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 Africa’s 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?

• Improve current economic vulnerability to food insecurity?

• Increase food consumption?

• Improve diet quality?

Summary

Does the Malawi Social Cash Transfer Program (SCTP) have an impact on household food and nutrition security?

• Improve current economic vulnerability to food insecurity?

‒ Yes, weak evidence

• Less likely to worry about having enough food

• Increase expenditures on food

• Decrease food share

Summary

Does the Malawi Social Cash Transfer Program (SCTP) have an impact on household food and nutrition security?

• Increase food consumption?

‒ Yes, strong evidence

• More likely to have ≥2 meals/day

• Consume more calories

• Less likely to be food energy deficient

• Smaller hunger deficit

Summary

Does the Malawi Social Cash Transfer Program (SCTP) have an impact on household food and nutrition security?

• Improve diet quality?

‒ No evidence

Theory of Change

Engel’s Law

• As income increases, household decreases its budget share of food

Bennett’s Law

• As income increases, households reduce food budget share of starchy staples and substitute toward fruits, vegetables, dairy, and meat

Poor households

• Higher expenditure elasticity for food

• Higher marginal utility for calories

Theory of Change

Our study households are the most destitute and vulnerable

Expectations

• Choose a diet which maximizes caloric content

• Majority of food budget devoted to staple foods

• After meeting a critical caloric quantity threshold, shift to foods with improved caloric quality

Caveat

• Baseline data collected post-harvest

• Midline data collected during lean-season

Empirical Approach: Outcome Measures

Current Economic Vulnerability• Worried not enough food during past week• Annualized real p.c. food expenditures (MWK Aug ‘13)• Food share

Diet Quantity• Consumed ≥ 2 meals/day• P.C. daily energy acquisition• Food energy deficient • Hunger Depth

Diet Quality • Household Diet Diversity Score (HDDS)• Proportion food energy from staples• Expenditures – 5 food groups• Food share – 5 food groups

Empirical Approach: Diff-in-Diff w/ GLM Models

Basic Model

𝑌𝑗𝑘𝑡 = 𝑔 𝛽0 + 𝛽1𝑇𝑅𝐸𝐴𝑇𝑘 + 𝛽2𝑇𝐼𝑀𝐸 + 𝜷𝟑 𝑇𝑅𝐸𝐴𝑇𝑘 ∗ 𝑇𝐼𝑀𝐸 + 𝛽4𝑋𝑗𝑘𝑡 + 𝜀𝑗𝑘𝑡

Heterogeneous Model

𝑌𝑗𝑘𝑡 = 𝑔𝛽0 + 𝛽1𝑇𝑅𝐸𝐴𝑇𝑘 + 𝛽2𝑇𝐼𝑀𝐸 + 𝛽3 𝑇𝑅𝐸𝐴𝑇𝑘 ∗ 𝑇𝐼𝑀𝐸 + 𝛽4𝑋𝑗𝑘𝑡 + 𝛽5𝑀𝑂𝐷𝑗𝑘

+ 𝛽6 𝑇𝑅𝐸𝐴𝑇𝑘 ∗ 𝑀𝑂𝐷𝑗𝑘 + 𝛽7 𝑇𝐼𝑀𝐸 ∗ 𝑀𝑂𝐷𝑗𝑘 + 𝜷𝟖 𝑇𝑅𝐸𝐴𝑇𝑘 ∗ 𝑇𝐼𝑀𝐸 ∗ 𝑀𝑂𝐷𝑗𝑘+ 𝜀𝑗𝑘𝑡

Transfer Share Model

𝑌𝑗𝑘𝑡 = 𝑔𝛼0 + 𝛼1𝑇𝑅𝐸𝐴𝑇𝑘 + 𝛼2𝑇𝐼𝑀𝐸 + 𝛼3𝑇𝑋𝑆𝐻𝑅𝑘 + 𝜶𝟒 𝑇𝑅𝐸𝐴𝑇𝑘 ∗ 𝑇𝐼𝑀𝐸 + 𝛼5 𝑇𝑅𝐸𝐴𝑇𝑘 ∗ 𝑇𝑋𝑆𝐻𝑅𝑘+ 𝛼6 𝑇𝐼𝑀𝐸 ∗ 𝑇𝑋𝑆𝐻𝑅𝑘 + 𝜶𝟕 𝑇𝑅𝐸𝐴𝑇𝑘 ∗ 𝑇𝐼𝑀𝐸 ∗ 𝑇𝑋𝑆𝐻𝑅𝑘 + 𝛼8𝑋𝑗𝑘𝑡

+ 𝜀𝑗𝑘𝑡

Empirical Approach: Study Sample

N = 3,163 households (94% of panel)• 1,479 Treatment

• 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

• Heterogeneous impacts by baseline poverty level for p.c. food exp. and food share

• Impacts on worried about food and p.c. food exp. significant among households with child 0-17

• Differential impact on p.c. food exp. by transfer share

Results: Diet Quantity

Outcome Impact Baseline MeanT Hhld

Midline MeanC Hhld

Midline Mean

≥ 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

• Heterogeneous impacts by baseline poverty level and distance to the market for ≥ 2 meals/day

• Results very similar among households with children

• 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.

Thank you

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