Estimating Treatment Heterogeneity of International Monetary Fund Programs on Child Poverty with Generalized Random Forest

A flourishing group of scholars of family sociology study how macroeconomic shockwaves propagate via households dynamics and landing a blow on children’s living conditions; simultaneously, scholars of political economy unravel impacts of such shockwaves on population outcomes. Since these two strands of literature have evolved independently, little is know about the relative importance of societal and family features moderating this impact on children’s material living conditions. In this article, we synthesize insights from these two strands by examining the effect of economic austerity following International Monetary Fund programs—a type of economic shock—on child poverty across a sample representative of about half the world’s population of mainly the Global South. This article addresses the following fundamental sociological questions: to what extent do the pathways of economic austerity propagate through families’ living conditions and societies’ structural and political characteristics. To capture these multiple non-linear heterogeneous relationships between macro and micro traits, we deploy machine learning in the service of policy evaluation. First, our analysis identifies an adverse average treatment effect (ATE) following the implementation of IMF programs on children’s probability of falling into poverty: 0.14, 95% CI 0.03- 0.24. Second, our algorithms identify substantial impact heterogeneity distributed about this ATE. Macro constellation moderate about half of the impact variation on children, and families’ capabilities moderate the other half of this variation. We named this finding the 50-50 impact-moderation rule of thumb. Our algorithm identified family wealth closely followed by governments’ education spending as the critical moderating factors. IMF program affects children residing in the middle of the social stratification more than compared to their peers residing in both the top and bottom of this stratification; for those children residing in societies that have selected into IMF programs and have historically spent most on education, are at a higher risk of falling into poverty. These findings identify the value of combining family sociology and political economy perspectives. Scholars will likely cross-fertilize this research further by testing this 50-50 rule of thumb to other types of economic shocks.