resource transfers to local governmentswebfac/bardhan/papers/wbpoleconoct2017… · i do voter...

Resource Transfers to Local Governments:Political Manipulation and Clientelism in West Bengal

Pranab Bardhan, Sandip Mitra, Dilip Mookherjee andAnusha Nath

UC Berkeley, Indian Statistical Institute, Boston University, Federal Reserve Bankof Minneapolis and University of Minnesota

Work-in-Progress; October 2017

Bardhan, Mitra, Mookherjee, Nath Political Manipulation and Clientelism

Background

I Existing literature on political economy of decentralizationhas largely focused on problems of political accountabilityof leaders of lower level local governments(intra-community elite capture)

I Insufficient attention toI Inter-community allocationsI Distortions related to clientelism, qualitatively distinct from

elite capture

I In this project we examine both of these dimensions, andargue they need to be viewed jointly


Questions

1 Do upper level governments manipulate flows ofdevelopment projects to lower level governments on thebasis of political (vote-generating) motives?

2 How do voters respond to delivery of benefits? Is thereevidence of clientelism:

I private versus local public goods?

I short-term, recurring benefits versus long-term, one-timebenefits?

I do voter expectations regarding electoral prospects ofincumbents matter?

3 Do these lower level voting patterns match/rationalize theupper level fund flow patterns?


1. Inter-Community Allocations

I Existing literature has largely ignored problem ofaccountability of elected officials in upper levelgovernments that control flow of funds down to localgovernments

I Significance of inter-community vis-a-vis intra-communityallocations indicated in earlier work on West Bengal(Bardhan-Mookherjee 2006):

I very limited evidence of significant effects of landless, landinequality or proportion of low castes on within-villagetargeting

I significant effects on inter-village allocations (e.g., 2.5% risein landlessness associated with 18% decline in programgrants from above)


1. Inter-Community Allocations, contd.

I Reasons for this are not well-understood: politicaldiscretion/incentives of upper level goverment officials?

I If so, it would suggest the need to institute formula-boundvertical fiscal transfers and/or measures to reduce scopefor discretion by political intermediaries


2. Testing for Clientelism

I Typically hard to separate clientelism from pork-barrel andcitizen-candidate models.

I Distinctive predictions of clientelism models:

1. Recurring, private benefit programs are more effective ingenerating votes

2. Voters’ expectation of who is going to come to powermatters for voting behavior.

I We test these empirically, while addressing supply-sideendogeneity concerns


Empirical Strategy

I First step: examine variations in allocations for differentprograms (generated by electoral redistricting shock atupper levels) to local governments

I Second step: use these to instrument variation in benefitflows at local level, to examine impacts on voting patterns

I Check consistency between results: is there largerupper-level manipulation of programs whose delivery ismore effective in mobilizing votes?


1. Context: West Bengal, India

I There are 18 districts in WB

I Each district covers (approx.) 2 parliamentaryconstituencies, 15 state assembly constituencies and 2000villages

I Local government hierarchy: program funds filter downfrom a district governments (ZP) through 20 PSs(intermediate layer) to 200 GPs

I Benefit programs targeted for the poor:

I roads, drinking water, employment in public works(NREGA), housing and toilets, credit, seeds/fertilizers, BPLcards, pensions


Government Hierarchy


Political Competition

I Two main contesting parties in West Bengal since 2000:Left Front coalition (LF), Trinamool Congress (TMC)

I LF held an absolute majority in state legislature and inZP/GP elections since 1977

I Has been losing vote share to TMC since the latter wasformed in the late 90s: intense competition since then

I LF lost control of state assembly and most ZP/GPs in 2011


Redistricting

I Electoral constituencies redrawn every 3 decades

I Based on population size changes shown by Census

I Last one since 2001 Census, completed 2007

I Every state has a state Redistricting Commission (RC):

I Appointed by National Election Commission

I Has 3 (non-political) members: retired Chief Justice, NECmember, state election commissioner

I Advisory committee consisting of 5 MPs and 5 MLAs


2. Data: Sample

I Random sample from89 villages in 59 GPs

- Covers 15 maindistricts of rural WB

I Household Panel: Tworounds of surveys(2004, 2011)

- 2402 households

- Attrition rate < 1%


GP Disbursed Benefits

I In each round of survey, the head of household (HoH)reports benefits received from GP in past 7 years

I One-time benefits: one-shot interactions

I Ration Card, House, Toilet, Drinking Water, Irrigation, RoadAccess.

