 401

TA

BL

EII

(CO

NT

INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

93

p48

1

1981

Lan

dR

efor

ms

(Am

endm

ent)

Act

Des

ign

edto

plu

gth

elo

oph

oles

inth

eea

rlie

rA

cts

rela

tin

gto

the

ceil

ing

ofla

ndh

oldi

ngs

3

1986

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sou

ght

tobr

ing

allc

lass

esof

land

un

der

the

ceil

ing

prov

isio

ns

byw

ith

-dr

awin

gpr

evio

us

exem

ptio

nsp

rovi

ded

for

regu

lato

rym

easu

res

toch

eck

indi

scri

min

ate

conv

ersi

onof

land

from

one

use

toan

oth

erl

awn

otye

tfu

lly

impl

emen

ted

3

1990

Lan

dR

efor

ms

(Am

endm

ent)

Act

Sam

eas

abov

e3

Th

eco

nte

nt

ofla

nd

refo

rmac

tsar

ecl

assi

ed

into

fou

rca

tego

ries

(15

ten

ancy

refo

rm

25

abol

itio

nof

inte

rmed

iari

es

35

ceil

ings

onla

ndh

oldi

ngs

4

5co

nso

lida

tion

ofla

nd

hol

din

gs)

wh

ere

itis

poss

ible

for

agi

ven

act

tobe

lon

gto

mor

eth

anon

eca

tego

ryI

nth

eza

man

dar

ilan

dte

nu

resy

stem

wh

ich

cove

red

56p

erce

nt

ofpr

ivat

ely

own

edla

nd

inB

riti

shIn

dia

the

lan

dw

asve

sted

inth

ela

nd

lord

know

nas

Zam

inda

rB

etw

een

him

and

the

real

cult

ivat

orth

ere

wer

ese

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QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

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RO

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ral

hea

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un

tU

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pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

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LS

AR

(1)

GL

SA

R(1

)G

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AR

(1)

GL

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R(1

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LS

AR

(1)

Fou

r-ye

arla

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cum

ulat

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lan

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form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

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gged

cum

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ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

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mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

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mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

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32

(12

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81

(09

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145

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90)

Fou

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per

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3(2

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007

0(2

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6(1

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1(1

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7(2

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4(0

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Fou

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per

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038

(08

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(09

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072

(07

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83)

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8(1

76)

Fou

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per

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002

0(2

69)

001

7(2

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002

6(1

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20

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(04

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our-

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ate

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013

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20

142

(29

2)2

036

4(3

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20

045

(12

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018

2(3

53)

20

422

(32

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our-

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11

(29

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(01

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000

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003

(00

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20

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(04

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031

(14

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3(0

30)

Sta

teef

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sY

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YE

SY

ES

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SY

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aref

fect

sY

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YE

SY

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SN

um

ber

ofob

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atio

ns

436

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436

436

436

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z-st

atis

tics

are

inpa

ren

thes

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ata

App

end

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rde

tail

son

con

stru

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nan

dso

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esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

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jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

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lit

from

the

Pu

nja

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1965

we

hav

eda

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70ndash1

975

and

1978

ndash199

2fo

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mm

uan

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ash

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1968

ndash199

1fo

rB

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and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

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pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

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edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 13: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

1961

(am

71)

Pu

blic

Ten

ants

Act

Pro

vide

sth

atn

opu

blic

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stca

nev

ict

its

cult

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ing

tena

nts

119

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orm

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ixat

ion

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ng

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ecta

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fter

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ords

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nte

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plet

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cord

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cyri

ghts

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upa

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Pro

vide

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quis

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rmen

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ghts

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ltu

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gric

ultu

rall

abor

ers

and

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lart

isan

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1976

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ralA

rtis

ans

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ferm

ent

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wn

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ship

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eas

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rade

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d19

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inda

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tion

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efor

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rity

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rew

itho

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righ

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mpt

ion

for

the

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dow

ner

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ses

inge

ner

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reba

nned

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pro-

vide

dfo

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vest

ing

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inda

ries

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min

dari

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ish

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er60

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illi

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tof

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eaof

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dati

onof

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din

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ctIn

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uct

ion

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mpu

lsor

yco

nso

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tion

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Impo

siti

onof

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gson

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dhol

d-in

gsA

ctIm

posi

tion

ofce

ilin

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din

gsof

161

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tare

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960ndash

1972

)an

dof

730

ndash18

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ecta

res

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er19

72)

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Wes

tB

enga

l19

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arga

dars

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Sti

pula

ted

that

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adar

and

the

lan

dow

ner

cou

ldch

oose

any

prop

or-

tion

acce

ptab

leto

them

1

1953

Est

ates

Acq

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LAND POVERTY AND GROWTH INDIA 401

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QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

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taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

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duct

ton

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wn

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Red

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ibu

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me

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nd

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erty

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ata

Ap

pen

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ils

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ruct

ion

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rces

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riab

les

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are

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een

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ates

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mn

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hav

eda

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for

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vest

ates

for

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nja

ban

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arya

na

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ich

spli

tin

1965

we

hav

eda

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for

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mu

and

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hm

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for

Bih

ar19

611

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1969

ndash199

2T

his

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of48

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1969

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arya

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mu

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aran

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1964

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am19

69an

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1964

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see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 14: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TA

BL

EII

(CO

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INU

ED

)

Sta

teY

ear

Tit

leD

escr

ipti

onC

lass

Wes

tB

enga

l(c

ont

)

1977

Lan

dR

efor

ms

(Am

endm

ent)

Act

lsquolsquoRai

ses

pres

um

ptio

nin

favo

rof

shar

ecro

pper

srsquorsquo

Yuga

ndh

aran

dIy

er19

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QUARTERLY JOURNAL OF ECONOMICS402

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

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OR

MA

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PO

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RT

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IND

IA

CO

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RO

LL

ING

FO

RO

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Mod

el

Ru

ral

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gap

Ru

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Ru

ral

hea

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un

tU

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pove

rty

gap

Pov

erty

gap

diff

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ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

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R(1

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LS

AR

(1)

Fou

r-ye

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cum

ulat

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lan

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form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

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gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

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mul

ativ

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olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

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mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

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02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

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81

(09

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145

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90)

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0(2

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6(1

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1(1

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7(2

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003

4(0

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Fou

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(08

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(09

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072

(07

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83)

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76)

Fou

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her

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002

0(2

69)

001

7(2

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002

6(1

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our-

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142

(29

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20

045

(12

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53)

20

422

(32

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11

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20

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(04

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(14

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3(0

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Sta

teef

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sY

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YE

SY

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SY

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aref

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sY

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YE

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um

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ofob

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atio

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436

436

436

436

436

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z-st

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tics

are

inpa

ren

thes

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ata

App

end

ixfo

rde

tail

son

con

stru

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nan

dso

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esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

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we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

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70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

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ash

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1968

ndash199

1fo

rB

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and

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64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

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pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

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yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

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iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

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xT

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(1)m

odel

allo

ws

ast

ate-

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R(1

)pro

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mdashse

eeq

uati

on(1

)in

the

text

for

deta

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edis

trib

uti

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xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 15: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

Pradesh Kerala and Tamil Nadu having a lot of activity whilePunjab and Rajasthan have very little

Our poverty data come from a consistent set of gures for therural and urban areas of Indiarsquos sixteen major states spanning theperiod 1958ndash1992 compiled by Ozler Datt and Ravallion 1996The measures are based on consumption distributions from 22rounds of the National Sample Survey (NSS) spanning thisperiod The poverty line is based on a nutritional norm of 2400calories per day and is dened as the level of average per capitatotal expenditure at which this norm is typically attained Twopoverty measures are considered the headcount index and thepoverty gap4 Given that NSS surveys are not annual weightedinterpolation has been used to obtain values between surveys5

Our study should be seen in the context of a signicant overallreduction in poverty throughout our data periodmdashthe all-Indiarural headcount measure has fallen from around 55 percent to 40percent and the rural poverty gap from 19 percent to around 10percent That said there is considerable cross-sectional variationin performance across states6 Agricultural wage data were alsocollected to enable us to examine whether land reforms hadgeneral equilibrium effects and were thus capable of reachinggroups of the poor (eg landless laborers) who did not directlybenet from the reforms

Real values of per capita agricultural nonagricultural andcombined state domestic product are also available to examine thedeterminants of growth Agricultural state domestic product wasdeated using the Consumer Price Index for Agricultural Labor-ers while the Consumer Price Index for Industrial Workers wasused to deate the nonagricultural state domestic product Wealso constructed a variable to measure agricultural yields Thiswas dened as real agricultural state domestic product divided bythe net sown area This crudely captures technological changes inagriculture

Public nance data at the state level were also collectedchiey as a means to control for other government interventionsbesides land reform On the expenditure side the main classica-

4 The headcount index is the proportion of the population living below thepoverty line The poverty gap is the average distance below the line expressed as aproportion of the poverty line where the average is formed over the wholepopulation (counting the nonpoor as having zero distance below the line)

5 Below we check that our results are robust to including only those yearswhere there was an NSS survey round

6 See Datt and Ravallion 1998 for further discussion

LAND POVERTY AND GROWTH INDIA 403

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

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nd

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dup

arti

esla

gged

eigh

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erio

dsp

lus

cum

ula

tive

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dre

form

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ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 16: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

tion available for our data period is into development andnondevelopment expenditure While development expendituredoes include expenditure on economic and social services there isno particular connection between this category and governmentrsquosefforts to develop the population or infrastructure in their states7

Development expenditures are therefore further disaggregatedinto health and education expenditures that we might expect tohave appreciable impacts on poverty We put these in real percapita terms We also collected total state taxes as a share of statedomestic product as a crude measure of the size of state govern-ments and state redistributive taxes per capita8 to capture theeffort of state governments to redistribute from rich to poorPopulation estimates from the ve censuses for 1951 1961 19711981 and 1991 were used as additional controls Between any twocensuses these were assumed to grow at a constant (compound)rate of growth derived from the respective population totals

