Elsa Valli examines if any recent changes have been made to the way aid is targeted in Ethiopia and the outcomes.

1. Targeting of aid in rural Ethiopia: Any improvement
with recent changes?
Elsa Valli
CSAE Conference 2017
University of Sussex & UNICEF Office of Research
March 20, 2017
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 1 / 22

2. Outline
1 Motivation and literature review
2 Aid in Ethiopia: Food Aid and PSNP
3 Data and Descriptive statistics
4 Empirical strategy
5 Results
6 Conclusions
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 2 / 22

3. Motivation and literature review
Motivation
Ethiopia: drought-prone country and long history of aid,
emergency-based
Aid in 2 forms: Public Works and Food Aid
In 2005 major reforms on aid
Targeting in Ethiopia: Community-Based Targeting (CBT)
Studies on targeting of past aid: biases in selection of beneficiaries
(gender and political connections) and targeting errors (geography and
assets/welfare)
Growing attention to targeting in Sub-Saharan Africa
Question: Has there been any improvement in targeting after the major
changes in aid programmes in Ethiopia compared to the past?
Is now aid reaching the poorest and the most vulnerable?
Do political connections still play an important role in aid allocation?
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 3 / 22

4. Motivation and literature review
Literature Review
Targeting of anti-poverty programmes
Community-Based Targeting (CBT): mixed evidence. More transparent,
better information, higher perceived fairness. BUT risks of elite capture and
rent seeking behaviours (Bardhan et al., 2000; Conning et al., 2002; Alatas
et al., 2012)
Evidence in Africa: comparison different methods (Handa et al., 2012;
Sabates-Wheeler et al., 2015) and challenging PMT (Brown et al., 2016;
Kidd et al., 2017)
Targeting in Ethiopia
PW: mostly determined on labour supply characteristics; FA: some evidence
of targeting based on demographics and economic need (Jayne et al., 2002,
JDE)
Political connections important role (Caeyers & Dercon, 2012; Broussard et
al., 2014)
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 4 / 22

5. Aid in Ethiopia: Food Aid and PSNP
Aid in Ethiopia: Food Aid and PSNP
Previous aid programmes similar characteristics BUT emergency-based,
discontinuous, unpredictable
Productive Safety Net Programme (PSNP)
Started in 2005, still ongoing
Coverage: 7.5 mln people (10% of population)
Budget: $360m (1.2% of GDP). Annual avg transfers per hh: $137 (14% of
GDP pc)
Components: Public Works (PW): used to build community infrastructure
during non-farming activities; Direct Support (labour-constrained
households)
Objective: "to assure food consumption and prevent asset depletion for food
insecure households in chronically food insecure Woredas, while stimulating
markets, improving services and natural resources, and rehabilitating and
enhancing the natural environment"
Emergency Food Aid still massive ($509m per year 2002-2012).
Humanitarian Response Fund (2006)
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 5 / 22

6. Aid in Ethiopia: Food Aid and PSNP
Targeting
Allocation of aid in two stages: federal and district
List of beneficiaries by Community Food Security Task Force
Policy changes with PSNP (list of beneficiaries in public and endorsed by
public meeting, grievance procedures)
Target of PSNP: chronically food insecure households
Continuous food shortages in last 3 years and received food assistance prior
to PSNP
Suddenly more vulnerable and not able to support themselves
Without family support and other means of social protection and support
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 6 / 22

7. Data and Descriptive statistics
Data
Ethiopian Rural Household Survey
Panel with 7 rounds in 15 rural villages across different agro-ecological areas
Sample: 1,477 households
Modules on aid
Livestock
Food insecurity: months the household faced food shortages in previous
12 months
Political connections: friends or relatives holding a position in the local
administration
For analysis: 2 rounds for comparability
2004
2009
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 7 / 22

8. Data and Descriptive statistics
Summary statistics
Table 1: Characteristics of households by beneficiary status and round: Public Works
2004 2009
Non-benef Benef Diff. Non-benef Benef Diff.
Head primary education 0.14 0.14 -0.00 0.16 0.13 -0.03
Female head 0.36 0.28 -0.08** 0.37 0.46 0.09**
Age head 51.30 48.01 -3.29*** 54.29 50.23 -4.06***
Ability score 1.46 1.24 -0.22*** 1.62 1.38 -0.24***
Household size 5.41 5.94 0.53** 5.50 5.75 0.25
Share of elders 0.10 0.04 -0.06*** 0.12 0.05 -0.08***
Livestock pc 307.25 362.27 55.03* 350.67 217.47 -133.20***
Food insecurity 2.89 3.60 0.72*** 3.45 4.58 1.13***
Political connections 0.32 0.46 0.13*** 0.32 0.33 0.01
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 8 / 22

