overcoming market and government failures in india and africa

Overcoming Market and Government Failures

in India and Africa

Shanta DevarajanWorld Bank

http://africacan.worldbank.org

GDP growth in South Asia has been strong and accelerating

Source: World Development Indicators

Rapid growth is reducing poverty, but inequality is increasing

Source: Narayan, Ambar, et. al. 2006. “The challenge of promoting equality and inclusion in South Asian countries.” mimeo, World Bank: Washington DC.

Big gaps between enrolment and completion in primary education

Source: Schweitzer, Julian. 2006. “Human development in South Asia.” mimeo, World Bank: Washington, DC.

Immunization rates are low and stagnant

Measles Immunization: 12-23 Months

505560657075808590

2000 2001 2002 2003 2004

Year

% Im

mun

ized Bolivia

ChinaIndiaIndonesiaKenya

Source: WDI Indicators Database

For the first time in 20 years, Africa’s growth is high and accelerating

Per capita income

-4

-2

0

2

4

6

8

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

Ann

ual c

hang

e in

real

GD

P pe

r ca

pita

(%)

Developing countries Developing countries, excluding China and India

Sub-Saharan Africa High-income countries

Africa’s progress on poverty and social outcomes is uneven

Number of countries that will achieve MDGs Number of population that will achieve MDGs

-800

-700

-600

-500

-400

-300

-200

-100

0

100

200

Malnutr

ition

Educat

ion Gende

r

Child m

ortali

tyBirth

s

Wate

r

Num

ber

of p

opul

atio

n, m

illio

n

-60

-50

-40

-30

-20

-10

0

10

20

Povert

y

Malnutr

ition

Educa

tion

Gende

r

Child m

ortali

ty

Births

Wate

r

Sanita

tion

Num

ber o

f cou

ntrie

s

-800

-700

-600

-500

-400

-300

-200

-100

0

100

200

Malnutr

ition

Educat

ion Gende

r

Child m

ortali

tyBirth

s

Wate

r

Num

ber

of p

opul

atio

n, m

illio

n

-60

-50

-40

-30

-20

-10

0

10

20

Povert

y

Malnutr

ition

Educa

tion

Gende

r

Child m

ortali

ty

Births

Wate

r

Sanita

tion

Num

ber o

f cou

ntrie

s

Achieved 1 On track 2 Off track 3 Seriously off track 4 No data 5 Source: Global Monitoring Report, 2007.

I. Water in India

24x7 water: A pipe dream?

Source: Data collected from the water boards or utilities

per capita lpd vs. hours of supply/dayGoa

ChandigarhMumbai

DelhiPatna

LudhianaJodhpur

DasuyaDera Bassi

ParisJaipur

AhmedabadBikaner

BangaloreGurdaspur

BathindaBharatpur

UdaipurChennai 32

80105

106108

123133

145149

173184

190220

222223

240332

341

1.5 2.5 1.5

8 10

2.5 1.5

2 3

8 10

2.5 10 10

4 5

10 8

24150

Service to the Poor is big business

Politics, patronage, & network servicesPOLITICIANS

EMPLOYEESUTILITY

COMPANY

CONNECTEDPOPULATION

Operational subsidiesAppointment of directors

Political favours

Artificiallydepressed

tariffs

Poorquality of

service

Over-staffing

UNCONNECTEDPOPULATION

High prices

CONTRACTORS

Untendered contracts

II. Transport in Africa

• Transport corridors

From Teravaninthorn and Raballand, Transport Prices and Costs in Africa: A Review of the Main International Corridors, Directions in Development Series, World Bank, 2008.

SELECTED CORRIDORS

OF THE STUDY

23.5 4

5 5 57

8

11

02468

101214

Paki

stan

Braz

il

USA

Chi

na

Wes

tern

Euro

pe –

long

dist

ance

Afric

a-D

urba

n-Lu

saka

Afric

a- L

omé

-O

uaga

doug

ou

Afric

a –

Mom

basa

Kam

pala

Afric

a-D

oual

a-N

djam

énaA

vera

ge tr

ansp

ort p

rices

(in

US

cen

ts p

er tk

m)

Central Africa East Africa West Africa Southern Africa France

Variable costs (USD per veh-km) 1.31 0.98 1.67 1.54 0.72

Fixed costs (USD per veh-km) 0.57 0.35 0.62 0.34 0.87

Total transport costs (USD per veh-km) 1.88 1.33 2.29 1.88 1.59

Transport costs are not excessively high in Africa comparing to France for example

However, average transport prices in Africa are high in a global comparison

Corridor Gateway - Destination Price(USD/ veh-km)

Variable cost

(USD/veh- km)

Fixed cost(USD/veh- km)

Average yearly

mileage (‘000)

Profit margin

(%)

