The Benefit Incidence of Public Spending in Ethiopia Agricultural Extension, Drinking Water, and the Food Security Program...
Acknowledgements <ul><li>Financial support for this study: </li></ul><ul><ul><li>IrishAid (through its Ethiopia country of...
BIA in Three Programmes in Ethiopia <ul><li>The benefit incidence of local public investments in selected agricultural and...
Why these three programmes <ul><li>Ag extension:  recent big-push to dramatically expand extension services—how far have d...
Benefit Incidence Analysis –  What it does and doesn’t do <ul><li>What benefit incidence analysis  does  do: </li></ul><ul...
Existing BIAs have neglected agriculture <ul><li>In studies of benefit incidence in developing countries, agricultural and...
Benefit incidence of public spending: Basic Methodology <ul><li>Some notation:  i  = public service type (index);  j  = qu...
Average vs. Marginal Benefit Incidence From: Lanjouw & Ravallion (1999)
Average vs. Marginal Benefit Incidence <ul><li>Additional notation:   k  = lower administrative unit index (below  l ) </l...
Data Used in this Study <ul><li>“ Demand-side” data on the  use  of public services: Gender and Rural Services Survey </li...
<ul><li>Agricultural Extension </li></ul>
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 Access
Incidence of Ag Extension,  by Gender and Headship Status     Total Women Men * Gender gap Total All extension 32.93% 24.7...
Public Spending Incidence of Ag Extension,  by Gender and Headship Status Benefit share B-P odds ratio Gender Women 41.97%...
Average and Marginal Odds Ratio for Agricultural Extension Q1 (poorest) Q2 Q3 Q4 Q5 Total Average odds 1.193 1.506 0.873 0...
<ul><li>Food Security Programme </li></ul>
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
Concentration Curve of  Value of FSP receipts
Public Spending Incidence of FSP, by Gender All FSP BP odds ratio Public Works BP odds ratio Direct Support BP odds ratio ...
Average and Marginal Odds Ratio for FSP Q1 (poorest) Q2 Q3 Q4 Q5 Total Average odds 1.454 1.360 0.658 0.699 0.831 Marginal...
<ul><li>Drinking Water </li></ul>
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 (m...
Summary and Conclusions <ul><li>Agricultural extension:  </li></ul><ul><ul><li>On average, greatest incidence for poorest ...
The Benefit Incidence of Public Spending in Ethiopia Agricultural Extension, Drinking Water, and the Food Security Program...
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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 Room

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  • Table 10
  • Table 10: Pro-poor access to extension
  • Table 10
  • Figure 2: Farm/home visits more likely to reach poor households
  • Table 11: 1) Relatively high access 2) Gender gap is large; differentiated by extension type 3) Headship gap pertains; 4) Gender vs head
  • Table 11
  • Table 12: 1) Average odds shows pro-poor 2) But: Richest gain the most from expansion of service
  • Table 13: Pro-poor access for FSP
  • Table 13: Still pro poor
  • Table 13: Not true for DS! Best-off gain the most 2) Driven by female results
  • Figure 3: This is reflected in CC as well
  • Figure 3: Even more pronounced when considering value of receipts
  • Table 14: Overall, incidence slightly higher for men However, women gain most from DS
  • Table 16: Poorest benefit less from expansion than they benefit on average (see Q1 and Q2).
  • Table 17
  • Table 17
  • Table 18
  • Table 19
  • The Benefit Incidence of Public Spending in Ethiopia

    1. 1. The Benefit Incidence of Public Spending in Ethiopia Agricultural Extension, Drinking Water, and the Food Security Programme Tewodaj Mogues Preliminary results: Comments very welcome!