III LAND REFORM AND POVERTY REDUCTION

A Basic Results

The empirical approach is to run panel data regressions of theform

(1) xst 5 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

where xst is some measure of poverty in state s at time t a s is astate xed effect b t is a year dummy variable yst is a vector ofvariables that we treat as exogenous (detailed below) lst 2 4 is thestock of past land reforms four periods previously and e st is anerror term which we model as AR(1) process where the degree ofautocorrelation is state-specic ie e st 5 r s e st 2 1 1 ust Estimationvia generalized least squares will also allow for heteroskedasticityin the error structure with each state having its own errorvariance

Equation (1) is a reduced-form model of the impact of landreform Thus any effect of land reform on poverty is picked up by

7 Economic services include agriculture and allied activities rural develop-ment special area programs irrigation and ood control energy industry andminerals transport and communications science technology and environmentSocial services include education medical and public health family welfare watersupply and sanitation housing urban development labor and labor welfaresocial security and welfare nutrition and relief on account of natural calamities

8 These include land tax agricultural income tax and property tax all ofwhich are under the control of state governments

QUARTERLY JOURNAL OF ECONOMICS404

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

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(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

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(1)

GL

SA

R(1

)G

LS

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(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

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539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

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Fou

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per

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tah

ealt

hex

pend

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8)0

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072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

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31)

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56)

001

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40)

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008

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0)F

our-

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rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

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142

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2)2

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25)

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045

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53)

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422

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our-

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edst

ate

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ape

rcen

tage

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ate

dom

esti

cpr

oduc

t2

495

9(2

99)

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11

(29

4)2

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3(2

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3)16

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ricu

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ield

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003

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2)2

050

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19)

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006

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2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 17: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

that variable along with other effects that change the claims thattenants have to land The land reform variable will also pick upany general equilibrium effects of land reform through changes inwages and prices Below we discuss what kind of theoreticalmodel is consistent with our empirical ndings

The approach is also reduced form because land reformlegislation is used as regressormdashwe are unable to measurewhether land reforms are actually implemented We cannotdistinguish therefore between ineffective and unimplementedland reforms Even though we have no measure of this there isanecdotal evidence that some land reforms were not fully imple-mented Hence the coefficient on land reform in (1) is likely toprovide a lower bound on the true effect of an implemented landreform We have lagged the land reform variable four periods fortwo main reasons9 First because even effective legislation willtake time to be implemented and to have an impact Second itmay help to allay concerns that shocks to poverty will be corre-lated with land reform efforts an issue to which we return belowFixed effects at the state level control for the usual array ofcross-state differences in history and economic structure thathave been constant over our sample period while the year effectscover for macro-shocks and policies enacted by the central govern-ment that affect poverty and growth

Table III gives the basic picture from our data In column (1)we control for other factors affecting poverty only by using stateand year effects Land reform is represented only by the cumula-tive land reform variable where all types of land reforms areaggregated The negative and signicant association betweenland reform and the rural poverty gap measure is clear from thisColumn (2) conrms that this result is not sensitive to using theinterpolated years when there were no NSS rounds In column (3)land reforms are disaggregated into their component types alsolagged four periods This suggests that tenancy reforms and theabolition of intermediaries are driving the aggregate effects whileland ceiling legislation and consolidation of landholdings have anegligible impact on rural poverty Below we will suggest atheoretical interpretation of the results that is consistent withthis nding The fact that land ceiling legislation is unimportantconrms anecdotal accounts of the failure to implement thesereform measures in any serious way Bardhan 1970 Appu 1996

9 The results are not sensitive to the exact lag specication chosen here

LAND POVERTY AND GROWTH INDIA 405

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 18: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

Behuria 1997 Mearns 1998 Column (4) checks the sensitivity ofthe ndings to using an alternative measure of povertymdashthehead-count index A similar negative impact of tenancy reformand the abolition of intermediaries on poverty is found here

If land reform is really responsible for these results (ratherthan some omitted variable that is correlated with land reform)

TABLE IIILAND REFORM AND POVERTY IN INDIA BASIC RESULTS

Model

Ruralpoverty

gap

Ruralpoverty

gap

Ruralpoverty

gap

Ruralheadcount

Urbanpoverty

gap

Povertygap

difference

Povertygap

difference

Head-count

difference

(1) (2) (3) (4) (5) (6) (7) (8)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

GLSAR(1)

Four-year laggedcumulative landreformlegislation

2 0281(218)

2 0443(321)

0085(105)

2 0534(524)

Four-year laggedcumulativetenancy reformlegislation

2 0604(252)

2 1378(313)

2 0736(327)

2 1916(437)

Four-year laggedcumulativeabolition ofintermediarieslegislation

2 2165(408)

2 4354(411)

2 1327(259)

2 3364(373)

Four-year laggedcumulative landceilinglegislation

0089(011)

0734(086)

0230(061)

0888(114)

Four-year laggedcumulative landconsolidationlegislation

0456(082)

2 0208(019)

2 0210(042)

2 1737(162)

State effects YES YES YES YES YES YES YES YESYear effects YES YES YES YES YES YES YES YESNumber obser-

vations507 300 507 507 507 507 507 507

z-statistics are in parentheses See the Data Appendix for details on construction and sources of thevariables The data are for the sixteen main states We use data 1961ndash1992 for fourteen states For Haryanawhich split from the Punjab in 1965 we use data 1965ndash1995 and for Jammu and Kashmir we use data1961ndash1991 as there was no NSS survey in 1992 This gives us a sample size of 507 The sample size in column(2) is smaller as it is only run for years when NSS surveys were carried out Poverty measures in otherregressions have been interpolated between survey years The GLS AR(1) model allows a state-specic AR(1)processmdashsee equation (1) in the text for details In columns (6) and (7) the poverty gap difference is thedifference between the rural and urban poverty gap In column (5) the headcount difference is the differencebetween the rural and urban head-count index

QUARTERLY JOURNAL OF ECONOMICS406

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 19: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

then we would not expect to see such effects on urban povertyThere is no good reason to think production and distributiondecisions in the urban sector would be affected (apart from somecomplex general equilibrium reasons) This is conrmed in col-umn (5) of Table III which nds no signicant negative associationbetween land reform and urban poverty as measured by the sameNSS data This adds credence to the idea that our land reformvariable is picking up something peculiar to the rural sector

Columns (6)ndash(8) use the difference between rural and urbanpoverty as the left-hand-side variable As we observed fromcolumn (5) urban poverty does not respond to land reform Thishelps to control for any omitted variables that have commoneffects on poverty in both places10 Column (6) conrms our ndingthat aggregate cumulative land reforms lagged four periods arenegatively associated with a reduction in rural-urban povertydifference Results broken out by type of land reform are consis-tent with those for rural poverty tenancy reforms and theabolition of intermediaries have had a signicant impact inclosing rural-urban poverty gap while the impact of the other twotypes of land reform are insignicant (column (7)) Using the gapbetween rural and urban head-count index yields similar ndings(column (8))

Taken together these results demonstrate a consistent pic-ture11 Land reform in general appears to be associated withreductions in rural poverty with these effects most strongly

10 Unlike poverty levels it is also a variable that does not trend downwardovertime In the levels regression the cumulative nature of our land reformvariable makes it difficult to identify its effect separately from a state-specic timetrend Indeed including state-specic time trends as regressors in a poverty levelsregression leads to the land reform variable becoming less signicant Howeverwhen the poverty difference is included as the left-hand-side variable the effectof land reforms remains signicant even when state-specic time trends areincluded

11 These results assume that the effects of each land reform work indepen-dently from one another To reect the possibility that packaging of certain reformsis important we ran our basic specications including interactions between thedifferent types of land reforms No general pattern emerges from this exercisealthough there is some suggestive evidence that undertaking both tenancy reformand abolition of intermediaries together enhances the impact of land reformfurther However this nding is somewhat sensitive to the exact measure ofpoverty used and the inclusion of particular control variables We also consideredwhether there was a difference between land reforms enacted recently comparedwith those more than ten years ago To this end we reran the main resultsseparating out a variable cumulating recent land reforms and those more than tenyears old We found that both enter negatively and signicantly in the povertyregressions with the older land reforms frequently taking an (absolutely) largecoefficient Following Moene 1992 we also investigated whether land reforms inmore densely populated states appeared to have a larger impact on poverty Formost of the specications that we looked at this was indeed the case

LAND POVERTY AND GROWTH INDIA 407

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 20: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

associated with land reforms that seek to abolish intermediariesand reform the conditions of tenancies

B Robustness

While these results are clean they leave two signicantconcerns unmet First they make no effort to allow for otherpolicies that affect povertymdashland reform may be proxying forother policies that are correlated with poverty reduction Secondland reform could be endogenous and responding to the sameforces that drive poverty We now address both of these concerns

Table IV reports results that include an array of additionalcontrols All regressions now include the population growth rateand agricultural yield lagged four periods The latter may proxyfor other policies that could have enhanced agricultural productiv-ity and are correlated with land reform It may also pick upexogenous technological change Our policy measures are in twocategories reecting the expenditure and tax policies of stategovernments Our expenditure variables are health expendituresper capita education expenditures per capita and other expendi-tures per capita12 The former two might be thought to beimportant determinants of poverty reduction efforts On the taxside we have two rather crude measures that give a picture of thegeneral policy stance of the government in office State taxesexpressed as a share of state domestic product crudely serve tomeasure the size of the state government We can also measurehow much the government is intent on designing a tax systemthat is geared toward taxing the better off We create a measure ofthe progressiveness of the tax system under state control This isthe sum of land taxes agricultural income taxes and propertytaxes expressed in real per capita terms All policy variables arelagged four periods to give the same timing structure as the landreform variables and to minimize concerns about the possibleendogeneity of these policy variables

In columns (1)ndash(6) of Table IV we replicate the regressions ofland reform on poverty including these other policies13 Irrespec-tive of the specication state redistributive taxes and state taxshare exert signicant negative impacts on rural poverty whereas