9. Data and Descriptive statistics
Summary statistics
Table 2: Characteristics of households by beneficiary status and round: Food Aid
2004 2009
Non-benef Benef Diff. Non-benef Benef Diff.
Head primary education 0.13 0.12 -0.01 0.24 0.21 -0.03
Female head 0.33 0.33 -0.00 0.34 0.33 -0.00
Age head 49.08 51.55 2.48** 50.15 55.02 4.87***
Ability score 1.27 1.47 0.20*** 1.38 1.53 0.15**
Household size 5.98 5.50 -0.47** 5.97 5.66 -0.31
Share of elders 0.05 0.09 0.05*** 0.06 0.13 0.08***
Livestock pc 311.34 362.29 50.95* 324.74 172.06 -152.67***
Food insecurity 3.11 3.49 0.38** 3.36 4.14 0.79***
Political connections 0.38 0.45 0.08** 0.40 0.43 0.02
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 9 / 22

10. Empirical strategy
Empirical strategy
Pooled model
Yijt = β0 + β1Xijt + β2(Xijt ∗ t1) + vjt + εijt (1)
Yijt : 0/1 participation in PW/FA; amount of aid (log of real amount of aid per household)
Xijt : household characteristics, assets, shocks, political affiliations
t1: 0/1 dummy for year 2009
vjt : time-varying village fixed effects
Standard errors clustered at household level
Models
Participation equations: Probit
Level equations: Tobit
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 10 / 22

11. Results
Public Works
Participation (Probit ME) Amount (Tobit ME)
(Pooled) (Full int) (Net) (Pooled) (Full int) (Net)
Log pc livestock -0.022** -0.004 -0.060** -0.004
(0.009) (0.009) (0.027) (0.024)
Food insecurity 0.021*** 0.030*** 0.061*** 0.078***
(0.007) (0.009) (0.023) (0.024)
Political connections (d) 0.069* 0.083** 0.191* 0.205*
(0.037) (0.037) (0.112) (0.106)
2009 * Log pc livestock -0.033** -0.037** -0.212*** -0.216***
(0.015) (0.017) (0.074) (0.078)
2009 * Food insecurity -0.024** 0.006 -0.082 -0.004
(0.012) (0.015) (0.057) (0.062)
2009 * Political connections (d) -0.069 0.014 -0.178 0.027
(0.055) (0.066) (0.280) (0.299)
Controls Yes Yes Yes Yes
Time-varying village fe Yes Yes Yes Yes
Observations 1110 1110 1110 1110
LL -626.071 -616.275 -1665.855 -1652.691
Significance levels * 10% ** 5% *** 1%. Standard errors are clustered at the household level.
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 11 / 22

12. Results
Food Aid
Participation (Probit ME) Amount (Tobit ME)
(Pooled) (Full int) (Net) (Pooled) (Full int) (Net)
Log pc livestock -0.015* -0.012 -0.035** -0.023
(0.008) (0.010) (0.018) (0.022)
Food insecurity 0.003 0.005 0.005 0.012
(0.007) (0.010) (0.016) (0.022)
Political connections (d) 0.079** 0.073* 0.134* 0.156
(0.031) (0.041) (0.074) (0.098)
2009 * Log pc livestock -0.003 -0.015 0.005 -0.018
(0.011) (0.015) (0.015) (0.027)
2009 * Food insecurity -0.002 0.003 0.005 0.018
(0.010) (0.014) (0.014) (0.027)
2009 * Political connections (d) 0.001 0.073 -0.030 0.126
(0.046) (0.062) (0.069) (0.119)
Time-varying village fe Yes Yes Yes Yes
Observations 1352 1352 1352 1352
LL -774.581 -773.444 -1773.841 -1253.877
Significance levels * 10% ** 5% *** 1%. Standard errors are clustered at the household level.
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 12 / 22

13. Results
Robustness checks
Past aid and political connections
Different models (SUR models)
Analysis done also restricting only to villages that received both FA and
PW
Quantile regressions on amount of aid received
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 13 / 22

14. Conclusions
Conclusions
Compare the differences in targeting with a focus on three main variables
that capture food insecurity, poverty and political connections
Public Works: Evidence of improvement
Livestock now strong predictor
Political connections not a key factor anymore
Food Aid: Only minor improvement
In economic terms, no differences and no signs of targeting along welfare
lines
Political connections not a key factor anymore
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 14 / 22

