Title page
Contents
Abstract 1
1. Introduction 3
2. Data and Summary Statistics 9
2.1. Variable Construction and Harmonization for Analysis 10
2.2. Mexico's Progresa 11
2.3. Nicaragua's Red de Protección Program 12
2.4. The Philippines' Pantawid Program 13
2.5. Mexico's Programa de Apoyo Alimentario (PAL) 14
2.6. The World Food Program's Cash and Food Transfer in Uganda 14
2.7. Descriptive Statistics 15
3. Empirical Framework 15
3.1. Core Approach 16
3.2. Bayesian Aggregation 18
4. Results and Discussion 19
4.1. Core Results 19
4.2. Bayesian Aggregation 23
4.3. Nutrient Availability Impacts 24
5. Summary and Concluding Remarks 25
References 28
Appendix Figures and Tables 41
TABLE I. Overview of the five randomized controlled trials of conditional cash transfer programs included in the study, conducted in Mexico, Nicaragua,... 36
TABLE II. Mean weekly food consumption expenditure in the control group by program 37
TABLE III. Income elasticities of food demand estimated using a binary treatment indicator and pooled OLS on all five programs 38
TABLE IV. Impact of cash transfers on food consumption for the second and third quartiles of expenditure using pooled OLS on all five programs 39
TABLE V. Impact of cash transfers on food expenditure ratios (in natural log terms) using pooled OLS on all five programs 40
FIGURE I. Engel Curves for overall food demand pooling data from 5 conditional cash transfer programs in Mexico, Nicaragua, Philippines, and Uganda 34
FIGURE II. Protein share and overall food expenditures pooling data from 5 conditional cash transfer programs in Mexico, Nicaragua, Philippines, and Uganda 35
TABLE A1. Overview of food types surveyed and categorization in food groups by RCT 46
TABLE A2. Income elasticities of food demand and household-level nutrition impacts using a binary treatment indicator and pooled OLS on all five programs 47
FIGURE A1. Treatment effects on staples demand aggregated using Bayesian Hierarchical Modeling 41
FIGURE A2. Treatment effects on coarse staples demand aggregated using Bayesian Hierarchical Modeling 42
FIGURE A3. Treatment effects on fine staples demand aggregated using Bayesian Hierarchical Modeling 43
FIGURE A4. Treatment effects on protein demand aggregated using Bayesian Hierarchical Modeling 44
FIGURE A5. Treatment effects on vegetables and fruits demand aggregated using Bayesian Hierarchical Modeling 45