12 That is total expenditure excluding health and education13 We experimented with an array of specications that included a larger

array of controls for government expenditure including those on food securityfamine relief rural infrastructure and other social services and ner disaggrega-tions of taxes Including these variables did not affect our key results in anysignicant way so we have decided to use a more parsimonious specication

QUARTERLY JOURNAL OF ECONOMICS408

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 21: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TAB

LE

IVL

AN

DR

EF

OR

MA

ND

PO

VE

RT

YIN

IND

IA

CO

NT

RO

LL

ING

FO

RO

MIT

TE

DP

OL

ICY

EF

FE

CT

S

Mod

el

Ru

ral

pove

rty

gap

Ru

ral

pove

rty

gap

Ru

ral

hea

dco

un

tU

rban

pove

rty

gap

Pov

erty

gap

diff

eren

ceH

ead

cou

nt

diff

eren

ce

(1)

(2)

(3)

(4)

(5)

(6)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dre

form

legi

slat

ion

20

378

(37

8)0

037

(00

42)

20

539

(46

3)2

129

8(5

04)

Fou

r-ye

arla

gged

cum

ulat

ive

tena

ncy

refo

rmle

gisl

atio

n2

056

5(2

32)

20

897

(19

8)F

our-

year

lagg

edcu

mul

ativ

eab

olit

ion

inte

rmed

iari

esle

gisl

atio

n2

179

0(2

81)

23

14(2

48)

Fou

r-ye

arla

gged

cum

ulat

ive

lan

dce

ilin

gle

gisl

atio

n2

035

2(0

82)

20

121

(01

4)F

our-

year

lagg

edcu

mul

ativ

ela

nd

con

soli

dati

onle

gisl

atio

n0

164

(03

2)2

100

0(1

02)

Pop

ula

tion

grow

thra

te2

906

1(1

14)

297

99

(12

1)2

875

9(0

50)

274

32

(12

2)74

81

(09

1)2

145

05(0

90)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

006

3(2

04)

007

0(2

24)

007

6(1

10)

004

1(1

73)

007

7(2

18)

003

4(0

42)

Fou

r-ye

arla

gged

per

capi

tah

ealt

hex

pend

itur

e0

038

(08

8)0

041

(09

1)0

072

(07

6)2

000

3(0

09)

004

2(0

83)

021

8(1

76)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

002

0(2

69)

001

7(2

31)

002

6(1

56)

001

2(2

40)

000

09(0

12)

20

008

(04

0)F

our-

year

lagg

edpe

rca

pita

redi

stri

buti

vest

ate

taxe

s2

013

0(2

70)

20

142

(29

2)2

036

4(3

25)

20

045

(12

5)2

018

2(3

53)

20

422

(32

1)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

oduc

t2

495

9(2

99)

249

11

(29

4)2

873

3(2

46)

227

70

(22

3)16

43

(09

7)4

790

(01

3)F

our-

year

lagg

edag

ricu

ltu

raly

ield

000

1(0

05)

20

003

(00

2)2

050

7(1

19)

20

006

(04

2)0

031

(14

5)2

001

3(0

30)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SYe

aref

fect

sY

ES

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

436

436

436

436

436

436

z-st

atis

tics

are

inpa

ren

thes

esS

eeth

eD

ata

App

end

ixfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

64ndash1

992

for

nin

est

ates

F

orP

un

jab

we

hav

eda

ta19

69ndash1

992

for

Har

yan

aw

hic

hsp

lit

from

the

Pu

nja

bin

1965

we

hav

eda

ta19

70ndash1

975

and

1978

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1968

ndash199

1fo

rB

ihar

and

Gu

jara

t19

64ndash1

975

and

1977

ndash199

2fo

rT

amil

Nad

u19

64ndash1

975

and

1978

ndash199

2an

dfo

rB

ihar

1964

196

9an

d19

72ndash1

977

Th

isgi

ves

us

ato

tals

amp

lesi

zeof

436

Inco

lum

n(5

)th

epo

vert

yga

pd

iffe

ren

ceis

the

diff

eren

cebe

twee

nth

eru

ral

and

urb

anpo

vert

yga

pIn

colu

mn

(6)

the

hea

d-co

un

tdi

ffer

ence

isth

ed

iffe

ren

cebe

twee

nth

eru

ral

and

urb

anh

ead-

cou

nt

inde

xT

heG

LS

AR

(1)m

odel

allo

ws

ast

ate-

spec

icA

R(1

)pro

cess

mdashse

eeq

uati

on(1

)in

the

text

for

deta

ilsR

edis

trib

uti

veta

xes

are

agri

cult

ura

linc

ome

taxe

sla

nd

taxe

san

dpr

oper

tyta

xes

LAND POVERTY AND GROWTH INDIA 409

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

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041

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041

041

0

t-st

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tics

are

inpa

ren

thes

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llre

gres

sion

sar

ere

port

edw

ith

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stst

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rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

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tle

fta

nd

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dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

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riod

sIV

2In

stru

men

tsfo

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enou

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licy

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able

(cu

mu

lati

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nd

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lagg

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ur

peri

ods)

are

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stat

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bly

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(cu

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nd

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ur

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iods

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esh

ares

ofse

ats

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asse

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ied

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ess

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les

are

excl

ud

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ere)

Th

eov

erid

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tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 22: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

education and health expenditure per capita yield and popula-tion growth are generally insignicant at conventional levels14 Incolumn (1) we include the full set of policy control variables in thebasic regression of cumulative land reform on the rural povertygap measure Despite controlling for these many dimensions ofstate activity cumulative land reform continues to exert a nega-tive and signicant impact on rural poverty In column (2) we runthe same regression while disaggregating the land reform vari-able We continue to nd that tenancy reforms and the abolition ofintermediaries exert a negative and signicant impact on therural poverty gap measure whereas land ceiling and land consoli-dation legislation exert no signicant inuence Replacing thepoverty gap measure with the head-count index as is done incolumn (3) produces a similar set of results When we examine theurban poverty regression (column (4)) we nd that in commonwith the rural poverty regressions health and education expendi-ture and yield have no signicant impact and tax share has asignicant impact State redistributive taxes are insignicant inthis regression suggesting that their impact is restricted to therural sector Inclusion of these extra variables has no effect on theinsignicant impact of cumulative land reform on urban poverty

Columns (5) and (6) regress the difference between rural andurban poverty on cumulative land reform and the full set ofcontrol variables Note that compared with column (1) of thistable only the land reform variable and state redistributive taxesremain signicant in this specication15 Other policy effectsappear to be common to both rural and urban sectors becominginsignicant in this regression Contrasting columns (5) and (6)conrms that results are robust to the type of poverty measurebeing used Taken together the results presented in Table IV offerfurther conrmation of our initial nding of a signicant negativeassociation between lagged land reform and rural poverty

A further concern with the specication in equation (1) is thepotential endogeneity of the land reform variable It is notpossible to ascertain the direction of bias due to this a priori If

14 The expenditure results are interesting given the priority attached incurrent debates to expansion of expenditures on education and health as a keymeans of reducing poverty (see Dreze and Sen 1995) If anything educationexpenditures per capita seem to exert a positive inuence on the rural poverty gap(columns (1) and (2)) but not on the rural head-count ratio (column (3)) However itis possible that we would need ner measures of the ways in which particularprograms are prioritized to make progress on this

15 An exception is education expenditure per capita in the poverty gapspecication (see column (5))

QUARTERLY JOURNAL OF ECONOMICS410

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

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gres

sh

ard

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nd

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ssed

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ally

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gged

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licy

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able

(cu

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nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

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ied

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ongr

ess

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dle

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riod

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nd

refo

rmva

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les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 23: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

land reform is purposefully aimed at poverty reduction then wewould expect policy effort to focus on where poverty is highestleading to downward bias However if responsiveness to landreform is greater where poverty is highest then the effect may goin the other direction While lagging land reform as we have in (1)goes some way toward minimizing concerns about this there issome residual worry that long-lived shocks to poverty that affectantipoverty legislation could bias the results

To x this problem requires an instrument for land reform16

To this end we exploit the fact that land reform is intenselypolitical with different groupings in state legislatures (the Vid-han Sabha) being more likely to enact land reform legislationHowever this can be problematic if as seems likely shocks topoverty affect who is elected To mitigate this problem we proposeusing long lags of the political variables as instruments for landreform Specically political variables from four periods prior tothe land reform (eight periods before the poverty observation) areused as an instrument for land reform This is legitimate providedthat contemporaneous shocks to poverty are uncorrelated withshocks that lead to particular groups being elected eight yearspreviously Such an assumption seems defensible given both thefrequency of elections and policy shifts in India and because it isdifficult to think of long-lasting shocks affecting both currentpoverty and political structure eight years ago

This strategy implies a rst-stage equation for land reform

(2) lst 5 microlst2 4 1 as 1 bt 1 cyit 1 dzst2 4 1 h st

where lst is the cumulative land reform variable as is a state xedeffect bt is a year dummy variable yst is a vector of variables thatwe treat as exogenous and the variables zst2 4 are politicalvariables reecting the seat shares of different political groupseach lagged by four years These are constructed from records ofthe number of seats won by different national parties at each ofthe state elections under four broad groupings (The partiescontained in the relevant group are given in parentheses after thename of the grouping) These are (i) Congress Party (IndianNational Congress 1 Indian Congress Socialist 1 Indian Na-tional Congress Urs 1 Indian National Congress Organization)(ii) a hard left grouping (Communist Party of India 1 Communist

16 This will also help to deal with measurement error which is a concerngiven that we measure only legislated land reforms

LAND POVERTY AND GROWTH INDIA 411

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

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tle

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nd

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esla

gged

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dsp

lus

cum

ula

tive

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dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

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riod

sIV

3In

stru

men

tsfo

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een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 24: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

