does agricultural and food aid reduce child stunting? an … · 2017. 12. 21. · stunting...
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S É B A S T I E N M A R YD E P A U L U N I V E R S I T Y , D E P A R T M E N T O F E C O N O M I C S , C H I C A G O , U S A
K E L S E Y S H A W
C O H E R E N T E C O N O M I C S , H I G H L A N D P A R K , U S A
L I E S B E T H C O L E E N , S E R G I O G O M E Z Y P A L O M AE U R O P E A N C O M M I S S I O N , J O I N T R E S E A R C H C E N T R E , S E V I L L E , S P A I N
“ Q U A N T I T A T I V E M E T H O D S F O R I N T E G R A T E D F O O D A N D N U T R I T I O N S E C U R I T Y M E A S U R E M E N T S – L E S S O N S T O B E L E A R N E D ! ”
B R U S S E L S , N O V . 1 5 - 1 7 2 0 1 7
Does Agricultural And Food Aid Reduce Child Stunting?
The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an officialposition of the European Commission.
Outline
Context
Agriculture/Nutrition
Evidence base
Approach
Results
Conclusions
Context
155 million stunted children FAO, IFAD, UNICEF, WFP and WHO. 2017. The State of Food
Security and Nutrition in the World 2017. Building resilience for peace and food security. Rome, FAO.
Sustainable Development Goal 2.2:
“By 2030, end all forms of malnutrition, includingachieving, by 2025, the internationally agreed targetson stunting […] in children under 5 years of age […]”
2025 target: A 40 percent reduction in the number ofchildren under 5 years who are stunted
‘Making agriculture work for nutrition’
Relative role of agriculture in food security strategies Strong conceptual links though potentially offsetting impacts
Aggregate level Agricultural growth increases food expenditures, decreases food
prices and raises rural incomes (Johnston and Mellor, 1961; Mellor, 1976)
Household level Higher production, consumption, marketed output, incomes, higher
social economic and social access for women to farm production and food allocation (World Bank, 2007; FAO, 2011)
Evidence base: macro
Empirical evidence on the role of agriculture
Agricultural growth
Webb and Block 2012; Headey 2013; Mary, Shaw and Gomez y Paloma 2017
Inconsistent results
Impacts
Agricultural growth vs. non-agricultural growth
Evidence base: micro
Evidence of positive impacts of agricultural interventions on nutrition is scarce
Arimond et al., 2011; Girard et al., 2012; Masset et al., 2012; DFID, 2014; Webb and Kennedy, 2015
“The question this systematic review set out to answer was “howeffective are the agricultural interventions that aim to improve thenutritional status of children?” We have concluded that we cannotanswer this question with any confidence.”
- MASSET ET AL., 2012
Why?
“say more about weak methodology rather than it does about the true effect of interventions” (Masset et al., 2012)
Poor design, external validity, lack of power
Literature review
7239 studies, 307 and then 23
Implementing the SDG agenda
Implemented through food security strategies Supported by increased aid inflows
‘Evidence-base’ policy How to design efficient policies?
Rethinking the role of agriculture (Dercon, 2013) Priority? Place for nutrition-specific/nutrition-sensitive?
Development aid strategy Implicit sectoral allocation of resources
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Figure 3. Share of sector aid (% total aid)
Agricultural aid Food Aid
Approach
Assess the impacts of aid earmarked for agriculture on stunting prevalence
Useful and necessary complement to microeconomic case studies and RCTs
Cross-country regressions Appropriate given the paucity of the microeconomic evidence base Accounts for wider sectoral and economy wide feedbacks and
externalities Answers the question:
“does agricultural aid reduce child undernutrition overall?”
Model
Underlying’ model
Inclusion of food aid
Endogeneity (‘Good Samaritan’) Aid directed at failing countries
Dynamic panel (SGMM) or traditional IV. Does it make sense?
