Date post: | 11-Feb-2017 |
Category: |
Government & Nonprofit |
Upload: | transferprojct |
View: | 283 times |
Download: | 1 times |
Impacts of an Unconditional Cash Transfer on Household Food and Nutrition Security in Malawi
Kristen Brugh,1
Gustavo Angeles,1 Peter Mvula,2 & Maxton Tsoka2
Giving Cash to the Poor? Impacts of Africaβs Unconditional Cash Transfers
APPAM 2015 Fall Research Conference
The Malawi SCTP Evaluation Team1 University of North Carolina at Chapel Hill
2 Centre for Social Research, University of Malawi
Research Questions
Does the Malawi Social Cash Transfer Program (SCTP) have an impact on household food and nutrition security?
β’ Improve current economic vulnerability to food insecurity?
β’ Increase food consumption?
β’ Improve diet quality?
Summary
Does the Malawi Social Cash Transfer Program (SCTP) have an impact on household food and nutrition security?
β’ Improve current economic vulnerability to food insecurity?
β Yes, weak evidence
β’ Less likely to worry about having enough food
β’ Increase expenditures on food
β’ Decrease food share
Summary
Does the Malawi Social Cash Transfer Program (SCTP) have an impact on household food and nutrition security?
β’ Increase food consumption?
β Yes, strong evidence
β’ More likely to have β₯2 meals/day
β’ Consume more calories
β’ Less likely to be food energy deficient
β’ Smaller hunger deficit
Summary
Does the Malawi Social Cash Transfer Program (SCTP) have an impact on household food and nutrition security?
β’ Improve diet quality?
β No evidence
Theory of Change
Engelβs Law
β’ As income increases, household decreases its budget share of food
Bennettβs Law
β’ As income increases, households reduce food budget share of starchy staples and substitute toward fruits, vegetables, dairy, and meat
Poor households
β’ Higher expenditure elasticity for food
β’ Higher marginal utility for calories
Theory of Change
Our study households are the most destitute and vulnerable
Expectations
β’ Choose a diet which maximizes caloric content
β’ Majority of food budget devoted to staple foods
β’ After meeting a critical caloric quantity threshold, shift to foods with improved caloric quality
Caveat
β’ Baseline data collected post-harvest
β’ Midline data collected during lean-season
Empirical Approach: Outcome Measures
Current Economic Vulnerabilityβ’ Worried not enough food during past weekβ’ Annualized real p.c. food expenditures (MWK Aug β13)β’ Food share
Diet Quantityβ’ Consumed β₯ 2 meals/dayβ’ P.C. daily energy acquisitionβ’ Food energy deficient β’ Hunger Depth
Diet Quality β’ Household Diet Diversity Score (HDDS)β’ Proportion food energy from staplesβ’ Expenditures β 5 food groupsβ’ Food share β 5 food groups
Empirical Approach: Diff-in-Diff w/ GLM Models
Basic Model
ππππ‘ = π π½0 + π½1ππ πΈπ΄ππ + π½2ππΌππΈ + π·π ππ πΈπ΄ππ β ππΌππΈ + π½4ππππ‘ + ππππ‘
Heterogeneous Model
ππππ‘ = ππ½0 + π½1ππ πΈπ΄ππ + π½2ππΌππΈ + π½3 ππ πΈπ΄ππ β ππΌππΈ + π½4ππππ‘ + π½5πππ·ππ
+ π½6 ππ πΈπ΄ππ β πππ·ππ + π½7 ππΌππΈ β πππ·ππ + π·π ππ πΈπ΄ππ β ππΌππΈ β πππ·ππ+ ππππ‘
Transfer Share Model
ππππ‘ = ππΌ0 + πΌ1ππ πΈπ΄ππ + πΌ2ππΌππΈ + πΌ3ππππ»π π + πΆπ ππ πΈπ΄ππ β ππΌππΈ + πΌ5 ππ πΈπ΄ππ β ππππ»π π+ πΌ6 ππΌππΈ β ππππ»π π + πΆπ ππ πΈπ΄ππ β ππΌππΈ β ππππ»π π + πΌ8ππππ‘
+ ππππ‘
Empirical Approach: Study Sample
N = 3,163 households (94% of panel)β’ 1,479 Treatment
β’ 1,682 Delayed-Entry Control
Treatment and Control balanced at baseline
No evidence of selective or differential attrition
Results: Current Economic Vulnerability
Outcome Impact Baseline MeanT Hhld
Midline MeanC Hhld
Midline Mean
Worried about food -0.11+ 0.84 0.77 0.88
PC food exp. 4,303+ 34,016 27,711 24,516
Food share -0.02*** 0.80 0.74 0.77
Notes: Average Marginal Effects. + p<0.10; *p<0.05; **p<0.01; ***p<0.001
β’ Heterogeneous impacts by baseline poverty level for p.c. food exp. and food share
β’ Impacts on worried about food and p.c. food exp. significant among households with child 0-17
β’ Differential impact on p.c. food exp. by transfer share
Results: Diet Quantity
Outcome Impact Baseline MeanT Hhld
Midline MeanC Hhld
Midline Mean
β₯ 2 meals/day 0.11+ 0.80 0.94 0.87
Daily PC Kcal 325*** 1,770 1,657 1,489
Energy Deficient -0.12*** 0.64 0.68 0.76
Hunger Depth -179*** 554 534 653
Notes: Average Marginal Effects. + p<0.10; *p<0.05; **p<0.01; ***p<0.001
β’ Heterogeneous impacts by baseline poverty level and distance to the market for β₯ 2 meals/day
β’ Results very similar among households with children
β’ Differential impact on daily p.c. Kcal by transfer share
Results: Diet Quality
Outcome Impact Baseline MeanT Hhld
Midline MeanC Hhld
Midline Mean
HDDS 0.51 5.61 5.78 5.31
Proportion staples -0.01 0.83 0.81 0.82
Exp. Cereal 1,759*** 18,838 12,839 11,857
Exp. Fruit/Veg 559 5,504 7,094 6,535
Exp. Meat 838 2,512 3,474 2,886
Exp. Legumes 345 4,250 2,269 1,687
Exp. Other 1,247+ 2,912 2,034 1,552
Shr. Cereal -0.01 0.57 0.48 0.50
Shr. Fruit/Veg -0.01 0.19 0.26 0.27
Shr. Meat 0.01 0.05 0.12 0.11
Shr. Legumes -0.01 0.12 0.07 0.06
Shr. Other 0.02 0.08 0.07 0.06
Notes: Average Marginal Effects. + p<0.10; *p<0.05; **p<0.01; ***p<0.001
Results: Relative Impacts
20%
12%
35%
PC FOOD EXP.
31%
54%
14%
68%
50% 48%
PC KCAL*** HUNGER DEPTH
Total Low Tx Share High Tx Share
Current Economic Vulnerability Diet Quantity
Conclusions
Small program impact on current economic vulnerability to food insecurity.
Strong protective program impact on diet quantity during the lean season.
No evidence of program impact on diet quality.
After one year of program exposure, treatment households attempted to increase diet quantity
rather than improve diet quality.
SCT and IHS3-Rural Ultra Poor: Still fewer of working-age
12 10 8 6 4 2 0 2 4 6 8 10 12
<5
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80+
Percent
SCT Eligible Population by Age and Sex
(N = 16,078)
Male Female
12 10 8 6 4 2 0 2 4 6 8 10 12
Percent
IHS3 Rural Ultra-Poor Population by Age and
Sex (N = 12,750)
Male Female