Party of India Marxist) (iii) a soft left grouping (SocialistParty 1 Praja Socialist Party) and (iv) Hindu parties (BhartiyaJanata Party 1 Bhartiya Jana Sangh) We express these as ashare of total seats in the legislature Congress has tended todominate the assemblies over the period although hard leftparties have also recorded majorities in Kerala and West BengalOver time there has been a decline in the importance of Congressand a rise in the importance of religious and regional parties

Table V presents estimates of equation (2) for the differentkinds of land reforms As we would expect all cases nd laggedland reforms to be strongly signicant The political variables alsomatter for land reform legislation and are jointly signicant in allcolumns In column (1) we see that relative to the omitted lsquolsquootherrsquorsquocategory which is composed of a amalgam of regional indepen-dent and Janata parties Congress and soft left decrease theprobability of enacting land reform legislation while hard leftexerts a positive inuence and Hindu parties are insignicantLooking across columns (2) to (5) we see that the negativeinuence of Congress is spread across all types of land reform butit is particularly pronounced for tenancy reforms and abolition ofintermediaries The negative inuence of soft left parties is alsospread across the board with the exception of land consolidationThe overall positive inuence of hard left parties however seemsto originate principally through a strong positive effect on thepassage of land ceiling legislation This is interesting given ourfailure to nd evidence that such reforms reduce poverty Hinduparty representation appears to exert no inuence on the passageof tenancy reforms or the abolition of intermediaries Howeverthey exert a signicant positive inuence on land ceiling and asignicant negative inuence on land consolidation

Table VI presents our results from instrumental variablesestimation Column (1) which uses political variables and laggedland reforms as instruments continues to nd a negative andsignicant impact of land reform on the rural poverty gap We nda similar result when we use the head-count poverty measure inplace of the poverty gap measure in column (2) Columns (3) and(4) follow a similar instrumentation procedure but break out totalland reforms into constituent types This conrms our earlierresults both tenancy reforms and abolition of intermediariesremain negative and signicant while other types of land reform

QUARTERLY JOURNAL OF ECONOMICS412

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 25: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TABLE VLAND POLICY DETERMINATION

Model

Cumulativetotal land

reformlegislation

Cumulativetenancyreform

legislation

Cumulativeabolition of

intermediarieslegislation

Cumulativeland ceilinglegislation

Cumulativeland

consolidationlegislation

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Four-year laggedcumulativeland reform leg-islation

0406(1223)

Four-year laggedcumulative ten-ancy reformlegislation

0693(1626)

2 0002(016)

2 0009(038)

0021(113)

Four-year laggedcumulative abo-lition of inter-mediaries legis-lation

0041(053)

0664(1421)

0109(151)

2 0029(106)

Four-year laggedcumulativeland ceiling leg-islation

2 0131(211)

2 0172(065)

0631(1560)

2 0045(144)

Four-year laggedcumulativeland consolida-tion legisla-tion

0694(506)

2 0038(114)

0174(293)

0772(785)

Four-year laggedcongress partyshare of seats

2 0460(281)

2 0472(478)

2 0098(237)

2 0066(185)

2 0075(185)

Four-year laggedhard left shareof seats

2837(295)

0476(072)

0149(097)

1437(546)

2 0302(073)

Four-year laggedsoft left share ofseats

2 3921(309)

2 2363(325)

2 1101(260)

2 1990(363)

2 0426(106)

Four-year laggedhindu partiesshare of seats

0270(033)

2 0089(019)

2 0045(015)

0556(201)

2 0410(208)

State effects YES YES YES YES YESYear effects YES YES YES YES YESNumber of obser-

vations474 474 474 474 474

t-statistics are in parentheses All regressions are reported with robust standard errors All monetaryvariables are in real terms See the DataAppendix for details on construction and sources of the variables Thedata are for the sixteen main states We have data 1962ndash1992 for eight states Punjab and Haryana split intoseparate states in 1965 For Punjab we have data 1962ndash1989 while for Haryana we have data 1969ndash1991 ForJammu and Kashmir we have data 1965ndash1991 for Kerala and West Bengal 1962ndash1991 for Gujarat andMaharashtra 1963ndash1992 and for Bihar 1962ndash1989 This gives us a total sample size of 474 The partiescontained in the relevant group are given in parentheses after the name of the grouping These are (i)Congress Party (Indian National Congress 1 Indian Congress Socialist 1 Indian National CongressUrs 1 Indian National Congress Organization) (ii) a hard left grouping (Communist Party ofIndia 1 Communist Party of India Marxist) (iii) a soft left grouping (Socialist Party 1 Praja Socialist Party)and (v) Hindu parties (Bhartiya Janata Party 1 Bhartiya Jana Sangh)

LAND POVERTY AND GROWTH INDIA 413

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

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ogof

agri

cult

ura

lyie

ld

(1)

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(3)

(4)

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SA

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)G

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(1)

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)G

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(1)

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R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

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(12

53)

On

e-ye

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gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

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ta0

195

(41

7)0

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9)F

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edcu

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ativ

ete

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form

s2

000

2(0

43)

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037

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92)

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gged

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ulat

ive

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rmed

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es2

000

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016

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013

(04

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our-

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edcu

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ativ

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ion

20

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nd

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olid

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ula

tion

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gged

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tion

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ture

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ndit

ures

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gged

per

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her

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ndi

ture

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000

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nu

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tage

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dom

esti

cpr

odu

ct0

474

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4)0

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edlo

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agri

cult

ura

lyie

ld0

010

(01

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001

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Sta

teef

fect

sY

ES

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ES

Year

effe

cts

YE

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SN

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ber

ofob

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atio

ns

484

484

433

488

433

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ren

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inco

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per

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tain

edby

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essi

ng

esti

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esof

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edo

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tic

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ctin

real

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tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

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rati

oof

real

agri

cult

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ted

omes

tic

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duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 26: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TAB

LE

VI

LA

ND

RE

FO

RM

AN

DP

OV

ER

TY

ININ

DIA

IN

ST

RU

ME

NT

AT

ION

Mod

el

Rur

alpo

vert

yga

p

Rur

alh

ead

cou

nt

Rur

alpo

vert

yga

p

Rur

alhe

adco

unt

Pov

erty

gap

diff

eren

ce

Rur

alpo

vert

yga

p

Ru

ral

head

coun

t

Rur

alhe

adco

unt

Ru

ral

pove

rty

gap

Ru

ral

head

cou

nt

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

IV1

IV1

IV1

IV1

IV1

IV2

IV2

IV2

IV3

IV3

Fou

r-ye

arla

gged

cum

ula

tive

land

refo

rmle

g-is

lati

on2

073

2(6

02)

21

360

(56

8)2

043

8(3

60)

20

659

(40

9)2

119

2(3

67)

20

599

(31

8)2

126

3(3

24)

Fou

r-ye

arla

gged

cum

ula

tive

ten

ancy

refo

rmle

gisl

atio

n2

099

8(3

16)

22

404

(36

7)2

459

5(4

69)

Fou

r-ye

arla

gged

cum

ula

tive

abol

itio

nof

inte

rmed

iari

esle

gisl

atio

n2

227

1(2

58)

25

701

(36

4)2

740

8(4

10)

Fou

r-ye

arla

gged

cum

ula

tive

land

ceil

ing

leg-

isla

tion

21

372

(23

4)0

432

(03

8)2

199

8(1

89)

Fou

r-ye

arla

gged

cum

ula

tive

land

cons

olid

a-ti

onle

gisl

atio

n1

624

(17

2)1

969

(10

0)2

402

7(1

45)

Ove

ride

nti

cati

onte

stp-

valu

e0

930

980

990

980

990

930

980

980

920

96St

ate

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Num

ber

ofob

serv

atio

ns41

041

041

041

041

041

041

041

041

041

0

t-st

atis

tics

are

inpa

ren

thes

esA

llre

gres

sion

sar

ere

port

edw

ith

robu

stst

anda

rder

rors

See

the

Dat

aA

ppe

ndi

xfo

rde

tail

son

con

stru

ctio

nan

dso

urc

esof

the

vari

able

sT

he

data

are

for

the

sixt

een

mai

nst

ates

We

hav

eda

ta19

66ndash1

992

for

twel

vest

ates

For

Har

yan

aw

hic

hsp

lit

from

Pu

nja

bin

1965

we

hav

ed

ata

1973

ndash199

2fo

rJa

mm

uan

dK

ash

mir

1969

ndash199

2an

dfo

rG

uja

rat

and

Mah

aras

htr

a19

67ndash1

992

Th

isgi

ves

us

ato

tals

ampl

esi

zeof

410

Inco

lum

n(5

)pov

erty

gap

dif

fere

nce

isth

edi

ffer

ence

betw

een

rura

lan

du

rban

pove

rty

IV1

Inst

rum

ents

for

the

endo

gen

ous

poli

cyva

riab

le(c

um

ula

tive

lan

dre

form

sla

gged

fou

rpe

riod

s)ar

esh

are

ofse

ats

inst

ate

asse

mbl

yoc

cupi

edby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dspl

us

lan

dre

form

vari

able

sla

gged

eigh

tpe

riod

sIV

2In

stru

men

tsfo

rth

een

dog

enou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

peri

ods)

are

shar

eof

seat

sin

stat

eas

sem

bly

occu

pie

dby

Con

gres

sh

ard

left

sof

tle

fta

nd

Hin

dup

arti

esla

gged

eigh

tp

erio

dsp

lus

cum

ula

tive

lan

dre

form

spa

ssed

inge

ogra

phic

ally

con

tigu

ous

stat

esla

gged

eigh

tpe

riod

sIV

3In

stru

men

tsfo

rth

een

doge

nou

spo

licy

vari

able

(cu

mu

lati

vela

nd

refo

rms

lagg

edfo

ur

per

iods

)ar

esh

ares

ofse

ats

inst

ate

asse

mbl

yoc

cup

ied

byC

ongr

ess

har

dle

ftan

dso

ftle

ftp

arti

esla

gged

eigh

tpe

riod

s(l

agge

dla

nd

refo

rmva

riab

les

are

excl

ud

edh

ere)

