the benefit incidence of public spending in ethiopia
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Ethiopia Development Research Institute (EDRI) and International Food Policy Research Institute (IFPRI) Seminar Series, August 20, 2010 Addis Ababa, EDRI Meeting RoomTRANSCRIPT
The Benefit Incidence of Public Spending in Ethiopia
Agricultural Extension, Drinking Water, and the Food Security Programme
Tewodaj Mogues
Preliminary results: Comments very welcome!
Acknowledgements
• Financial support for this study:• IrishAid (through its Ethiopia country office)• World Bank (through its Ethiopia country office)
• The study draws on data, the survey work for which was financed by:• Ethiopia Strategy Support Programme II (ESSP-II)• IrishAid (country office)• World Bank (country office)• World Bank (through BNPP trust fund)
BIA in Three Programmes in Ethiopia
• The benefit incidence of local public investments in selected agricultural and rural programmes in Ethiopia• Agricultural extension• Food Security Programme• Drinking water supply
• Asks: Who benefits the most? the least? from these programmes? • To what extent does local public spending reach
different wealth groups? To what extent women versus men?
Why these three programmes
• Ag extension: recent big-push to dramatically expand extension services—how far have different segments of rural areas gained access to these services?
• FSP: A huge programme, the second-largest of its kind in Africa, seeking to target food insecure households—examine the incidence of FSP components by wealth groups and gender
• Drinking water: A service which has been identified as the most important by households themselves (IFPRI/WB 2010)—what types of households have better access to (safe) drinking water?
Benefit Incidence Analysis – What it does and doesn’t do
• What benefit incidence analysis does do:• Provides insights into how the benefits from the supply of
public services are distributed across different socio-economic groups
• E.g. can address whether public spending in certain sectors is progressive or regressive
• Allows examination of extent to which public resources equitably benefit men and women
• What benefit incidence analysis doesn’t do:• It does not examine the impact of having access to these
public services on other outcomes (e.g. household income, agricultural production, etc.)
Existing BIAs have neglected agriculture
• In studies of benefit incidence in developing countries, agricultural and rural services wholly neglected• Nearly all BIA analyses are on the health and education
sectors (e.g. Younger 2003 for Peru, Castro-Leal 1999 for S. Africa, van de Walle 1994 for Indonesia, Lanjouw et al. 2001 for Indonesia)
• In Ethiopia, the only benefit incidence analysis I am aware of is World Bank (2005) and Woldehanna and Jones (2006), both on the education sector
• Yet, important—certainly in Ethiopia, though not only here—to understand who is most reached by public investments for agricultural and rural development
Benefit incidence of public spending: Basic Methodology
• Some notation: i = public service type (index); j = quantile index; l = location index; = No. of people in quantile j and location l with access to service i; = public spending on service i in location l; Mj = No. of people in quantile j;
• Benefit incidence of public spending:• Benefit incidence (share of public spending on
service i accruing to quantile j), where:
• Amount of public spending on service i reaching
quantile j, with
• Total amount of public spending on service i
• Benefit-to-population odds ratio:
Average vs. Marginal Benefit Incidence
From: Lanjouw & Ravallion (1999)
Average vs. Marginal Benefit Incidence
• Additional notation: k = lower administrative unit index (below l)
• Average odds ratio:
• Marginal odds ratio:
• Define , i.e. the average participation rate of quantile j
• The marginal odds ratio MOj is obtained through instrumental
variables estimation of:
• where is instrumented by , the “leave-out mean” participation rate for the higher unit l, i.e. the mean participation rate in l, after removing the respondents in the jth quantile of lower unit k.