    2. 2. Acknowledgements <ul><li>Financial support for this study: </li></ul><ul><ul><li>IrishAid (through its Ethiopia country office) </li></ul></ul><ul><ul><li>World Bank (through its Ethiopia country office) </li></ul></ul><ul><li>The study draws on data, the survey work for which was financed by: </li></ul><ul><ul><li>Ethiopia Strategy Support Programme II (ESSP-II) </li></ul></ul><ul><ul><li>IrishAid (country office) </li></ul></ul><ul><ul><li>World Bank (country office) </li></ul></ul><ul><ul><li>World Bank (through BNPP trust fund) </li></ul></ul>
    3. 3. BIA in Three Programmes in Ethiopia <ul><li>The benefit incidence of local public investments in selected agricultural and rural programmes in Ethiopia </li></ul><ul><ul><li>Agricultural extension </li></ul></ul><ul><ul><li>Food Security Programme </li></ul></ul><ul><ul><li>Drinking water supply </li></ul></ul><ul><li>Asks: Who benefits the most? the least? from these programmes? </li></ul><ul><ul><li>To what extent does local public spending reach different wealth groups? To what extent women versus men? </li></ul></ul>
    4. 4. Why these three programmes <ul><li>Ag extension: recent big-push to dramatically expand extension services—how far have different segments of rural areas gained access to these services? </li></ul><ul><li>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 </li></ul><ul><li>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? </li></ul>
    5. 5. Benefit Incidence Analysis – What it does and doesn’t do <ul><li>What benefit incidence analysis does do: </li></ul><ul><ul><li>Provides insights into how the benefits from the supply of public services are distributed across different socio-economic groups </li></ul></ul><ul><ul><li>E.g. can address whether public spending in certain sectors is progressive or regressive </li></ul></ul><ul><ul><li>Allows examination of extent to which public resources equitably benefit men and women </li></ul></ul><ul><li>What benefit incidence analysis doesn’t do: </li></ul><ul><ul><li>It does not examine the impact of having access to these public services on other outcomes (e.g. household income, agricultural production, etc.) </li></ul></ul>
    6. 6. Existing BIAs have neglected agriculture <ul><li>In studies of benefit incidence in developing countries, agricultural and rural services wholly neglected </li></ul><ul><ul><li>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) </li></ul></ul><ul><ul><li>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 </li></ul></ul><ul><ul><li>Yet, important—certainly in Ethiopia, though not only here—to understand who is most reached by public investments for agricultural and rural development </li></ul></ul>
    7. 7. Benefit incidence of public spending: Basic Methodology <ul><li>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 ; M j = No. of people in quantile j ; </li></ul><ul><li>Benefit incidence of public spending: </li></ul><ul><ul><li> Benefit incidence (share of public spending on </li></ul></ul><ul><ul><li> service i accruing to quantile j ), where: </li></ul></ul><ul><ul><li> Amount of public spending on service i reaching </li></ul></ul><ul><ul><li> quantile j , with </li></ul></ul><ul><ul><li> Total amount of public spending on service i </li></ul></ul><ul><li>Benefit-to-population odds ratio: </li></ul>
    8. 8. Average vs. Marginal Benefit Incidence From: Lanjouw & Ravallion (1999)
    9. 9. Average vs. Marginal Benefit Incidence <ul><li>Additional notation: k = lower administrative unit index (below l ) </li></ul><ul><li>Average odds ratio: </li></ul><ul><li>Marginal odds ratio: </li></ul><ul><ul><li>Define , i.e. the average participation rate of quantile j </li></ul></ul><ul><ul><li>The marginal odds ratio MO j is obtained through instrumental </li></ul></ul><ul><ul><li>variables estimation of: </li></ul></ul><ul><ul><li>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 j th quantile of lower unit k . </li></ul></ul><ul><ul><li>MO j = β j , the marginal odds ratio for quantile j </li></ul></ul>
    10. 10. Data Used in this Study <ul><li>“ Demand-side” data on the use of public services: Gender and Rural Services Survey </li></ul><ul><ul><li>Eight weredas in seven regions </li></ul></ul><ul><ul><li>Kebele-level surveys: Census of all kebeles in the sample weredas </li></ul></ul><ul><ul><li>Household/individual level survey: In four randomly selected kebeles in each sample wereda (total of 1,118 households; 1,898 respondents) </li></ul></ul><ul><ul><ul><li>Each questionnaire was administered separately to the head as well as spouse of each sample household </li></ul></ul></ul><ul><li>“ Supply-side” data on the provision of public services: Wereda-City Benchmarking Survey </li></ul><ul><ul><li>Used wereda-level survey’s data on the sample weredas overlapping with G & RS survey </li></ul></ul>