Th

eov

erid

enti

ca

tion

test

we

empl

oyis

due

toS

arga

n1

958

Th

en

um

ber

ofob

serv

atio

ns

tim

esth

eR

2

from

the

regr

essi

onof

the

stat

e2

resi

dual

son

the

inst

rum

ents

isd

istr

ibu

ted

x2

(T1

1)w

her

eT

isth

en

um

ber

ofin

stru

men

ts

QUARTERLY JOURNAL OF ECONOMICS414

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 27: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

are insignicant17 Column (5) conrms that land reform still hasa signicant impact in closing the gaps between rural and urbanpoverty We also report tests of our overidentifying restrictions forthe instrumental variables regressions The political and laggedland reform variables pass standard statistical tests of overidenti-cation and therefore at least on econometric grounds wouldappear to be suitable instruments for land reforms18 Thus whenthe instrument set includes political variables and lagged landreforms the picture is consistent with the patterns of resultsshown in Tables III and IV

The remainder of Table VI experiments with alternatives tousing lagged land reforms as instruments In columns (6)ndash(8) weuse cumulative land reforms passed in geographically neighbor-ing states (lagged eight periods) in our instrument set in place ofcumulative land reforms lagged eight periods These neighboringland reforms could proxy for regional waves of support for landreform Using these together with the political variables asinstruments yields robust results Aggregate land reforms con-tinue to exert a negative and signicant impact on the ruralpoverty gap (column (6)) or rural head count (column (7)) Whenwe break out land reforms by type we again nd tenancy reformsand abolition of intermediaries exerting the strongest negativeinuences on the head-count index (column (8)) The overidenti-cation tests are also passed In columns (9) and (10) of Table VI wedrop lagged land reforms completely from the instrument set Wecontinue to obtain a negative impact of land reforms on the ruralpoverty gap (column (9)) or the rural headcount (column (10)) foraggregate land reforms19

Taken together Table VI nds a pattern of results that isconsistent with those presented in Tables III and IV20 It is alsoreassuring that the magnitude of coefficients remains roughly

17 With the exception of land ceilings in column (3)18 The test we employ is due to Sargan 1958 and tests whether the

instruments are correlated with residuals from the second-stage (poverty) regres-sion See notes to Table VI

19 We did not obtain signicant effects for disaggregated land reforms in thisspecication

20 We also experimented with a fourth instrumentation procedure where theendogenous policy variable (cumulative land reforms lagged four periods) isinstrumented using a lsquolsquosimulatedrsquorsquo cumulative land index created by cumulatingvalues from a linear probability model which predicts whether a land reform takesplace in a given year based on political composition of the state parliament (laggedfour periods) and year and state effects As with the three other procedures wefound that instrumented aggregate land reform had a signicant negative impacton the rural poverty gap

LAND POVERTY AND GROWTH INDIA 415

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 28: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

constant across the different instrumentation procedures On thewhole the instrumented coefficients on land reform are largerthan the baseline results of Tables III and IV Overall theseresults are best thought of as a robustness check on our earlierndings rather than trying to present a carefully thought outstructural model

IV LAND REFORM AND AGRICULTURAL WAGES

It would be surprising if land reforms that affected povertydid not impact on other aspects of the rural economy We nowconsider whether such reforms have an effect on agriculturalwages The wage data are for the daily agricultural wages of malelaborers expressed in real terms21 Agricultural wages are arobust indicator of the welfare of landless laborers who comprise asignicant fraction of the poor in rural India (see World Bank1997) If land reform pushes up agricultural wages this repre-sents an additional mechanism through which these reforms canreduce rural poverty

The results using the agricultural wage as a left-hand-sidevariable are in Table VII Column (1) contains results for theaggregate land reform variable This demonstrates a positive andsignicant impact of land reform on wages In column (2) thiseffect is disaggregated across types of land reform and shows thatthis effect is primarily attributable to legislation to abolishintermediaries These results conrm the impact of land reformson the rural economy They also illustrate an indirect routethrough which land reform may positively affect the welfare oflandless laborers even if they do not benet directly from thereforms In Section VII we discuss why such effects might bepresent in theory

V LAND REFORM AND GROWTH

Even if land reform does help the poor it could do so at a costto economic performance We turn now therefore to exploringwhether land reform has a positive or negative effect on agricul-tural output per capita In this case we use the log of real stateincome per capita as the left-hand-side variable with the right-hand side augmented by lagged log real state income per capita to

21 See the Data Appendix for details

QUARTERLY JOURNAL OF ECONOMICS416

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 29: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

model dynamics in a very simple way and to allow for convergenceover time22 We therefore have a regression of the form

(3) xst 5 l xst 2 1 1 a s 1 b t 1 g yst 1 c lst 2 4 1 e st

This is basically the same form of regression that has becomepopular in the cross-country growth literature summarized inBarro 1997 although our panel data allow us to use xed effectsand year effects We will also continue to allow for a state-specicAR(1) error specication with heteroskedasticity

Table VIII presents the main results for the regression ofstate income per capita on cumulative land reform In column (1)we present results for a GLS model of total state income per capitaon land reform containing only state xed effects and year effectsas controls We nd that the disaggregated land reform variables

22 Statewise estimates of total and agricultural state domestic product areavailable for the 1960ndash1992 period See the Data Appendix These state domesticproduct estimates are used as our proxy of state income

TABLE VIILAND REFORM AND AGRICULTURAL WAGES

Model

Real agriculturalwages

Real agriculturalwages

(1) (2)

GLSAR(1)

GLSAR(1)

Four-year lagged cumulative land reformlegislation

0081(271)

Four-year lagged cumulative tenancyreform legislation

0049(088)

Four year lagged cumulative abolition ofintermediaries legislation

0339(261)

Four-year lagged cumulative land ceilinglegislation

0069(009)

Four-year lagged cumulative consolida-tion of land holdings legislation

0018(013)

State effects YES YESYear effects YES YESNumber of observations 441 441

z-statistics are in parentheses The wage data refer to the daily wage rate for male agricultural laborersexpressed in real terms See the Data Appendix for details on construction and sources of the variables Thedata are for fourteen statesmdashdata for Haryana and Jammu and Kashmir are not available For thirteen ofthese states we have data 1961ndash1992 and for Rajasthan we have 1967ndash1991 This gives a sample size of 441GLS AR(1) model allows a state-specic AR(1) processmdashsee equation (1) in the text for details

LAND POVERTY AND GROWTH INDIA 417

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

ofst

ate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta

Log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

taL

ogof

agri

cult

ura

lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

gged

log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

Fou

r-ye

arla

gged

cum

ulat

ive

abol

itio

nof

inte

rmed

iari

es2

000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

nde

nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 30: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

TAB

LE

VII

IL

AN

DR

EF

OR

MA

ND

GR

OW

TH

ININ

DIA

Mod

el

Log

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inco

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ta

Log

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ricu

ltu

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tate

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ta

Log

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ltu

rals

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inco

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per

capi

taL

ogof

agri

cult

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lyie

ldL

ogof

agri

cult

ura

lyie

ld

(1)

(2)

(3)

(4)

(5)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)G

LS

AR

(1)

GL

SA

R(1

)

On

e-ye

arla

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log

ofst

ate

inco

me

per

capi

ta0

497

(12

53)

On

e-ye

arla

gged

log

ofag

ricu

ltu

rals

tate

inco

me

per

capi

ta0

195

(41

7)0

167

(32

9)F

our-

year

lagg

edcu

mul

ativ

ete

nan

cyre

form

s2

000

2(0

43)

20

037

(45

4)2

003

3(2

94)

20

050

(65

5)2

003

8(3

92)

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r-ye

arla

gged

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ulat

ive

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nof

inte

rmed

iari

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000

5(0

54)

000

5(0

27)

20

016

(07

6)2

000

2(0

12)

20

013

(04

9)F

our-

year

lagg

edcu

mul

ativ

ela

nd

ceil

ing

legi

slat

ion

20

002

(02

2)0

019

(12

6)0

012

(06

4)0

015

(09

5)0

015

(08

8)F

our-

year

lagg

edla

nd

cons

olid

atio

nle

gisl

atio

n2

001

3(1

29)

006

5(3

31)

005

7(2

12)

007

4(3

87)

005

4(2

15)

Pop

ula

tion

grow

thra

te2

256

7(0

75)

416

6(1

11)

Fou

r-ye

arla

gged

per

capi

taed

uca

tion

expe

ndi

ture

s0

003

(14

8)0

003

(16

7)F

our-

year

lagg

edpe

rca

pita

hea

lth

expe

ndit

ures

20

005

(19

7)2

000

2(0

77)

Fou

r-ye

arla

gged

per

capi

taot

her

expe

ndi

ture

s2

000

04(0

99)

20

0002

(04

0)F

our-

year

lagg

edpe

rca

pita

tax

reve

nu

efr

omre

dist

ribu

tive

taxe

s2

000

4(1

51)

20

003

(10

5)F

our-

year

lagg

edst

ate

taxe

sas

ape

rcen

tage

ofst

ate

dom

esti

cpr

odu

ct0

474

(05

4)0

278

(03

1)F

our-

year

lagg

edlo

gof

agri

cult

ura

lyie

ld0

010

(01

7)2

001

8(0

32)