Extend a recent strategy (Bruckner, 2013)
𝑆𝑖𝑡 = 𝛽ln(𝐴𝐴𝐼𝐷𝑖𝑡) + 𝛼ln(𝐹𝐴𝐼𝐷𝑖𝑡) + 휃𝑥𝑖𝑡 + 𝜇𝑖 + 휀𝑖𝑡 (1)
Two-step estimation
1. First step 1.1 Effect of stunting on aid: 2SLS-IV
ln(𝐴𝐴𝐼𝐷𝑖𝑡) = 휁𝑆𝑖𝑡 + 휂ln (𝐹𝐴𝐼𝐷𝑖𝑡) + 𝛿𝑥𝑖𝑡 + 𝜌𝑖 + 𝜑𝑖𝑡
ln(𝐹𝐴𝐼𝐷𝑖𝑡) = 𝜆𝑆𝑖𝑡 + 𝜅ln(𝐴𝐴𝐼𝐷𝑖𝑡) + 𝜏𝑥𝑖𝑡 + 𝜚𝑖 + 𝜒𝑖𝑡
1.2 Create residual used as IV for second step
ln(𝐴𝐴𝐼𝐷𝑖𝑡∗ ) = ln(𝐴𝐴𝐼𝐷𝑖𝑡) − 휁𝑆𝑖𝑡 + 휂ln(𝐹𝐴𝐼𝐷𝑖𝑡) + 𝛿𝑥𝑖𝑡 + 𝜌𝑖
ln(𝐹𝐴𝐼𝐷𝑖𝑡∗ ) = ln(𝐹𝐴𝐼𝐷𝑖𝑡) − 𝜆𝑆𝑖𝑡 + 𝜅ln(𝐴𝐼𝐷𝑖𝑡) + 𝜏𝑥𝑖𝑡 + 𝜚𝑖
2. Second step: effect of aid on stunting: 2SLS-IV
IV approach in the first step
Temperature anomalies as IV in the first step
Supply shocks to food production that affect nutrition and aid as a response to increased undernutrition
Why? Because stunting is not chronic. Substantial catch up possible after 24 mo. (Prentice et al., 2013; Prendergast and Humphrey, 2014)
Exclusion restriction
Temperature anomalies affect aid only through stunting (plausible and test)
Data
Sample: 90 developing countries between 2002-2014
Table 1. Descriptive statistics of the estimation sample
Variables (Unit) Mean Std. dev. Min Max
Child stunting prevalence 28.66 13.31 1.20 57.70
(% of children under five)
Agricultural aid per capita 2.06 2.45 0.00 21.13
(US dollars constant 2013)
Food aid per capita 1.05 1.85 0.00 12.46
(US dollars constant 2013)
Temperature deviation 0.001 0.17 -2.10 1.48
(Yearly deviation from long run level)
Quadratic term 0.03 0.30 0.00 4.43
Access to sanitation (%) 56.53 28.10 8.20 99.00
(% population with access to improved sanitation facilities)
Access to water (%) 78.59 15.74 29.50 99.90
(% population with access to water sources)
Sources: WHO, CRU of EA, OECD-CRS, WDI-WB
Results: 1. Effect of stunting on aid
Table 2.The effect of child stunting prevalence on agricultural and food aid
(1) (2) (3) (4)
First-stage 2SLS First-stage 2SLS
Dependent variable: Stunting Agricultural aid Stunting Food aid
Child stunting prevalence
0.012
0.073**
[0.51]
[0.02]
Food aid per capita, log 0.248 -0.083
(0.35) (-0.93)
Agricultural aid per capita, log
0.481 -0.098
(0.58) (-0.98)
Access to sanitation -0.404*** -0.011 -0.402*** 0.007
(-2.60) (-0.71) (-2.60) (0.37)
Access to water -0.145 -0.001 -0.137 0.026
(-1.07) (-0.16) (-1.01) (1.58)
Temperature deviation 4.859*
5.260**
(1.97)
(2.28)
Quadratic term 9.289***
9.765***
(2.99)
(3.35)
Observations
283
283
Number of countries
90
90
Country FE
YES
YES
Year FE
YES
YES
Hansen J, p-value
0.99
0.37
First-stage, F-stat
43.25
42.97
Stock-Yogo 10% maximal size
19.93
19.93
Stock-Yogo 15% maximal size
11.59
11.59
Stock-Yogo 20% maximal size
8.75
8.75
Notes: Robust z-statistics in parentheses. Anderson-Rubin p-values between square brackets. *** p<0.01, **