I Note: local public goods are onetime benefits.

I Recurring benefits: repeated interactions

I public works employment (MNREGA, MPLAD), low interestloans, agri-minikits (subsidized seeds, fertilizers)


Summary Statistics: Benefits Received by Households

(1993 - 2003) (2004-2011)% HoH Reporting % HoH Reporting

Any Benefit 61.5 62.5Recurring Benefits

Any Recurring 9.19 46.81Credit 4.7 2.1Minikit 5.4 10.5MNREGA NA 33.9MPLAD n.a. 0.2

One-time BenefitsAny Onetime 44.46 44.97BPL Cards 17.7 18.1House or Toilet 4.6 10.2Drinking Water 7.6 12.5Road 27.1 24.8

[1] MNREGA scheme began in 2004, hence Not Applicable (NA) prior to 2003.

[3] n.a. means “Not Available”. Questions regarding these schemes were not asked

in the 2004 survey.


Straw Poll

I A straw poll was conducted at the end of each survey

I Each HoH cast ballot containing symbols of major politicalparties in the local area

I The response rate was 93%


Election Results and Poll Responses

Panel [a] Results from Poll Responses

Party Poll Shares (%) 2004 2011

TMC/INC 30 57Left Front 58 34

Panel [b] Official Election Results*

Party Vote Shares (%) 2006 2011

TMC/INC 40 47Left Front 50 42

* The official election results are reported only for constituencies in which survey was conducted.


Theory: Model of Upper-Level AllocationI Model budgetary allocations across a 3-layer hierarchy:

District (ZP) to different MLA constituencies Ci to villages vto households

I Each level has a government controlled by either L or Tparty

I Within given village v: competing parties in GP electionsallocate HH benefits to maximize vote shares (given votingbehavior, to be described later), resulting in:

σv =12

+ θi + Iv∑

k

νkbkv

σv : L vote share in v ∈ Ci ; νk : vote-generatingeffectiveness of benefit k ; θi : a constituency-specificpopularity shock; bkv : per capita benefit k alloted to v ;Iv = 1(−1) if L(T) is incumbent


Modeling Allocation of Resources, contd.

I Incumbent MLA in Ci allocates its assigned budget(received from ZP) across village governments tomaximize chance of re-election, less a disutilityproportional to variance of allocations (dealing withprotests, fairness concerns)

I Taking as given how incumbent village governments intheir constituency will subsequently behave

I MLA re-election probability p increasing function ofaggregate vote share of the party across villages in theconstituency, strictly concave (convex) above (below) 1

2

I Incumbent at ZP level allocates budget across MLAconstituencies in the district to maximize number of MLAseats the party will be able to secure.


Testable Predictions for Upper-Level Allocation

1. If political control is perfectly aligned acrossdifferent levels e.g. L controls ZP, C1,C2, where Lis in a weaker competitive position in C2,redistricting of L-controlled v from C1 to C2 willcause v ’s allocation to increase

2. With a different political alignment involvingconflicting control at different layers, the change inallocation will be smaller

3. Direction of change should be the same for allbenefit programs; with larger increases for thoseprograms that are more effective in generatingvotes (higher νk )


Intuition for Upper-Level Allocation Result

I Deviation of budget for any village from district average isthe sum of two components: inter-constituency bias plusinter-village intra-constituency bias

I Given concavity of re-election probability in vote shares,increasing vote share in weaker constituencies havegreater priority

I With alignment of control across ZP and C1,C2, theweaker constituency C2 gets a larger budget:inter-constituency bias is positive

I MLA controlling C2 discriminates more in favor of villagescontrolled by the same party: so v also benefits from alarger intra-constituency bias (lack of alignment will reversethis)