Sta

teef

fect

sY

ES

YE

SY

ES

YE

SY

ES

Year

effe

cts

YE

SY

ES

YE

SY

ES

YE

SN

um

ber

ofob

serv

atio

ns

484

484

433

488

433

z-st

atis

tics

are

inpa

ren

thes

esS

tate

inco

me

per

cap

ita

isob

tain

edby

expr

essi

ng

esti

mat

esof

stat

edo

mes

tic

pro

du

ctin

real

per

capi

tate

rms

Agr

icu

ltu

raly

ield

mea

sure

sre

pres

ent

the

rati

oof

real

agri

cult

ura

lsta

ted

omes

tic

pro

duct

ton

etso

wn

area

Red

istr

ibu

tive

taxe

sar

eag

ricu

ltu

rali

nco

me

taxe

sla

nd

taxe

san

dp

rop

erty

taxe

sS

eeth

eD

ata

Ap

pen

dix

for

deta

ils

onco

nst

ruct

ion

and

sou

rces

ofth

eva

riab

les

Th

ed

ata

are

for

the

sixt

een

mai

nst

ates

For

colu

mn

s(1

)an

d(2

)we

hav

eda

ta19

61ndash1

992

for

twel

vest

ates

for

Pu

nja

ban

dH

arya

na

wh

ich

spli

tin

1965

we

hav

eda

ta19

66ndash1

992

for

Jam

mu

and

Kas

hm

ir19

65ndash1

992

and

for

Bih

ar19

611

966

and

1969

ndash199

2T

his

give

sa

sam

ple

size

of48

4T

he

sam

ple

size

inco

lum

n(4

)is

slig

htl

yla

rger

asit

does

not

con

tain

ala

gged

depe

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nt

vari

able

asre

gres

sor

For

colu

mn

s(3

)an

d(5

)w

eh

ave

dat

a19

64ndash1

992

for

nin

est

ates

fo

rP

un

jab

1969

ndash199

2fo

rH

arya

na

1970

ndash197

5an

d19

78ndash1

992

for

Jam

mu

and

Kas

hm

ir19

68ndash1

992

for

Bih

aran

dG

uja

rat

1964

ndash197

5an

d19

77ndash1

992

for

Ass

am19

69an

d19

72ndash1

992

and

for

Tam

ilN

adu

1964

ndash197

5an

d19

78ndash1

992

Th

isgi

ves

asa

mpl

esi

zeof

433

GL

SA

R(1

)m

odel

allo

ws

ast

ate-

spec

ic

AR

(1)p

roce

ssmdash

see

equ

atio

n(1

)in

the

text

for

deta

ils

QUARTERLY JOURNAL OF ECONOMICS418

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 31: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

lagged four periods have no signicant impact on total stateincome per capita In column (2) we look only at agricultural stateincome per capita This makes sense given that land reform ispredominantly concerned with affecting production relations inagriculture This suggests that tenancy reform has a negativeeffect on agricultural output with land consolidation having theopposite effect No effect is observed for the other kinds of landreform Column (3) shows that both the tenancy reform and landconsolidation effects are robust to including our other policyvariables lagged four years In column (4) we show that theseeffects remain when agricultural yields rather than income percapita is the left-hand-side variable23 In column (5) we show thatthis effect of tenancy reform is robust to including other policyvariables

VI LAND REFORM AND LAND INEQUALITY

Taken together our results hint at an equity-efficiency trade-off for tenancy reformsmdashboth poverty and output per capita arelower after such reforms are enacted No such trade-off emergesfor abolition of intermediaries Ceilings on landholdings do notseem to have an effect on either output measures or poverty whileland consolidation promotes output increases in agriculture with-out affecting poverty The failure of land ceiling legislation to showany signicant impact on poverty reduction or output levels isconsistent with Bardhanrsquos 1970 claim that such reforms haverarely been implemented with any degree of seriousness

Overall these results suggest that the impact on povertycomes mainly through reforms that affect production relationsrather than by altering the distribution of land This interpreta-tion is underlined by looking at the limited evidence available onthe relationship between land reforms and land distribution overour data period Data on land distribution has only been gatheredby NSS special surveys at four points 1953ndash1954 1961ndash19621971ndash1972 and 1982 (see Sharma 1994) We classify states ashigh or low land reform depending on whether they had more orless than a total of three land reforms (of any type) during the1958ndash1992 period24 We then investigate whether high land

23 Our measure of yield is real agricultural state domestic product dividedby net sown area See the Data Appendix for details

24 Under this system Andra Pradesh Assam Haryana Jammu and Kash-mir Madya Pradesh Maharashtra Punjab and Rajasthan are low land reform

LAND POVERTY AND GROWTH INDIA 419

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 32: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

reform states classied in this way experienced the largest drop inthe gini for land operated and proportion of landless householdsover the period25 The overall impression that we have from thiscrude exercise is of persistent inequalities in land operatedwithin both groups of states (see also Sharma 1994) Thus theidea that the major impact of land reform on poverty must comemainly through mechanisms that did not involve land redistribu-tion gains further support In further conrmation of this wefailed to nd a signicant effect of aggregate land reform on thegini coefficient for rural per capita consumption26

Thus in making sense of the results it is imperative to thinkabout land reforms that have changed production relations inagriculture rather than altering the pattern of landholdings All ofthis notwithstanding there is evidence that the impact of landreforms on poverty is greatest in those states where land inequal-ity was greatest in 1953ndash1954 To test this we interacted thepercentage of landless individuals and the land gini coefficientwith our land reform variable This interaction term was negativeand signicant in every case when we looked at aggregate landreform activity27

VII MAKING SENSE OF THE RESULTS

Our empirical analysis suggests that poverty reduction isassociated with land reform and this is primarily attributable tolegislation that has abolished intermediaries and reformed theterms of tenancies The role of land redistribution per se seems tohave been of limited importance in the Indian context Theempirical analysis also uncovers some evidence of general equilib-rium effects on wages Our theoretical model focuses on twothings a model of agricultural contracting and a model of labor

states while Bihar Gujarat Karnataka Kerala Orissa Tamil Nadu UttarPradesh and West Bengal are high land reform states

25 For high land reform states the land gini falls from 0686 in 195354 to0669 in 1982 (a fall of 0017) whereas the drop in low land reform states is from0653 to 0643 (a drop of 0010) For high land reform states the average drop in theproportion landless is from 1497 percent to 1203 percent (a fall of 294 percent)whereas for low land reform states the drop is from 1240 percent to 1091 percent(a fall of 149 percent)

26 To look at this issue we ran the basic regression shown in column (1) ofTable III but replaced the rural poverty gap with the gini coefficient for rural percapita consumption Our inability to nd a signicant impact on rural inequalitycould be explained by the fact that land reform may be shifting income from themiddle income groups to the poor rather than from the rich to the poor

27 The results are available from the authors on request

QUARTERLY JOURNAL OF ECONOMICS420

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 33: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

supply by tenants The former focuses on how rents to tenantsshift in response to land reforms and the latter gives rise to effectson agricultural wages This focus on contractual problems cap-tures the spirit of recent models of the inequality-growth relation-ship that emphasize agency problems particularly in creditmarkets (See Benabou 1996 for a survey) Here we emphasizeagency problems in tenancy contracts and how they can be alteredby land reform even if the ownership pattern is unchanged

There are three groups landlords who rent out land as well asfarming some of the land themselves tenants who rent land andlandless laborers The poor are made up predominantly of thelatter two groups Tenants and landless laborers supply labor tothe labor market where it is demanded by landlords who choose tobe owner-cultivators Tenants and landless laborers care aboutconsumption c and labor supply l Their preferences are u(c) 2f (l) where u(middot) is increasing and concave and f (middot) is increasingand convex Suppose that the agricultural wage is v Then anindividual with nonlabor income x has optimal labor supply of

l(xv ) 5 larg max u(x 1 v l) 2 f (l)

It is straightforward to check that labor supply is decreasing in xNow dene v(xv ) 5 u(x 1 v l(xv )) 2 f (l(x v )) as the indirectutility of a tenant with nonlabor income x Hence we expectlandless laborers to supply l(0 v ) while for tenants x is equal tothe value of their tenancy As the value of tenancy increases as aresult of land reform we would expect tenants to reduce laborsupply to the market

We now consider the agricultural contracting problem of atenant and landlord Suppose that the output on a given piece ofland under tenancy is given by R(e) where e denotes effort appliedto the land by the tenant We suppose that the cost of this effort isseparable from labor supply and is measured in units of disutilityEffort is also committed before the labor supply decision is madeWe assume that R(middot) is smooth increasing and concave

We suppose that tenants need to be monitored in order to putin effort on the land Specically we imagine that a contractspecies an effort level of e However the tenant may choose tolsquolsquoshirkrsquorsquo putting in zero effort in which case the landlord catcheshim with probability p and he is red becoming a landless laborerand receiving a payoff of v(0 v ) The tenant can now only beinduced to supply effort if the threat of eviction is sufficientlystrong and some rents are earned from being a tenant Suppose

LAND POVERTY AND GROWTH INDIA 421

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 34: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

then that the tenant receives a payment of w to farm the landwhich he receives only if he is not caught shirking Thus a tenantis willing to put in an effort level e at payment w if and only theincentive constraint (1 2 p)v(wv ) 1 pv(0 v ) v(w v ) 2 e issatised Solving this as an equality gives the payment schedulew(e v ) needed to induce effort level e as

w(e v ) 5 v 2 1(v(0 v ) 1 e p)

The contract must now specify a paymenteffort pair consis-tent with this schedule The optimal effort that the landlordchooses to induce is given by

e( pv ) 5 arg maxe

5 R(e) 2 w(ev )

It is easy to verify that e( pv ) is increasing in p The tenantrsquosequilibrium payoff is V( p v ) 5 v(0 v ) 1 e( p v ) (1 2 p) p which islarger than the payoff from being a landless laborer

It is straightforward to calculate the impact of changes in p onoutput and the tenantrsquos payoff An increase in p will increasenet-output since e( p v ) is increasing The effect on the tenantrsquospayoff (and hence poverty) is given by

shy V( pv )

shy p5

shy e( pv )

shy p

1 2 p

p2 e( p v )

1

p2

The rst term is positivemdashan increase in the eviction probabilityelicits higher effort and hence raises the tenantrsquos rent The secondeffect works in the opposite direction For a given effort level thetenantrsquos rent is lower since he must be paid less now to preventhim from shirking We are interested in cases where the tenantenjoys a more secure right to the land so that p falls In this casethe tenant will benet from a tenancy reform that reduces theprobability that he will be evicted if caught shirking if theelasticity of effort with respect to the probability of eviction( shy e( p v )shy p middot pe( pv )) is less than 1(1 2 p) p2 If tenantsrsquo rentsincrease from receiving higher tenure security then this will leadthem to reduce their labor supply to the market and we wouldpredict that such a tightening of the labor market would lead toincreased agricultural wages28

