Can Conditional Cash Transfer Programs Improve Social Risk Management? Lessons for Education and Child Labor Outcomes

This paper explores the role of Conditional Cash Transfer (CCT) programs in serving as a risk management instrument for the poor. Using various rounds of panel data from the successful CCT Progresa program in Mexico, the impact analysis indicates a number of interesting patterns. First, strong state dependence indicates that children taken out of school (partly due to shocks) are less likely to subsequently return, implying long-term consequences from short-term decisions. Nonetheless, the CCT program seems to mitigate this state dependence. Second, a number of shocks - such as unemployment or illness of the household head or younger children, droughts, natural disasters in the community and loss of land, harvest, or animals - have strong effects on children’s schooling attainment, indicating that that children are used as risk coping instruments. While this creates short run consumption smoothing gains for the household, such coping strategy implies long-term losses in human capital for children that are accentuated by state dependence. Again, the impact evaluation analysis shows that the Progresa transfers compensate for these shocks, protecting child schooling from a range of shocks. Finally, while the shocks reported also seem to induce children to work - particularly girls and children of farm workers when their parents are affected by unemployment -, the impact evaluation suggests that Progresa transfers and the conditionality on school attendance serve to deter using child labor as a risk coping strategy. Despite the fact that CCT are not designed to deal directly with shocks or serve as “insurance” instruments per se, these results clearly indicate that they can provide an important safety net role by protecting child education from a range of idiosyncratic and covariate shocks. Such findings also imply that incorporating risk exposure and shock incidence criteria in the design of such programs’ eligibility rules, or allowing additional flexibility in terms of scaling up or down such interventions to address large covariate or idiosyncratic shocks is a potentially worthwhile direction and use of such programs.