Intra-Village Benefit Distribution

I Benefit program types k = 1, ...,K partitioned intorecurring (R), one-time (O) and public (P) subsets, eachbenefit is indivisible (0− 1) at the household level

I Group g = 1, ...,G of citizens, demographic weights µg ,receives marginal utility bkg from type k benefit


Parties and Elections

I Party policies at GP/village level v :I Select πkg proportion of group g citizens that receive benefit

kI subject to constraints πkg = πk for k ∈ P,

∑g µgπkg = bkv

I bkv per capita benefit bk of program k allocated to village vby upper level government

I Two competing parties P,T engage in Downsiancompetition to maximize chance of winning the nextelection

I For arbitrary election at date t , focus on benefits allocatedby incumbent elected at t − 1 between t − 1 and t


Retrospective (Probabilistic) Voting

I Voters receiving a recurring or public benefit between t − 1and t from the incumbent expects to receive the samebenefit between t and t + 1 if the incumbent is re-elected att (and other conditionalities specified by the incumbent aremet)

I A voter receiving a one-time private benefit between t − 1and t cannot receive it ever again

I If the challenger wins at t , voters expect benefits promisedby this party in its electoral platform (assumed to becredible)

I Probabilistic voting: voters vote partly on basis of expectedbenefits, and partly on non-policy-related (identity, loyalty,image) grounds that are uniformly distributed with loyaltybias lg and swing density sg within group g


Program (Pork-Barrel) Politics

I Benefit distribution policy of party p is unconditional (giveng, k ), wrt voting behavior of citizen

I Vote shares at the village (at t) depend on recurring andpublic good allocations (between t − 1 and t) actual orpromised:

σL =12

+∑

g

µg lg +∑

g

µgsg∑

k∈R∪Pβkg[πL

kg − πTkg]


Program (Pork-Barrel) Politics, contd.

I One-time benefits distributed between t − 1 and t do notaffect votes at t (except via ‘gratitude’)

I Delivery of one-time benefits will affect (strategic) votesonly at earlier dates

I As in standard (eg Dixit-Londregan (1994, 1995, 1996))models, obtain policy convergence: both parties selectallocation of recurring and public goods (between t − 1 andt) to maximize

∑g µgsgβkgπkg subject to resource

constraints


Clientelistic Politics

I Benefit distribution is conditional (given g, k ) on the citizenhaving voted for the winner

I Group g citizen with bias ε in favor of L party will vote for Lif (with pL denoting voter expectation that L will win at t):

εL+ pL∑

k∈R∪Pβkgπ

Lkg + (1− pL)

∑k∈P

βkgπTk > pL

∑k∈P

βkgπLk

+(1− pL)∑

k∈R∪Pβkgπ

Tk


Clientelistic Politics, contd.

I Condition for voting for L:

εL + pL∑k∈R

βkgπLkg > (1− pL)

∑k∈R

βkgπTk

I Public goods do not matter at all; only recurring benefitsmatter!

I Voter expectations pL also matter: higher pL raises (lowers)effectiveness of benefits distributed by L (T ) in generatingvotes (‘contagion’ effect, which can lead to policynon-convergence and hysteresis (Sarkar (2014),Bardhan-Mookherjee (2016))


Testable Predictions of Clientelism

Under Clientelism:

1. Only recurring benefits (distributed prior to the election)affect vote shares, public goods do not matter.

2. An increase in party j ′s perceived probability of winningincreases the effectiveness of recurring benefits distributedon likelihood of voting for the incumbent.

3. Upper level governments will manipulate allocations ofrecurring private benefit programs to lower levelgovernments to a far greater extent than either one-time orpublic good programs.


4. Natural Experiment: Changes in Electoral BoundaryI Assembly constituency boundaries changed in 2009

I Announcement came at the end of 2007

I 24 villages in our survey became part of a new jurisdiction


Defining Treatment GroupI Let C1 and C2 be the old and new assembly boundaries.

I Village vi belongs to assembly treatment group "LeftWeaker" if:

a. Left was in power in both C1 and C2 in 2006 and the victorymargin for Left was lower in C2 compared to C1.

b. Left was in power in C1 but not in C2 in 2006.