West Africa

Tema/Accra - Ouagadougou 3.53 1.54 0.66 30-40 80%

Tema/Accra - Bamako 3.93 1.67 0.62 40-50 80%

Central Africa

Douala - N’Djaména 3.19 1.31 0.57 60-70 73%

Douala - Bangui 3.78 1.21 1.08 50-60 83%

Ngaoundéré - N’Djaména 5.37 1.83 0.73 20-30 118%

Ngaoundéré - Moundou 9.71 2.49 1.55 10-20 163%

East Africa

Mombasa - Kampala 2.22 0.98 0.35 130-140 86%

Mombasa - Nairobi 2.26 0.83 0.53 90-100 66%

Southern Africa

Lusaka - Johannesburg 2.32 1.54 0.34 160-170 18%

Lusaka - Dar-es-Salaam 2.55 1.34 0.44 160-170 62%

An interesting observation: On Central Africa corridor, trucks with lower average yearly mileage

have the higher profit margins

West Africa Central Africa East Africa Southern Africa

Market entry

Licenses Not restrictive Not restrictive Not restrictive Not restrictive

Market access

Bilateral agreement Yes Yes No Yes

Quotas/freight allocation Yes Yes No No

Queuing system Yes Yes No No

Third country rule Prohibited Prohibited Prohibited Allowed in some countries

Technical regulation (road

user charges, axle-load, vehicle

standard, import restriction)

Problem of harmonization of

axle-load regulation

Problem of enforcement of

axle-load regulation

Problem of harmonization of axle-load regulation, delays

at weighbridges

Prohibition of second-hand

vehicle imports in South Africa

Customs regulation

Cumbersome transit procedures inducing border-crossing delays

Cumbersome transit procedures

1. Prohibition for trailers in transit to pick-up backloads in Kenya2. Cumbersome transit procedures inducing border-crossing delays

Cumbersome transit procedures inducing

border-crossing delays

Source: Darbera (1998)

Average transport prices (constant and current) from Mombasa to Kigali

0

50

100

150

200

250

300

35019

89

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Years

US$

/Ton

0

100

200

300

400

500

600

700

800

900

US$/Ton

Current transport tariffs (left) Real transport tariffs - GDP deflator (right)

After liberalizationBefore liberalization

III. Agriculture in India

Agriculture value added per worker, 1990=100

90

100

110

120

130

140

150

160

170

1990 1992 1994 1996 1998 2000 2002 2004 2006Bangladesh China India

China

Bangladesh

India

0

1

2

3

4

5

6

7

1975-79 1980-84 1985-89 1990-94 1995-99 2000-02

Per

cent

of A

g. G

DP

Subsidies

Public Investment

Public expenditures in India

IV. Education in India and Uganda

Percent of Std. 2-5 children who cannot read or do sums

010203040506070

Public Private

Perc

ent Level 2 reading

Subtraction/Division

All India Teacher Absence Map (Public Schools)

StateTeacher

Absence (%)Maharashtra 14.6Gujarat 17.0Madhya Pradesh 17.6Kerala 21.2Himachal Pradesh 21.2Tamil Nadu 21.3Haryana 21.7Karnataka 21.7Orissa 23.4Rajasthan 23.7West Bengal 24.7Andhra Pradesh 25.3Uttar Pradesh 26.3Chhatisgarh 30.6Uttaranchal 32.8Assam 33.8Punjab 34.4Bihar 37.8Jharkhand 41.9Delhi -All India Weighted 24.8%Source: Kremer, Muralidharan, Chaudhury, Hammer, and Rogers. 2004. “Teacher Absence in India.”

Public School Teachers are paid a (lot) more

• Definitions• Unadjusted Wage

is the average wage of teachers in the public and private sector

• The adjusted wage is what a 25 year old female with a bachelors degree and a 2-year teacher training course residing locally would earn in the public and private sector

1231

1619

6178

5299

02,

000

4,00

06,

000

Sal

ary

in R

s.

Private PublicUnadjusted Adjusted Unadjusted Adjusted

Teacher Compensation

-400

-200

020

040

060

0D

evia

tion

from

Mea

n S

alar

y in

Rs

0 10 20 30Days Absent per Month

Private Schools Public Schools

Teacher Absenteeism and Compensation

The private sector pays more absent teachers

less

The public sector pays more absent teachers

more

Salary results are presented as“deviations from mean”. So the number

200 on the vertical axis means that the person’s salary is Rs.200 more than the average salary for the sector The figure is based on a non-parametric

plot of deviations from mean salary against the number of days absent.

