The impact of subsidized health insurance for the poor: evaluating the Colombian experience using propensity score matching

Abstract

This paper evaluates the impact of Colombia's subsidized health insurance program (SUBS) on medical care utilization. Colombia's SUBS program is a demand-side subsidy intended for low-income families, where the screening of beneficiaries takes place in decentralized locations across the country. Due to the self-selection problems associated with non-experimental data, we implement Propensity Score Matching (PSM) methods to measure the impact of this subsidy on medical care utilization. By combining unique household survey data with community and regional data, we are able to compute propensity scores in a way that is consistent with both the local government's decision to offer the subsidy, and with the individual's decision to accept the subsidy. Although the application of PSM using these rich datasets helps to achieve a balance between the treatment and control groups along observable dimensions, we also present instrumental variable estimates to control for the potential endogeneity of program participation. Using both methods, we find that Colombia's subsidized insurance program greatly increased medical care utilization among the country's poor and uninsured. This evidence supports the case for other Latin American countries implementing similar subsidy programs for health insurance for the poor.