How Effective are Cash Transfer Programs at Improving Nutritional Status?

Conditional cash transfer programmes are a widely applied social protection scheme that has achieved successes in fighting poverty worldwide. A large literature has sprung up around these programmes, yet two questions remain. First, why do conditional cash transfer programmes show no consistent relationship with the nutritional status of recipient children? Second, conditionalities are expensive: to what extent is the conditional character of cash transfer programmes the reason for their success? To answer these questions, we reviewed the literature linking nutritional status to interventions involving cash transfers in developing countries. After surveying 30,000 articles we identified 19 such studies of 15 social assistance programmes and found that the weighted average impact of all estimates was very close to zero. To investigate the pathways behind success and failure we assembled data on a variety of study, programme, recipient, and country characteristics, and used statistical meta-analysis to investigate correlations between these covariates and estimated impacts. Our key findings include higher marginal effects in the most disadvantaged areas and that girls benefit more than boys. We find that in our sample, conditional programmes accomplish slightly less than unconditional programmes though the difference is not statistically significant. However, this hides an important dichotomy. Conditionalities with health components have a slightly lower effect than unconditional programmes but are statistically indistinguishable, while other types of requirements strongly inhibit growth. We also find higher marginal effects in countries with poorer health care systems. Because of the ambiguity and potential for both help and harm, we conclude that programme evaluation must be integrated into such interventions. One important outcome of our search is a list of evaluated programmes which can now be used as a starting point for future research qualitatively investigating causal pathways behind the broad correlations we have identified