Defining Alignment

Define alignment based on parties that dominatesPanchayat Samiti (PS) and Gram Panchayat (GP) Seats

I Two-tier alignment: both Panchayat Samiti and GP are Leftdominated

I Three-tier alignment: Zila Parishad, Panchayat Samiti andGP are Left dominated


Our Sample: Government Hierarchy and Redistricting

I Left majority at Panchayat Samiti - 45

I 73 villages: 62 in aligned GPs, 11 in non-aligned

I 11 villages redistricted to Left weaker constituency

I 6 villages redistricted to Left stronger constituency

I TMC/INC majority at Panchayat Samiti - 9

I 16 villages: 10 in aligned GPs, 6 in non-aligned

I 3 villages redistricted to TMC weaker constituency

I 4 villages redistricted to TMC stronger constituency

Flowchart


Gerrymandering?

I Boundary changes were unlikely to be politicallymanipulated: carried out by Delimitation Commissionconsisting of a SC judge, CEC and SEC, on basis ofpopulation changes between 2001 and 1971 Census, in apublic, transparent process

I Iyer and Reddy (2013)

I Data from two states: Andhra Pradesh and Rajasthan

I Show that “for most part the redistricting was politicallyneutral”

I Census village data:

I No systematic differences in village characteristics acrosstreated and control groups


Predicting Redistricting

(1) (2)Redistricted Left Weaker*

Left AlignedLeft GP* Left PS 0.52

(0.31)Left Dominated GP 2008 -0.36

(0.22)Left PS -0.22

(0.19)Delimitation Commission Member 0.17 0.16

(0.12) (0.13)Observations 89 89Adjusted R2 0.113 0.081Mean Dependent Variable 0.09 0.07* p<0.10, ** p<0.05, *** p<0.01 Robust standard errors in parentheses, clustered at district level.

[1] Dependent Variable is indicated at the top of each column.

[2] Left Weaker is a dummy that includes two cases: [a] village was in TMC constituency and moved to

a less competitive TMC constituency [b] village was in Left constituency and moved to a more

competitive Left constituency.

[3] Left Aligned is a dummy that takes value 1 if Left is in power at the GP as well as Panchayat Samiti.

[4] Delimitation Commission (DC) Member is a dummy variable taking value 1 if MLA/MP was member of DC.


First Stage Analysis: Effects of Redistricting onInter-Village Benefit Allocations, Parliamentary Level

Bvt = α0 + α1Post ∗ LeftWeakerv ∗ LeftAlignedv

+ α2Post ∗ LeftWeakerv

+ α3Post ∗ LeftAlignedv + α4LeftAlignedv ∗ LeftWeakerv

+ α5Post + α6LeftAlignedv + α7LeftWeakerv + Fv + τt + εvt

where:Post=1 for years 2008-2011, 0 for earlier yearsLeftWeakerv = 1 if v was redistricted into a LFconstituency where LF had a lower vote share in 2003


Comparing Pre-trends: Per Capita Recurring Benefits

0.0

5.1

.15

Annu

al P

er H

H R

ec. B

enefi

ts

1995 2000 2005 2010

Year

Non-redistricted Villages Left WeakerLfit Non-redistricted Villages Lfit Left Weaker

Recurring Benefits


Comparing Pre-trends: Per Capita Onetime Benefits

0.1

.2.3

.4

Annu

al P

er H

H O

netim

e Be

nefit

s

1995 2000 2005 2010

Year

Non-redistricted Villages Left WeakerLfit Non-redistricted Villages Lfit Left Weaker

Onetime Benefits


Effect of Treatment on Per Capita Recurring Private Benefits (1994-2011)

Dependent variable: standardized annual per HH recurring benefits for each village.(1) (2) (3)

Post* Treated 0.03 -1.14 -1.14(0.38) (1.04) (1.04)

Post* Treated* Left Aligned Two-tier 3.04**(1.16)

Post* Treated* Left Aligned Three-tier 3.01**(1.17)

Observations 1775 1775 1775Adjusted R2 0.174 0.186 0.186Mean Annual Per HH Benefits 0.76 0.76 0.76SD Annual Per HH Benefits 1.87 1.87 1.87* p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses, clustered at GP level.

