overcoming market and government failures in india and africa
DESCRIPTION
Overcoming Market and Government Failures in India and Africa. Shanta Devarajan World 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. - PowerPoint PPT PresentationTRANSCRIPT
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