    11. 11. <ul><li>Agricultural Extension </li></ul>
    12. 12. Public Spending Wealth Incidence of Ag. Extension (Benefit-to-Population Odds Ratio)
    13. 13. Public Spending Wealth Incidence of Ag. Extension (Benefit-to-Population Odds Ratio)
    14. 14. Concentration Curve of Extension Access
    15. 15. Incidence of Ag Extension, by Gender and Headship Status     Total Women Men * Gender gap Total All extension 32.93% 24.70% 42.43% 0.58 Visit farm/home 22.90% 20.37% 25.82% 0.79 DA meetings 19.16% 11.12% 28.44% 0.39 Demo. plot/home 3.22% 1.08% 5.69% 0.19 FTC 0.79% 0.59% 1.02% 0.58 Heads of households All extension 39.44% 28.75% 42.38% 0.68 Visit farm/home 25.43% 23.75% 25.89% 0.92 DA meetings 26.06% 17.92% 28.29% 0.63 Demo. plot/home 5.03% 2.92% 5.61% 0.52 FTC 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 0.82 Visit farm/home 0.76 0.81 DA meetings 0.36 0.50 Demo. plot/home 0.13 0.18 FTC 0.71 1.52
    16. 16. 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% —
    17. 17. Average and Marginal Odds Ratio for Agricultural Extension Q1 (poorest) Q2 Q3 Q4 Q5 Total Average 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) Women Average odds 1.283 1.646 0.871 0.598 0.539 Marginal odds 1.029 *** 1.070 *** 0.671 ** -0.098 1.117 ** (0.082) (0.177) (0.275) (0.079) (0.556) Men Average 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)
    18. 18. <ul><li>Food Security Programme </li></ul>
    19. 19. Public Spending Incidence of FSP (Benefit-to-Population Odds Ratio)
    20. 20. Public Spending Incidence of PW (Benefit-to-Population Odds Ratio)
    21. 21. Public Spending Incidence of DS (Benefit-to-Population Odds Ratio)
    22. 22. Concentration Curve of Access to FSP
    23. 23. Concentration Curve of Value of FSP receipts
    24. 24. 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% 2.78 Male-headed HHs 74.66% 1.04 81.55% 1.14 20.62% 0.29
    25. 25. Average and Marginal Odds Ratio for FSP Q1 (poorest) Q2 Q3 Q4 Q5 Total Average odds 1.454 1.360 0.658 0.699 0.831 Marginal odds 1.239 *** 0.861 *** 0.647 *** 0.768 *** 0.920 *** (0.127) (0.135) (0.139) (0.158) (0.189) Female-Headed HHs Average odds 0.916 1.150 0.827 1.078 1.102 Marginal odds 0.746 *** 0.924 *** 0.954 *** 0.809 *** 1.089 *** (0.259) (0.188) (0.252) (0.171) (0.113) Male-Headed HHs Average odds 1.765 1.459 0.647 0.644 0.758 Marginal odds 1.486 *** 0.914 *** 0.585 *** 0.807 *** 0.872 *** (0.211) (0.143) (0.155) (0.203) (0.206)
    26. 26. <ul><li>Drinking Water </li></ul>
    27. 27. Time to Primary Water Source in Dry Season (minutes)
    28. 28. Time to Primary Water Source in Wet Season (minutes)
    29. 29. Access to Improved Water Sources in Both Seasons (%)
    30. 30. 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 1.20 Full trip 73.5 63.0 1.17 Primary source in wet season One-way 25.1 19.9 1.26 Full trip 62.8 50.5 1.24 Use of safe drinking water (per cent) Primary source in: Dry season 49.51% 33.68% 1.47 Wet season 48.53% 35.25% 1.38 Both seasons 48.04% 32.38% 1.48 All sources used in: Dry season 29.56% 24.77% 1.19 Wet season 29.56% 25.40% 1.16 Both seasons 28.08% 23.55% 1.19
    31. 31. Summary and Conclusions <ul><li>Agricultural extension: </li></ul><ul><ul><li>On average, greatest incidence for poorest households </li></ul></ul><ul><ul><li>However, incidence of the least poor is highest on the margin </li></ul></ul><ul><ul><li>Women’s incidence pronouncedly lower (only partially explained by headship status </li></ul></ul><ul><li>FSP: </li></ul><ul><ul><li>Pronouncedly pro-poor overall </li></ul></ul><ul><ul><li>However, while DS’s incidence is highest for FHHs, benefits of DS spending accrue disproportionately to least poor </li></ul></ul><ul><li>Water supply </li></ul><ul><ul><li>Surprisingly, benefit incidence of drinking water supply is highest for the poorest households </li></ul></ul><ul><ul><li>While FHHs’s is poorer when considering physical access to water, they consume better quality water at a higher rate than MHHs </li></ul></ul>
    32. 32. The Benefit Incidence of Public Spending in Ethiopia Agricultural Extension, Drinking Water, and the Food Security Programme Tewodaj Mogues
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