[1] Observations at the village-year level, 2003-2011.

[2] Treated refers to those cases where GP was redistricted to an assembly constituency where

Left party has a lower likelihood of winning based on victory margins.

[3] Recurring benefits include: MPLAD, MNREGA, IRDP, Minikits.

[4] Post takes value 1 for years 2007 and onwards.

[5] Left aligned two-tier refers to Left Panchayat Samiti and Left GP.

[6] Left aligned three-tier refers to Left ZP, Left Panchayat Samiti and Left GP.


Effect of Treatment on Public and Onetime Benefits (1994-2011)

Dependent variable: standardized annual per HH onetime benefits for each village.(1) (2) (3)

Post* Treated 0.13 0.47 0.46(0.31) (0.78) (0.78)

Post* Treated* Left Aligned Two-tier 0.84(1.07)

Post* Treated* Left Aligned Three-tier 0.84(1.07)

Observations 1775 1775 1775Adjusted R2 0.349 0.357 0.357Mean Annual Per HH Benefits 0.52 0.52 0.52SD Annual Per HH Benefits 1.67 1.67 1.67* p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses, clustered at GP level.


[2] Treated refers to those cases where GP was redistricted to an assembly constituency where

Left party has a lower likelihood of winning based on victory margins.

[3] One-time benefits include: Ration Card, House, Toilet, Drinking Water, Irrigation, Road Access.


[5] Left aligned two-tier refers to Left Panchayat Samiti and Left GP.

[6] Left aligned three-tier refers to Left ZP, Left Panchayat Samiti and Left GP.


Recurring Benefits (per capita)

0.0

5.1

.15

.2

Annu

al P

er H

H R

ec. B

enefi

ts

2002 2004 2006 2008 2010 2012

Year

Left Weaker Left Weaker*Left AlignedLfit Left Weaker Lfit Left Weaker*Left Aligned

Recurring Benefits


Public and Onetime Benefits (per capita)

0.1

.2.3

.4

Annu

al P

er H

H O

netim

e Be

nefit

s

2002 2004 2006 2008 2010 2012

Year

Left Weaker Left Weaker*Left AlignedLfit Left Weaker Lfit Left Weaker*Left Aligned

Onetime Benefits


Robustness - Effect of Treatment on Benefits Distributed

Recurring Without MNREGA Onetime Without Roads(1) (2) (3) (4) (5) (6)

Post* Treated -0.29 -1.03 -1.13* 1.08 2.15 2.11(0.40) (0.68) (0.67) (0.72) (2.15) (2.15)

Post* Treated* Left Aligned Two-tier 1.62* 1.24(0.92) (2.76)

Post* Treated* Left Aligned Three-tier 1.79* 1.29(0.91) (2.75)

Observations 1775 1775 1775 1775 1775 1775Adjusted R2 0.145 0.154 0.149 0.276 0.292 0.291Mean Annual Per HH Benefits 0.43 0.43 0.43 0.88 0.88 0.88SD Annual Per HH Benefits 2.16 2.16 2.16 2.40 2.40 2.40

* p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses, clustered at GP level.[1] Observations at the village-year level, 2003-2011.[2] The dependent variable is standardized measure of annual per HH benefits for each village.[3] Treated refers to those cases where GP was redistricted to an assembly constituency whereLeft party has a lower likelihood of winning based on victory margins.[4] Recurring benefits include: MPLAD, IRDP, Minikits.[5] One-time benefits include: Ration Card, House, Toilet, Drinking Water, Irrigation.


Placebo Test - Diff-in-diff (2003-2006)

Recurring Onetime(1) (2)

Post* Treated -0.15 0.15(2.28) (0.69)

Post* Treated* Left Aligned Two-tier -0.83 -1.16(2.40) (0.85)

Observations 764 764Adjusted R2 0.304 0.484Mean Annual Per HH Benefits 0.77 0.75SD Annual Per HH Benefits 1.89 1.56* p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses, clustered at GP level.


[2] The dependent variable is standardized measure of annual per HH benefits for each village.

