The Regulation in Private Health Care Market in Brazil: The Effects in Moral Hazard and Adverse Selection

Abstract

INTRODUCTION: The Brazilian private health insurance sector has operated since 1940’s without regulation. In 1998, the Brazilian Government stating the regulation of this sector. The reform improved the health insurance coverage level, stating no limit to physician visits and proibition to cream selection.

OBJECTIVE: We aim at evaluating whether private health insured individuals have exhibited changes in their behavior on medical services consumption, it is whether the regulation augmented the moral hazard in this market. We also evaluated the effects the regulation in demand to health insurance.

METHODS: We used three econometric methods to count data: Poisson Regression, Negative Binomial Regression and Count Data Quantile Regression. Also we used the Probit regression. The data come from the National Household Survey Sample (Pesquisa Nacional de Amostra de Domicilios-PNAD) for 1998 (before regulation) and 2003 (after regulation). The estimator of difference-in-difference (diff-in-diff) are used to estimate the impact of regulation.

RESULTS: The results showed that before and after regulation there are moral hazard in health insurance. The dummy variable diff-in-diff (year*regulation) was negative and significative stastistically suggesting its that after regulation the physician visits is lower than before. The results of Probit regression showed that after regulation there are adverse selection, since the number of chronical diseases variable after regulation is positive and significative statistically.

CONCLUSION: The results this paper apponted that after the regulation there are two important problems in Brazilian private health insurance: adverse selection and moral hazard. Only after regulation there are adverse selection.These problems can may generate inefficient outcomes in Brazilian private health insurance market.

Keywords: health insurance, theory of regulation, moral hazard, adverse selection, count quantile regression,

JEL Classification: I11, I18