Proposed modified probit model incorporating non-parametric density estimation: how to measure asymmetric information in the health insurance market?

Abstract

On the basis of the theory of Chiappori and Salanie (2000), this paper proposes a simple modified bivariate Probit model incorporating non-parametric kernel density estimation. The model is applied to test asymmetric information in a health insurance market, using MEPS96 data.1 Results show that asymmetric information (whether moral hazard or adverse selection) exists between the contract of insurance coverage, and some non-emergency visits services, which appear to support the conclusions of Cardon and Hendel (2001). It is also shown how this non-parametric approach plays an important role in the delicate task of correctly testing, by computing generalized residuals, the existence of asymmetric information.