15. Conclusions
Thank you!
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 15 / 22

16. Conclusions
Appendix
Targeting before and during PSNP
Probability of receiving aid and amount by consumption percentiles
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 16 / 22

17. Conclusions
pw: Summary statistics
Table 3: Characteristics of PW beneficiary/non-beneficiary households before/during
PSNP
Pre-PSNP PSNP
No FA FA Diff. p-value No FA FA Diff. p-value
Real consumption pc 82.94 77.61 -5.32 0.32 55.51 49.66 -5.84 0.13
Head primary education 0.14 0.14 -0.00 0.88 0.16 0.13 -0.03 0.43
Female head 0.36 0.28 -0.08 0.03 0.37 0.46 0.09 0.05
Age head 51.30 48.01 -3.29 0.00 54.29 50.23 -4.06 0.00
Ability score 1.46 1.24 -0.22 0.00 1.62 1.38 -0.24 0.00
Household size 5.41 5.94 0.53 0.01 5.50 5.75 0.25 0.29
Share of elders 0.10 0.04 -0.06 0.00 0.12 0.05 -0.08 0.00
Livestock pc 307.25 362.27 55.03 0.06 350.67 217.47 -133.20 0.00
Food insecurity 2.89 3.60 0.72 0.00 3.45 4.58 1.13 0.00
Office 0.32 0.46 0.13 0.00 0.32 0.33 0.01 0.81
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 17 / 22

18. Conclusions
FA: Summary statistics
Table 4: Characteristics of FA beneficiary/non-beneficiary households before/during
PSNP
Pre-PSNP PSNP
No FA FA Diff. p-value No FA FA Diff. p-value
Real consumption pc 77.53 83.52 5.99 0.29 54.38 38.22 -16.15 0.00
Head primary education 0.13 0.12 -0.01 0.77 0.24 0.21 -0.03 0.28
Female head 0.33 0.33 -0.00 0.93 0.34 0.33 -0.00 0.92
Age head 49.08 51.55 2.48 0.03 50.15 55.02 4.87 0.00
Ability score 1.27 1.47 0.20 0.00 1.38 1.53 0.15 0.01
Household size 5.98 5.50 -0.47 0.02 5.97 5.66 -0.31 0.11
Share of elders 0.05 0.09 0.05 0.00 0.06 0.13 0.08 0.00
Livestock pc 311.34 362.29 50.95 0.09 324.74 172.06 -152.67 0.00
Food insecurity 3.11 3.49 0.38 0.03 3.36 4.14 0.79 0.00
Office 0.38 0.45 0.08 0.05 0.40 0.43 0.02 0.50
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 18 / 22

19. Conclusions
Participation in PW
Sur LPM Probit ME Bivariate Probit ME
(1) (2) (3) (4) (5) (6)
Log household size 0.057* 0.111** 0.105** 0.109** 0.028 0.109**
(0.031) (0.052) (0.051) (0.052) (0.021) (0.052)
Share of elders -0.366*** -0.566*** -0.794*** -0.638*** -0.295** -0.638***
(0.070) (0.110) (0.145) (0.154) (0.127) (0.150)
Female head (d) -0.029 -0.086** -0.053 -0.087** -0.022 -0.084*
(0.027) (0.043) (0.041) (0.043) (0.016) (0.043)
Head primary education (d) -0.062** -0.087 -0.094* -0.092* -0.033* -0.093*
(0.029) (0.056) (0.052) (0.054) (0.017) (0.053)
Age head -0.002** -0.002 -0.003** -0.002 -0.001* -0.002
(0.001) (0.002) (0.001) (0.001) (0.001) (0.001)
Hh head died (d) 0.053 0.048 0.102 0.036 0.034 0.039
(0.049) (0.077) (0.092) (0.084) (0.042) (0.085)
Log pc livestock -0.013** -0.005 -0.022** -0.004 -0.009* -0.005
(0.006) (0.009) (0.009) (0.009) (0.005) (0.009)
Food insecurity 0.012*** 0.028*** 0.021*** 0.030*** 0.007* 0.030***
(0.004) (0.009) (0.007) (0.009) (0.004) (0.009)
Associates office (d) 0.032 0.077** 0.069* 0.083** 0.020 0.084**
(0.021) (0.037) (0.037) (0.037) (0.017) (0.037)
t1 (d) -0.141* 0.132 -0.167* 0.272 -0.060* 0.350
(0.083) (0.174) (0.095) (0.223) (0.035) (0.216)
t1 * Share of elders 0.303** -0.022 -0.018
(0.136) (0.207) (0.125)
t1 * Female head (d) 0.102** 0.078 0.038
(0.052) (0.059) (0.036)
t1 * Head died (d) 0.016 0.171 0.073
(0.091) (0.111) (0.069)
t1 * Log pc livestock -0.014 -0.033** -0.021***
(0.011) (0.015) (0.008)
t1 * Food insecurity -0.025** -0.024** -0.016**
(0.011) (0.012) (0.007)
t1 * Associates office (d) -0.083* -0.069 -0.054*
(0.045) (0.055) (0.032)
Time-varying village fixed effects Yes Yes Yes Yes Yes Yes
Pseudo R2
0.375 0.391 0.184 0.197
Observations 1532 1532 1110 1110 1532 1532
LL -626.071 -616.275 -1455.746 -1442.621
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 19 / 22