• MOj = βj , the marginal odds ratio for quantile j
Data Used in this Study
• “Demand-side” data on the use of public services: Gender and Rural Services Survey• Eight weredas in seven regions• Kebele-level surveys: Census of all kebeles in the sample
weredas• Household/individual level survey: In four randomly selected
kebeles in each sample wereda (total of 1,118 households; 1,898 respondents)
• Each questionnaire was administered separately to the head as well as spouse of each sample household
• “Supply-side” data on the provision of public services: Wereda-City Benchmarking Survey• Used wereda-level survey’s data on the sample weredas
overlapping with G & RS survey
Agricultural Extension
Public Spending Wealth Incidence of Ag. Extension (Benefit-to-Population Odds Ratio)
Public Spending Wealth Incidence of Ag. Extension (Benefit-to-Population Odds Ratio)
Concentration Curve of Extension Access0
.2.4
.6.8
1
0 .2 .4 .6 .8 1
Farm/home visit DA meetings All extension
Incidence of Ag Extension, by Gender and Headship Status
Total Women Men* Gender gap
Total
All extension 32.93% 24.70% 42.43% 0.58Visit farm/home 22.90% 20.37% 25.82% 0.79DA meetings 19.16% 11.12% 28.44% 0.39Demo. plot/home 3.22% 1.08% 5.69% 0.19FTC 0.79% 0.59% 1.02% 0.58
Heads of households
All extension 39.44% 28.75% 42.38% 0.68Visit farm/home 25.43% 23.75% 25.89% 0.92DA meetings 26.06% 17.92% 28.29% 0.63Demo. plot/home 5.03% 2.92% 5.61% 0.52FTC 0.90% 0.42% 1.03% 0.41
Spouses of household heads
All extension 23.66% 23.45%Visit farm/home 19.31% 19.33%DA meetings 9.34% 9.02%Demo. plot/home 0.64% 0.52%FTC 0.64% 0.64%
Headship gap
All extension 0.60 0.82Visit farm/home 0.76 0.81DA meetings 0.36 0.50Demo. plot/home 0.13 0.18FTC 0.71 1.52
Public Spending Incidence of Ag Extension, by Gender and Headship Status
Benefit share B-P odds ratio
Gender
Women 41.97% 0.78
Men 58.03% 1.25
Total 100% —
Headship status
Spouse 29.98% 0.73
Head 70.02% 1.19
Total 100% —
Average and Marginal Odds Ratio for Agricultural Extension
Q1 (poorest) Q2 Q3 Q4 Q5
TotalAverage odds 1.193 1.506 0.873 0.705 0.723
Marginal odds 1.081 *** 1.080 *** 0.828 *** -0.050 1.325 ***
(0.100) (0.097) (0.150) (0.156) (0.192)WomenAverage odds 1.283 1.646 0.871 0.598 0.539
Marginal odds1.029 *** 1.070 *** 0.671 ** -0.098 1.117 **
(0.082) (0.177) (0.275) (0.079) (0.556)MenAverage odds 1.202 1.401 0.858 0.760 0.824
Marginal odds 1.225 *** 1.024 *** 0.888 *** 0.303 1.268 ***
(0.152) (0.093) (0.139) (0.336) (0.124)
Food Security Programme
Public Spending Incidence of FSP (Benefit-to-Population Odds Ratio)
Public Spending Incidence of PW (Benefit-to-Population Odds Ratio)
Public Spending Incidence of DS (Benefit-to-Population Odds Ratio)
Concentration Curve of Access to FSP
0.2
.4.6
.81
0 .2 .4 .6 .8 1
FSP Direct Support Public Works Assets
Concentration Curve of Value of FSP receipts
0.2
.4.6
.81
0 .2 .4 .6 .8 1
FSP Direct Support Public Works Assets
Public Spending Incidence of FSP, by Gender
All FSP BP odds ratio
Public Works
BP odds ratio
Direct Support
BP odds ratio
Female-headed HHs 25.34% 0.89 18.45% 0.65 79.38% 2.78Male-headed HHs 74.66% 1.04 81.55% 1.14 20.62% 0.29
Average and Marginal Odds Ratio for FSP
Q1 (poorest)
Q2 Q3 Q4 Q5
TotalAverage odds 1.454 1.360 0.658 0.699 0.831Marginal odds 1.239 *** 0.861 *** 0.647 *** 0.768 *** 0.920 ***
(0.127) (0.135) (0.139) (0.158) (0.189)Female-Headed HHsAverage odds 0.916 1.150 0.827 1.078 1.102Marginal odds 0.746 *** 0.924 *** 0.954 *** 0.809 *** 1.089 ***
(0.259) (0.188) (0.252) (0.171) (0.113)Male-Headed HHsAverage odds 1.765 1.459 0.647 0.644 0.758Marginal odds 1.486 *** 0.914 *** 0.585 *** 0.807 *** 0.872 ***
(0.211) (0.143) (0.155) (0.203) (0.206)
Drinking Water
Time to Primary Water Source in Dry Season (minutes)
Time to Primary Water Source in Wet Season (minutes)
Access to Improved Water Sources in Both Seasons (%)
Gender Incidence of Water Supply
Female-headed HHs
Male-headed HHs
Gender gap (ratio)
Physical access to drinking water (minutes)
Primary source in dry season
One-way 29.0 24.3 1.20Full trip 73.5 63.0 1.17
Primary source in wet season
One-way 25.1 19.9 1.26Full trip 62.8 50.5 1.24
Use of safe drinking water (per cent)
Primary source in:
Dry season 49.51% 33.68% 1.47Wet season 48.53% 35.25% 1.38Both seasons 48.04% 32.38% 1.48
All sources used in:
Dry season 29.56% 24.77% 1.19Wet season 29.56% 25.40% 1.16Both seasons 28.08% 23.55% 1.19
Summary and Conclusions
• Agricultural extension:
• On average, greatest incidence for poorest households
• However, incidence of the least poor is highest on the margin
• Women’s incidence pronouncedly lower (only partially explained by headship status
• FSP:
• Pronouncedly pro-poor overall
• However, while DS’s incidence is highest for FHHs, benefits of DS spending accrue disproportionately to least poor
• Water supply
• Surprisingly, benefit incidence of drinking water supply is highest for the poorest households
• While FHHs’s is poorer when considering physical access to water, they consume better quality water at a higher rate than MHHs
The Benefit Incidence of Public Spending in Ethiopia
Agricultural Extension, Drinking Water, and the Food Security Programme
Tewodaj Mogues