[3] All specifications include other interactions; whether MLA/MP was part of delimitation committee;

village and year fixed effects.



5. Empirical Results: Impacts of Benefits on Votes

I Examine impacts of the variation in benefit flows owing tothe redistricting treatment

I (LeftWeaker ∗ LeftAligned) on LF support in the 2011 polls

I Challenge: exclusion restriction

I The treatment may affect LF support in ways other thanbenefits distributed

example: additional mobilization efforts by party cadres thatwe cannot observe

I Solution:

I Focus on within-village variation across households inbenefit flows


Impacts of Benefits on Votes, contd.

I Identification assumption

I Unobserved impacts of treatment on LF supportuncorrelated with targeting of benefits

I Household fixed effects: examine change in poll responsesfor household head between two rounds

I Controls for compositional changes in distribution ofbenefits in treated villages, in favor of LF-supporters

I One-time benefits distributed between t − 1 and t couldraise votes at t − 1, while having negligible effects on votesat t , so effect on the change would still be smaller than forrecurring benefit changes


Specification

First-Stage:

∆b̄ivkt = τ1kTvt ∗∆Svt + τ2kTvt + τ3k ∆Svt ∗ HCi

+τ4k ∆Svt + τ6k + ηiv (1)

where Tvt : treatment ; Svt : district per capita benefit (recurringplus one-time) year t ; HCi : household characteristics (caste,land, education dummies)

Second Stage:

∆Livt =∑

k

νk ∆b̄ivkt + ρ1Tvt + εivt


Effect of Change in Benefits on Change in Poll Responses between 2004, 2011 (Left GPs)

Dependent variable: change in poll responses between 2003, 2011OLS OLS IV IV(1) (2) (3) (4)

Change in Recurring Benefits 0.025*** 0.027**(0.006) (0.011)

Change in Onetime Benefits 0.020** 0.015(0.009) (0.014)

Change in Total Benefits 0.023*** 0.020***(0.006) (0.005)

Observations 1173 1173 1173 1173Adjusted R2 0.079 0.079 0.070 0.071* p<0.10, ** p<0.05, *** p<0.01 Robust standard errors in parentheses.

[1] Change in Vote for Left takes value 0 if HH voted for left in 2011 and 2003 straw polls respectively,

1 if voted left in 2011 but TMC in 2003, and -1 if voted left in 2003 and TMC in 2011.

[2] Change in Recurring Benefits is change in 3 year average recurring benefits between 2003 and 2011.

[3] Change in Onetime Benefits is change in 3 year average onetime benefits between 2003 and 2011.

[4] Change in Total Benefits is change in sum of onetime and recurring benefits between 2003 and 2011.

Details


Role of Expectations

I The above results are consistent with predictions of theclientelism model: only recurring benefits affect voteshares, local public goods do not matter.

I The second prediction of the model is: they will be moreeffective in villages where voters expect party j to win withhigher probability

I To test this, we use results from the elections that tookplace between the two survey rounds.

I Gamma High takes value 1 if victory margin at theassembly constituency level in 2009 Lok Sabha elections ismore than the median of treated constituencies.


Role of Expectations - Treatment at Assembly Level

Dependent variable: change in poll responses between 2003, 2011OLS IV(1) (2)

Change in Benefits* Gamma High 0.038*** 0.049**(0.005) (0.021)

Change in Total Benefits 0.018*** 0.015***(0.004) (0.003)

Observations 1173 1173Adjusted R2 0.097 0.087* p<0.10, ** p<0.05, *** p<0.01 Robust standard errors in parentheses.

[1] Change in Vote for Left takes value 0 if HH voted for left in 2011 and 2003 straw polls respectively,

1 if voted left in 2011 but TMC in 2003, and -1 if voted left in 2003 and TMC in 2011.

[2] Change in Total Benefits is change in sum of onetime and recurring benefits between 2003 and 2011.

[3] Gamma High takes value 1 if victory margin at the assembly constituency level in 2009 Lok Sabha

elections is more than the median of treated constituencies.

[4] HH Characteristics and Treatment Dummy included in all specifications.