20. Conclusions
Amount of PW
Two-Part OLS SUR Two-Part OLS Tobit
(1) (2) (3) (4) (5) (6)
Log household size 0.538*** 0.255** 0.603*** 0.536*** 0.439*** 0.349**
(0.080) (0.107) (0.114) (0.154) (0.162) (0.152)
Share of elders -0.263 -0.350 -1.371*** -1.562*** -2.770*** -2.326***
(0.342) (0.461) (0.306) (0.362) (0.626) (0.569)
Female head (d) -0.026 -0.040 -0.146 -0.247** -0.156 -0.282**
(0.063) (0.085) (0.094) (0.120) (0.117) (0.121)
Head primary education (d) 0.138 0.177 -0.019 0.118 -0.184 -0.168
(0.088) (0.126) (0.100) (0.155) (0.141) (0.131)
Age head -0.003 0.003 -0.007* -0.002 -0.007* -0.001
(0.002) (0.003) (0.004) (0.004) (0.004) (0.004)
Hh head died (d) 0.096 0.024 0.206 0.102 0.316 0.123
(0.085) (0.105) (0.165) (0.215) (0.250) (0.211)
Log pc livestock 0.008 0.004 -0.018 0.003 -0.060** -0.004
(0.018) (0.022) (0.019) (0.027) (0.027) (0.024)
Food insecurity 0.016 0.013 0.027 0.065** 0.061*** 0.078***
(0.013) (0.018) (0.018) (0.027) (0.023) (0.024)
Associates office (d) 0.120* 0.104 0.111 0.181 0.191* 0.205*
(0.062) (0.077) (0.087) (0.111) (0.112) (0.106)
t1 (d) 1.153*** 0.434 0.443 0.987 -0.289 0.905
(0.271) (0.493) (0.419) (0.716) (0.342) (0.756)
t1 * Share of elders -0.120 0.339 -0.174
(0.628) (0.564) (1.202)
t1 * Female head (d) 0.015 0.187 0.447
(0.122) (0.186) (0.325)
t1 * Head died (d) 0.324 0.286 0.992
(0.208) (0.321) (0.637)
t1 * Log pc livestock 0.007 -0.033 -0.212***
(0.030) (0.038) (0.074)
t1 * Food insecurity 0.009 -0.062* -0.082
(0.024) (0.037) (0.057)
t1 * Associates office (d) 0.056 -0.152 -0.178
(0.124) (0.162) (0.280)
Constant 1.223*** 1.519*** 1.352*** 1.058**
(0.330) (0.379) (0.376) (0.464)
Time-varying village fixed effects Yes Yes Yes Yes Yes Yes
Pseudo/Adj R2
0.751 0.760 0.576 0.580 0.112 0.119
Observations 587 587 1045 1045 1110 1110
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 20 / 22