This framework can be applied to the cases of abolition ofintermediaries and tenancy reform To include an intermediary in

28 These changes in wages would also be expected to reinforce reductions inoutput on farms that hire in labor

QUARTERLY JOURNAL OF ECONOMICS422

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 35: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

the analysis we suppose that there are three parties to theagricultural contract a tenant landlord and an intermediary Webegin by making the strong assumption that intermediaries havea very strong bargaining position can make take-it-or-leave-itoffers to the landlord and tenant This is very much in line withthe view that intermediaries captured the surplus from the landIn this world the tenant will receive a payoff of V( p v ) and thelandlord will receive his reservation payoff which we denote by vLThe intermediary receives the surplus R(e( pv )) 2 e( p v ) 2V( pv ) 2 vL

After the intermediary is abolished this surplus is nowavailable for distribution provided that p remains the same Onlyif the tenant obtains no bargaining power at all with his landlordwould we expect to observe no effect on the tenantrsquos payoffOtherwise we would expect to see the tenantrsquos payoff riseAssuming that tenants are a signicant group of poor in Indiathis is consistent with our nding that poverty is reduced by theabolition of intermediaries We would not expect to see any changein effort and hence output unless p were different when landlordsand intermediaries negotiated contracts Rent increases for ten-ants also would be associated with higher agricultural wages bythe general equilibrium mechanism we have identied

We now turn to the impact of tenancy reforms Such reformsare multifarious which make it difficult to offer a denitivetheoretical account This would require much more institutionalcontent as in the analysis of West Bengalrsquos land reforms byBanerjee and Ghatak 1997 Nonetheless it is still useful to thinkthrough a simple model in order to check that our empiricalndings conform to the predictions of the theory laid out aboveSuppose therefore that the landlord has all the bargaining powerand can make take-it-or-leave-it offers to tenants before and afterthe tenancy reform We shall model the effect of a tenancy reformas making it more difficult to evict tenants if they shirk In termsof our model this is equivalent to a fall in p As we have alreadyargued this has two effects First we expect effort and thereforeoutput to fall Second we expect a change in the payoff to thetenant as his rent could go up or down We showed that this ispositive under reasonable conditions and thus we would expectpoverty to be reduced which is what we found in the data This isalso consistent with higher agricultural wages if increased rentsto tenants lead them to reduce their labor supply

To summarize the empirical ndings are consistent with a

LAND POVERTY AND GROWTH INDIA 423

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 36: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

stylized model of agricultural contracting and labor supply bytenants While many complicating features could be added to thetheory the general thrust of the trade-off captured here isrelevant29 It is well-known that in a variety of contexts rents areused to motivate tenants Thus land reforms that affect howagency problems are solved will typically generate both outputand distributional effects We would expect these rents to affectlabor supply and result in changes to agricultural wages

VIII CONCLUDING REMARKS

The main contribution of this paper is to test whether landreform legislation is associated with poverty reductions usingstate-level data from India The high incidence of poverty and thelarge volume of land reforms enacted to counter this problem inthe post-Independence period make this an issue of considerableinterest We show that there is robust evidence of a link betweenpoverty reduction and two kinds of land reform legislationmdashtenancy reform and abolition of intermediaries Another impor-tant nding is that land reform can benet the landless by raisingagricultural wages Although the effects on poverty are likely tohave been greater if large-scale redistribution of land had beenachieved our results are nonetheless interesting as they suggestthat partial second-best reforms which mainly affect productionrelations in agriculture can play a signicant role in reducingrural poverty

As well as being important to policy debates in India suchndings may help to diffuse the more general pessimism that canundermine redistributive effort in developing countries In arecent study World Bank 1997 much emphasis was placed onthe role of economic growth in explaining the decline of poverty inIndia While our results are consistent with this nding theyemphasize that redistributive effort has also played its partUsing the average number of land reforms implemented our rstcoefficient in Table III implies that a reduction of the all-Indiapoverty gap of 1 percent can be explained by land reform This isone-tenth of the actual reduction in poverty over the period of ourdata This remains true even after factoring in the possibility thatoutput per capita is reduced by some kinds of land reform (Table

29 Following Banerjee and Ghatak 1997 it would be possible to introduceinvestment into the model In general we would expect increased tenurial securityto increase investment

QUARTERLY JOURNAL OF ECONOMICS424

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 37: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

VIII) To put this in perspective we compared the effect of landreforms on poverty with the effect of changes in per capita incomeThis comparison suggests that implementing a land reform has asimilar effect on poverty reduction to a 10 percent increase in percapita income or around four to ve years growth at the all-Indiaaverage growth rate over this period30

Since the effects of redistributive intervention on poverty andgrowth are not known a priori a signicant literature has testedthese links using cross-country data Benabou 1996 reviews thisliterature and emphasizes the diverse ndings While adding toour general understanding the difficulties of nding reliablecross-country measures of redistribution is a signicant drawbackin this research agenda There seems little doubt therefore thatexploiting policy variation due to the federal structure of somedeveloping countries may be an important additional source ofevidence on policy incidence It will also help to get behind broadbrush policy categories such as education or health expendituresthat mask important policy variations Our study underlines thateven within a particular area of government intervention (ieland reform) the empirical effects may vary depending on theexact form that the intervention takes This is true moreovereven though our policy measures are themselves fairly broadFuture efforts to quantify the empirical relationship betweengrowth poverty and redistribution will doubtless benet evenmore from a detailed specication of how particular policy inter-ventions are structured and implemented across space and time

DATA APPENDIX

The data used in the paper come from a wide variety ofsources31 They come from the sixteen main states listed in TableI Haryana split from the state of Punjab in 1965 From this dateon we include separate observations for Punjab and Haryana

30 Thus we regressed poverty on per capita income (along with state effectsand year effects) and compared the coefficient on per capita income with thatobtained on land reform (It made essentially no difference whether we did this byincluding both land reform and per capita income in one regression or ranseparate regressions in one case including only land reform and in the other onlyincome per capita) Results are available from the authors on request

31 Our analysis has been aided by Ozler Datt and Ravallion 1996 whichcollects published data on poverty output wages prices indices and populationto construct a consistent panel data set on Indian states for the period 1958 to1992 We are grateful to Martin Ravallion for providing us with these data towhich we have added information on land reform public nance and politicalrepresentation

LAND POVERTY AND GROWTH INDIA 425

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 38: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

Land Reform

To construct the land reform variable used in the regressionswe begin by recording all land reform acts that were passed in agiven state and year By examining the content of each landreform we then classify each land reform act into four categories(1 5 tenancy reform 2 5 abolition of intermediaries 3 5 ceilingson landholdings 4 5 consolidation of landholdings) where a singleland reform can belong to several types (see Table II) For eachland reform type this gives us a variable that is 0 or 1 in givenstate s and year t We cumulate these variables over time to giveus four cumulative land reform variables that capture the stock ofland reforms passed to date in each of the four categories We alsoaggregate across all four land reform categories to give us anaggregate cumulative land reform variable that gives us a mea-sure of the total stock of land reforms passed in state s by year tAmendments to acts are treated as new pieces of legislation TheIndex to Central and State Enactments (Ministry of Law andJustice Government of India) was used to identify Acts pertainingto land reform in different states To examine the exact content ofthese acts we mainly used Haque and Sirohi 1986 and Zaidi1985 although a range of secondary sources were used todouble-check the correctness of the information provided by thesetwo books and to ll in and update the detail regarding speciclegislations The secondary sources included Appu 1996 Behu-ria 1997 Bonner 1987 Borgohain 1992 Kurien 1981Mearns 1998 Pani 1983 Singh and Misra 1964 and Yugand-har and Iyer 1993

Poverty Data

We use the poverty measures for the rural and urban areas ofIndiarsquos sixteen major states spanning 1957ndash1958 to 1991ndash1992put together by Ozler Datt and Ravallion 1996 These measuresare based on 22 rounds of the National Sample Survey (NSS)which span this period Not all 22 rounds of the survey can becovered for each of the 22 rounds for each of the 16 states32 TheNSS rounds are also not evenly spaced the average interval

32 For 11 states (Andra Pradesh Assam Bihar Karnataka Kerala MadhyaPradesh Orissa Rajasthan Tamil Nadu Uttar Pradesh and West Bengal) all 22rounds have been covered Because Haryana only appears as a separate state fromPunjab in 1965 we have adopted including separate series for these two statesfrom this date onward For Gujarat and Maharashtra twenty rounds are includedbeginning with the sixteenth round in 1958ndash1959 (before 1958ndash1959 separatedistributions are not available for these two states as they were merged under the

QUARTERLY JOURNAL OF ECONOMICS426

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 39: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

between the midpoints of the surveys ranges from 09 to 55 yearsSurveys were carried out in the following years 1958 1959 19601961 1962 1963 1965 1966 1967 1968 1969 1970 1971 19731974 1978 1983 1987 1988 1990 1991 and 1992 Because otherdata are typically available on a yearly basis weighted interpola-tion has been used to generate poverty measures for years wherethere was no NSS survey The poverty lines used are thoserecommended by the Planning Commission 1993 and are asfollows The rural poverty line is given by a per capita monthlyexpenditure of Rs 49 at October 1973ndashJune 1974 all-India ruralprices The urban poverty line is given by a per capita monthlyexpenditure of Rs 57 at October 1973ndashJune 1974 all-India urbanprices See Datt 1995 for more details on the rural and urbancost of living indices and on the estimation of the povertymeasures The headcount index and poverty gap measures areestimated from the grouped distributions of per capita expendi-ture published by the NSS33 using parameterized Lorenz curvesusing a methodology detailed in Datt and Ravallion 1992

