This paper uses count and binary data models with an endogenous dummy variable to evaluate the effect of the subsidized health care program in Medellin (Colombia). The subsidized program, which primarily covers poor people, is found to have a significant impact on the use of preventive medical care and hospitalization that might have a negative impact on the financial statements of the program. Specifically, econometric estimations of health care utilization indicate that there is both selection and moral hazard. These facts imply that the program can improve its coverage if mechanisms are created to lower the individual moral hazard effect.
Binary Models; Count Models; Endogenous Dummy Regression; Program Evaluation