[5] In columns (3) and (4), excluded instruments are Treatment*Agg Benefits*HH characteristics,

Agg Benefits*HH characteristics, and included instruments are Treatment Dummy and HH characteristics.

Details


6. Summary and Broader Implications

I We find evidence in favor of clientelism at local level,implying (a) political biases in favor of recurring privatebenefit programs; (b) ‘contagious’ voting (Sarkar (2014)),lop-sided political competition and hysteresis(Bardhan-Mookherjee 2016)

I Evidence of corresponding manipulations of fund transfersby upper-level governments

I Both suggest possible value of direct formula-boundtransfers to local governments (for local public goodprograms) and citizens (for welfare benefits), but thisneeds to be explored further


Effect of Change in Benefits on Change in Votes for LeftFirst Stage First Stage Reduced Form IV

Ch. Recurring Ch. Onetime Ch Vote Ch. VoteBenefits Benefits for Left for Left

(1) (2) (3) (4)TREAT * Ch. Benefits * Maxedu -0.00 0.00 0.00

(0.00) (0.00) (0.00)TREAT * Ch. Benefits * Woman Head 0.00 0.00 -0.00

(0.01) (0.00) (0.00)TREAT * Ch. Benefits * Cultivator -0.00 0.00 0.00

(0.01) (0.00) (0.00)TREAT * Ch. Benefits * Landless -0.02*** -0.00 0.00

(0.01) (0.00) (0.00)TREAT * Ch. Benefits * SC/ST -0.02* -0.01 -0.00

(0.01) (0.01) (0.00)TREAT * Ch. Benefits * Hindu -0.00 -0.01 -0.00

(0.01) (0.01) (0.00)TREAT * Ch. Benefits * Immigration -0.01 -0.00 0.00

(0.01) (0.00) (0.00)Treat 0.60 -0.14 -0.26** -0.30***

(0.97) (0.64) (0.12) (0.10)Ch. Recurring 0.03**

(0.01)Ch. Onetime 0.02

(0.01)Observations 1173 1173 1173 1173Adjusted R2 0.404 0.731 0.055 0.070F-test for excluded instruments (p-value) 17.59

(0.00)48.73(0.00)

Overidentification test: Hansen J statistic (p-value) 13.49(0.41)

LM test for full rank of matrix (p-value) 60.94(0.00)

BackBardhan, Mitra, Mookherjee, Nath Political Manipulation and Clientelism

Expectations and Change in Votes for Left

First Stage First Stage Reduced Form IVCh. Benefits Ch. Benefits Ch Vote Ch. Vote

*γhigh for Left for Left(1) (2) (3) (4)

Treat* Ch. Benefits * Max Educ.* Gamma High 0.000 -0.000 0.000(0.001) (0.000) (0.000)

Treat* Ch. Benefits * Woman HOH * Gamma High 0.001 0.006 -0.002(0.005) (0.007) (0.002)

Treat* Ch. Benefits * Occup * Gamma High 0.001 -0.000 0.001(0.004) (0.007) (0.002)

Treat* Ch. Benefits * Landless* Gamma High -0.004 -0.017** 0.000(0.008) (0.008) (0.001)

Treat* Ch. Benefits * SC/ST * Gamma High -0.008 -0.027*** -0.001(0.009) (0.010) (0.001)

Treat* Ch. Benefits * Hindu * Gamma High 0.008 -0.013 -0.001(0.013) (0.011) (0.002)

Treat* Ch. Benefits * Immig * Gamma High 0.005 -0.013*** 0.001(0.006) (0.005) (0.003)

Treat 1.015 0.472 -0.260** -0.304***(1.039) (1.082) (0.114) (0.065)

Change in Benefits* Gamma High 0.049**(0.021)

Change in Total Benefits 0.015***(0.003)

Observations 1173 1173 1173 1173Adjusted R2 0.219 0.804 0.056 0.087F-test for excluded instruments (p-value) 43.15

(0.000)261.76(0.000)

Overidentification test: Hansen J statistic (p-value) 10.893(0.619)

LM test for full rank of matrix (p-value) 116.71(0.000)

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