p<0.05, * p<0.10, # p<0.15
Results: 2. Effect of aid on stunting
Table 3.The effect of aid inflows on child stunting prevalence
(1) (2) (3)
Child stunting prevalence IV-2SLS CUE OLS-FE
Food aid per capita, log -5.924*** -6.499*** 0.794
(-3.45) (-3.50) (1.19)
Agricultural aid per capita, log -1.444# -1.521# -0.586
(-1.49) (-1.51) (-0.88)
Access to water -0.469*** -0.468*** -0.471***
(-3.06) (-2.97) (-3.96)
Access to sanitation -0.625*** -0.637*** -0.513***
(-3.65) (-3.64) (-3.37)
Temperature deviation 12.719*** 13.40***
(3.70) (3.59)
Quadratic term 19.28*** 20.149***
(4.40) (4.23)
Observations 283 283 283
Country FE YES YES YES
Year FE NO NO NO
Number of countries 90 90 90
Kleibergen-Paap statistic 135.68 111.47 n.a.
Ramsey RESET test, GMM 0.18 0.17 0.61
Notes: Robust z-statistics in parentheses. *** p<0.01, ** p<0.05, * p<0.10, # p<0.15
Agricultural aid decomposed
Table 4. The effect of aid inflows on child stunting prevalence: sub-sectoral decomposition
IV-2SLS
Child stunting prevalence (1) (2) (3) (4) (5)
Food aid, per capita, log -5.492*** -6.619*** -5.708*** -6.753*** -5.752***
(-3.24) (-3.73) (-3.39) (-3.76) (-3.23)
Access to water -0.503*** -0.434*** -0.487*** -0.392** -0.408**
(-3.22) (-2.77) (-3.14) (-2.06) (-2.56)
Access to sanitation -0.632*** -0.704*** -0.624*** -0.594*** -0.644***
(-3.83) (-4.32) (-3.71) (-2.99) (-3.86)
Temperature shock 11.899*** 14.985*** 12.147*** 16.479*** 14.527***
(3.36) (4.40) (3.38) (5.08) (4.48)
Quadratic term 18.377*** 22.297*** 18.575*** 24.290*** 21.816***
(4.06) (5.11) (4.06) (5.85) (5.31)
Agricultural aid per capita, log
Input -1.839
(-0.64)
Education, research and services
-29.926***
(-3.45)
Production
-0.954
(-1.03)
Water
-8.483***
(-3.54)
Policy
-6.948***
(-3.83)
Observations 283 283 283 283 283
Number of countries 90 90 90 90 90
Country FE YES YES YES YES YES
Year FE NO NO NO NO NO
Notes: Robust z-statistics in parentheses. *** p<0.01, ** p<0.05, * p<0.10, # p<0.15
Summary
Positive reverse causality for food aid (bias spreads to agricultural coefficient)
A 10% increase in agricultural aid per capita would decrease stunting prevalence by 0.5%
A 10% increase in food aid per capita would decrease stunting prevalence by 2.1%
Agricultural education, research and services; water; policy
Robustness analyses Range of estimates for agricultural aid: 0.3-1.3%; and for food aid: 0.3-2.6% Medium-run impacts: 0.8% for agricultural aid and 4.5% for food aid
Conclusions
Continue the support to agricultural aid
Reallocation within agricultural aid
Reallocation of sector aid away from food aid?
Does it fit with SDG objective?