21. Conclusions
Participation in FA
Sur LPM Probit ME Bivariate Probit ME
(1) (2) (3) (4) (5) (6)
Log household size -0.032 -0.041 -0.036 -0.042 -0.113 -0.043
(0.034) (0.054) (0.044) (0.058) (0.108) (0.053)
Share of elders 0.303*** 0.364*** 0.373*** 0.368** 0.976*** 0.344**
(0.082) (0.134) (0.121) (0.166) (0.306) (0.155)
Female head (d) 0.018 0.009 0.019 -0.003 0.060 0.012
(0.027) (0.046) (0.037) (0.047) (0.091) (0.043)
Head primary education (d) 0.025 -0.006 0.015 -0.007 0.053 -0.015
(0.033) (0.053) (0.046) (0.061) (0.110) (0.054)
Age head 0.002** 0.001 0.003** 0.001 0.007** 0.001
(0.001) (0.002) (0.001) (0.002) (0.003) (0.002)
Hh head died (d) -0.058 -0.052 -0.077 -0.047 -0.203 -0.056
(0.059) (0.094) (0.078) (0.094) (0.187) (0.086)
Log pc livestock -0.011* -0.009 -0.015* -0.012 -0.034* -0.010
(0.006) (0.009) (0.008) (0.010) (0.020) (0.009)
Food insecurity 0.005 0.005 0.003 0.005 0.019 0.005
(0.005) (0.009) (0.007) (0.010) (0.017) (0.009)
Associates office (d) 0.054** 0.067* 0.079** 0.073* 0.185** 0.069*
(0.024) (0.039) (0.031) (0.041) (0.076) (0.037)
t1 (d) 0.029 -0.117 0.091 -0.096 0.346 -0.096
(0.041) (0.180) (0.078) (0.236) (0.404) (0.226)
t1 * Share of elders -0.097 -0.043 -0.020
(0.184) (0.193) (0.180)
t1 * Female head (d) 0.018 0.035 0.016
(0.064) (0.057) (0.051)
t1 * Head died (d) -0.016 -0.059 -0.032
(0.108) (0.108) (0.097)
t1 * Log pc livestock -0.004 -0.003 -0.004
(0.013) (0.011) (0.010)
t1 * Food insecurity 0.000 -0.002 0.002
(0.010) (0.010) (0.009)
t1 * Associates office (d) -0.022 0.000 -0.010
(0.050) (0.046) (0.041)
Time-varying village fixed effects Yes Yes Yes Yes Yes Yes
Pseudo/Adj R2
0.268 0.269 0.173 0.174
Observations 1532 1532 1352 1352 1532 1532
LL -774.581 -773.444 -1455.746 -1442.621
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 21 / 22

22. Conclusions
Amount of FA
Two-Part OLS SUR Two-Part OLS Tobit
(1) (2) (3) (4) (5) (6)
Log household size 0.207*** 0.364*** 0.023 0.129 -0.013 -0.024
(0.080) (0.107) (0.091) (0.143) (0.099) (0.128)
Share of elders 0.020 -0.287 0.887*** 1.062*** 0.630*** 0.581*
(0.152) (0.231) (0.213) (0.348) (0.218) (0.296)
Female head (d) 0.020 0.029 0.093 0.110 0.056 0.029
(0.063) (0.082) (0.079) (0.127) (0.085) (0.107)
Head primary education (d) -0.057 -0.090 0.121 0.151 0.019 -0.052
(0.084) (0.122) (0.087) (0.169) (0.100) (0.133)
Age head -0.000 0.002 0.008*** 0.006 0.007** 0.004
(0.002) (0.003) (0.003) (0.004) (0.003) (0.004)
Hh head died (d) -0.046 -0.155 -0.219 -0.263 -0.181 -0.130
(0.128) (0.181) (0.157) (0.247) (0.159) (0.197)
Log lagged pc livestock value 0.001 0.002 -0.012 -0.016 -0.035** -0.023
(0.012) (0.014) (0.016) (0.024) (0.018) (0.022)
Food insecurity 0.004 0.006 -0.003 -0.008 0.005 0.012
(0.012) (0.020) (0.016) (0.028) (0.016) (0.022)
Associates office (d) -0.061 -0.020 0.064 0.114 0.134* 0.156
(0.054) (0.077) (0.073) (0.107) (0.074) (0.098)
t1 (d) 0.452*** 1.222*** 0.313* 0.682 0.362* -0.103
(0.156) (0.421) (0.178) (0.519) (0.210) (0.744)
t1 * Share of elders 0.520 -0.317 0.194
(0.318) (0.462) (0.208)
t1 * Female head (d) -0.012 -0.037 0.091
(0.127) (0.174) (0.093)
t1 * Head died (d) 0.278 0.132 -0.231*
(0.258) (0.314) (0.130)
t1 * Log pc livestock -0.004 0.011 0.005
(0.023) (0.031) (0.015)
t1 * Food insecurity -0.003 0.006 0.005
(0.024) (0.033) (0.014)
t1 * Associates office (d) -0.082 -0.115 -0.030
(0.108) (0.133) (0.069)
Constant 1.085*** 0.658** 1.352*** 1.058**
(0.217) (0.277) (0.376) (0.464)
Time-varying village fixed effects Yes Yes Yes Yes Yes Yes
Pseudo/Adj R2
0.416 0.420 0.259 0.263 0.085 0.129
Observations 660 660 1045 1045 1352 1352
Elsa Valli (University of Sussex) Targeting of aid in rural Ethiopia March 20, 2017 22 / 22