Agricultural Wages

The primary source for the data is Agricultural Wages inIndia (Ministry of Agriculture Government of India) Nominalwage data from this series have been deated using the ConsumerPrice Index for Agricultural Laborers to obtain real agriculturalwages No agricultural wage data are available for the state ofJammu and Kashmir and no separate wage data are available forthe state of Haryana

Income Data

The primary source for data on state income is an annualgovernment publication Estimates of State Domestic Product(Department of Statistics Department of Statistics Ministry ofPlanning) The primary source for the Consumer Price Index forAgricultural Laborers (CPIAL) and Consumer Price Index forIndustrial Workers (CPIIW) which are used to deate agriculturaland nonagricultural state domestic product respectively is anumber of Government of India publications which include In-

state of Bombay) For Jammu and Kashmir only eighteen rounds can be includedbeginning with the sixteenth round for 1960ndash1961 due to a lack of data

33 Reports from the National Sample Survey Organisation Department ofStatistics Ministry of Planning Government of India and Sarvekshena Journal ofthe National Sample Survey Organisation Department of Statistics Ministry ofPlanning Government of India

LAND POVERTY AND GROWTH INDIA 427

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 40: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

dian Labour Handbook the Indian Labour Journal the IndianLabour Gazette and the Reserve Bank of India Report on Currencyand Finance Ozler Datt and Ravallion 1996 have furthercorrected CPIAL and CPIIW to take account of interstate cost-of-living differentials and have also adjusted CPIAL to take accountof rising rewood prices Using their data allows us to puttogether a consistent and complete series on real total agricul-tural and nonagricultural state income for the period 1960 to1992 Our measure of agricultural yield is obtained by dividingreal agricultural state domestic product by net sown area for allcrops which is obtained from a government publication Area andProduction of Principal Crops in India (Directorate of Economicsand Statistics Ministry of Agriculture)

Public Finance Data

The primary source for state level information on taxes andexpenditures is an annual publication Public Finance Statistics(Ministry of Finance Government of India) This information isalso collated in the Reserve Bank of Indiarsquos annual publicationReport on Currency and Finance

Population Data

The population estimates are constructed using Census datafrom the ve censuses for 1951 1961 1971 1981 and 1991(Census of India Registrar General and Census CommissionerGovernment of India) Between any two successive censuses thestate-sectoral populations are assumed to grow at a constant(compound) rate of growth derived from the respective populationtotals

Political Variables

Political variables are the main instruments used in thepaper Data on the number of seats won by different nationalparties at each of the state elections are from Butler Lahiri andRoy 1991 These primary data are aggregated into four politicalgroupings which are dened in the text and expressed as shares ofthe total number of seats in state legislatures State politicalcongurations are held constant between elections

DEPARTMENT OF ECONOMICSLONDON SCHOOL OF ECONOMICS

QUARTERLY JOURNAL OF ECONOMICS428

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 41: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

REFERENCES

Alesina Alberto and Dani Rodrik lsquolsquoDistributive Politics and Economic GrowthrsquorsquoQuarterly Journal of Economics CIX (1994) 465ndash490

Appu P S Land Reforms in India A Survey of Policy Legislation and Implemen-tation (New Delhi Vikas 1996)

Bandyopadhyay D lsquolsquoLand Reforms in India An Analysisrsquorsquo Economic and PoliticalWeekly June 21ndash28 1986

Banerjee Abhijit and Maitreesh Ghatak lsquolsquoEmpowerment and Efficiency TheEconomics of Tenancy Reformrsquorsquo mimeo Massachusetts Institute of Technol-ogy and University of Chicago 1996

Banerjee Abhijit and Andrew Newman lsquolsquoOccupational Choice and the Process ofDevelopmentrsquorsquo Journal of Political Economy CI (1993) 659ndash684

Bardhan Pranab lsquolsquoIndiarsquorsquo in Chenery et al eds Redistribution with Growth(Oxford Oxford University Press 1970)

Barro Robert Determinants of Economic Growth A Cross-Country EmpiricalStudy (Cambridge MIT Press 1997)

Behuria N C Land Reforms Legislation in India A Comparative Study (NewDelhi Vikas 1997)

Benabou Roland lsquolsquoInequality and Growthrsquorsquo NBER Macroeconomics Annual(Cambridge MIT Press 1996)

Binswanger Hans Klaus Deininger and Gershon Feder lsquolsquoPower DistortionsRevolt and Reform inAgricultural Land Relations in Jere Behrman and T NSrinivasan eds Handbook of Development Economics (Amsterdam Elsevier1995)

Bonner Jeffrey P Land Consolidation and Economic Development in IndiamdashAStudy of Two Hariana Villages (Riverdale The Riverdale Company 1987)

Borgohain Rooplekha Politics of Land Reforms in Assam (New Delhi ReliancePublishing House 1992)

Butler David Ashok Lahiri and Prannoy Roy India Decides Elections 1952ndash1991(New Delhi Aroom Purie for Living Media India 1991)

Chattopadhyay S N lsquolsquoHistorical Context of Political Change in West Bengal AStudy of Seven Villages in Bardhaman Economic and Political Weekly March28 1992

Chenery Hollis Montek Ahluwalia Clive Bell John Duloy and Richard JollyRedistribution with Growth (Oxford Oxford University Press 1970)

Datt Gaurav lsquolsquoPoverty in India 1951ndash1992 Trends and Decompositionsrsquorsquo PolicyResearch Department World Bank 1995

Datt Gaurav and Martin Ravallion lsquolsquoGrowth and Redistribution Components ofChanges in Poverty Measures A Decomposition with Applications to Braziland India in the 1980srsquorsquo Journal of Development Economics XXXVIII (1992)275ndash295

Datt Gaurav and Martin Ravallion lsquolsquoWhy Have Some Indian States Done Betterthan Others at Reducing Povertyrsquorsquo Economica LXV (1998) 17ndash38

Dreze Jean andAmartya Sen India Economic Development and Social Opportu-nity (Oxford Clarendon Press 1995)

Dreze Jean Peter Lanjouw and Naresh Sharma lsquolsquoEconomic Development 1957ndash1993rsquorsquo in Peter Lanjouw and Nicholas Stern Economic Development inPalanpur over Five Decades (Oxford Oxford University Press 1998)

Gough Kathleen Rural Change in Southeast India 1950s to 1980s (Delhi OxfordUniversity Press 1989)

Haque Tajamul and Amar Singh Sirohi Agrarian Reforms and InstitutionalChanges in India (New Delhi Concept Publishing Company 1986)

Hoff Karla and Andrew B Lyon lsquolsquoNon-Leaky Buckets Optimal RedistributiveTaxation and Agency Costsrsquorsquo Journal of Public Economics LIII (1995)365ndash390

Jayaraman Raji and Peter Lanjouw lsquolsquoLiving Standards in Rural India APerspective from Longitudinal Village Studiesrsquorsquo mimeo Cornell Universityand World Bank 1997

Kurien Christopher Thomas Dynamics of Rural TransformationmdashA Study ofTamil Nadu 1950ndash1975 (Madras Orient Longman 1981)

Mearns Robin lsquolsquoAccess to Land in Rural India Policy Issues and Optionsrsquorsquo mimeoWorld Bank 1998

LAND POVERTY AND GROWTH INDIA 429

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430

Page 42: LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE … · LAND REFORM, POVERTY REDUCTION, AND GROWTH: EVIDENCE FROM INDIA* TIMOTHYBESLEYANDROBINBURGESS In recent times there has

Moene Karl Ove lsquolsquoPoverty and Land Ownershiprsquorsquo American Economic ReviewLXXXII (1992) 52ndash64

Ozler Berk Gaurav Datt and Martin Ravallion lsquolsquoA Data Base on Poverty andGrowth in Indiarsquorsquo mimeo World Bank 1996

Pani Narendar Reforms to Pre-empt ChangemdashLand Legislation in Karnataka(New Delhi Concept Publishing Company 1983)

Perotti Roberto lsquolsquoIncome Distribution Democracy and Growth What Does theData Sayrsquorsquo Journal of Economic Growth I (1996) 149ndash187

Persson Torsten and Guido Tabellini lsquoIs Inequality Harmful for Growth Theoryand Evidencersquorsquo American Economic Review LXXXIV (1994) 600ndash621

Planning Commission Report on the Expert Group on the Estimation of theProportion and Number of Poor (New Delhi Government of India 1993)

Radhakrishnan P lsquolsquoLand Reforms Rhetoric and Realityrsquorsquo Economic and PoliticalWeekly November 24 1990

Rodrik Dani lsquolsquoGetting Interventions Right How South Korea and Taiwan GrewRichrsquorsquo Economic Policy XX (1995) 53ndash97

Sargan John Denis lsquolsquoThe Estimation of Economic RelationshipsUsing Instrumen-tal Variablesrsquorsquo Econometrica XXVI (1958) 393ndash415

Sharma H R lsquolsquoDistribution of Landholdings in Rural India 1953ndash54 to 1981ndash1982 Implications for Land Reformsrsquorsquo Economic and Political Weekly Septem-ber 24 1994

Singh Baljit and Shridhar Misra A Study of Land Reforms in Uttar Pradesh(Honolulu East-West Center Press 1964)

Thorner Daniel Agrarian Prospect in India (New Delhi Allied Publishers 1976)Wadley S S and B W Derr lsquolsquoKarimpur 1925ndash1984 Understanding Rural India

through Restudiesrsquorsquo in Pranab Bardhan ed Conversations between Econo-mists and Anthropologists (Delhi Oxford University Press 1990)

Warriner Doreen Land Reform in Principle and Practice (Oxford Oxford Univer-sity Press 1969)

World Bank lsquolsquoPoverty in India 50 Years after Independencersquorsquo World Bank mimeo1997

Yugandhar B N and K Gopal Iyer Land Reforms in India BiharmdashInstitutionalConstraints (London Sage Publications 1993)

Zaidi A Moin Not by a Class WarmdashA Study of Congress Policy on Land Reformsduring the Last 100 Years (New Delhi Document Press 1985)

QUARTERLY JOURNAL OF ECONOMICS430