No incentives to perform…

Primary Education in Uganda(PETS)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1990 1991 1993 1994 1995

US$ per Student

Intended Grant Amount Received by School (mean)

1999

Grants for Primary Education in Uganda

• In 1995, survey of 250 primary schools in 19 of 39 districts;

Absence rate among teachers

Country Rate (percent)Bangladesh 15Ecuador 14India 25Indonesia 19Papua New Guinea 15Peru 11Zambia 17Uganda 27

Uganda: What enumerators found

In class, teaching, 18.2%

Out of class, break, 17.6%

Out of class, in school, 34.2%

Can't find teacher, 19.2%

Administrative work, 8.1%

With surveyor, 0.2%

In class, not teacher, 2.4%

V. Health in India and Chad

Immunization rates are low and stagnant

Measles Immunization: 12-23 Months

505560657075808590

2000 2001 2002 2003 2004

Year

% Im

mun

ized Bolivia

ChinaIndiaIndonesiaKenya

Source: WDI Indicators Database

Distribution of Health Care Subsidies All India, 1995-6

0

5

10

15

20

25

30

35

Poorest II III IV Richest

Hospitals

Primary HealthCenters

Source: calculations based on Mahal et. al. 2001 – referred to in MTA para. 2.2.68

India 2003: Doctor absence from PHC’s

by state and reason

0

10

20

30

40

50

60

70

80

Official Duty

Leave

No reason

Quality is low, even when present (Delhi doctors)

0.1

.2.3

.4%

Who

ask

ed th

e re

leva

nt q

uest

ion

Private MBBS Private, No MBBS Public

...And What They DoWhat They Know

% Asked (DCO) % Asked (Vignettes)

What they do is in blue, what they know is in red. MBBS doctors are (roughly) the equivalent of MDs in the US. Das and Hammer (2005)

Chad“Although the regional administration is officially allocated 60 percent of the ministry's non-wage recurrent expenditures, the share of the resources that actually reach the regions is estimated to be only 18 percent. The health centers, which are the frontline providers and the entry point for the population, receive less than 1 percent of the ministry's non-wage recurrent expenditures.”

-- Bernard Gauthier and Waly Wane, “Leakage of public resources in the health sector : An empirical investigation of Chad,” 2008.

What can be done?

• Information

Primary Education in Uganda(PETS)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1990 1991 1993 1994 1995

US$ per Student

Intended Grant Amount Received by School (mean)

1999

Grants for Primary Education in Uganda

• In 1995, survey of 250 primary schools in 19 of 39 districts;

Primary Education in Uganda(PETS)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1990 1991 1993 1994 1995

US$ per Student

Intended Grant Amount Received by School (mean)

1999

• In 1995, survey of 250 primary schools in 19 of 39 districts;

• Survey repeated in 1998 and 2000.

Grants for Primary Education in Uganda

What can be done?

• Information• Separate public financing from provision

Stipends yield big gains for Bangladesh secondary education

Source: World Bank. 2006. Bangladesh: Secondary Education Development Support Credit II. World Bank: Washington, DC.

Rwanda: Results-based Financing

Donors

National Government

Households or Individuals

Results Based Aid

Results Based Contracting for

CCT, RB bonuses

Hospitals, Health Centers

Sub-National Government

District

Results Based Planning and Budgeting

National PBF model for Health Centers• Learning from 3 pilot experiences (since 2001)• Roll-out since May/June 2006• Currently 23 out of 30 districts covered• Seven control districts• 16 Primary Health Care indicators, e.g.

– New Curative Consultation = $0.27– Delivery at the HC = $3.63– Completely vaccinated child = $ 1.82

• 14 HIV/AIDS indicators, e.g. – One Pregnant woman tested (PMTCT) = $1.10– One couple tested voluntarily (PMTCT)= $1.10– HIV+ women treated with NVP = $1.10

• Separation of functions between stakeholders

Increase in Volume of Services (after 27 months)

PBF Indicator January 2006 average/month/

health center( 258 health centers

on average)

March 2008average/month/

health center(286 health centers

on average)

Percentage increase (linear/log R2)

Institutional Deliveries

21 37.5 78% (log 0.75)

New Curative Consultations

985 1,489 51% (log 0.19)

ANC: second dose of TT

21 52.5 150% (log 0.63)

Family Planning new users

15.5 47.9 209% (linear 0.88)

Family Planning users at the end of the month

175.2 711.6 306% (linear 0.98)

Rwanda 2005-2008Indicators DHS-2005 DHS-2008

Contraception (modern) 10% 27%Delivery in Health Centers 39% 52%

Infant Mortality rate 86 per 1000 62 per 1000

Under-Five Mortality rate 152 per 1000

103 per 1000

Anemia Prevalence : Children 56% 48%Vaccination : All 75% 80.4%

Vaccination : Measles 86% 90%Use of Insecticide treated nets

among children less than 54% 67%

Fertility 6.1 children

5.5 children

How to end poverty

Market failuresEfficiency & Equity

Government failure

How to end povertyMarket failuresEfficiency & Equity

Government failure