Separating Moral Hazard from Adverse Selection in Automobile Insurance: Longitudinal Evidence from France

This paper uses longitudinal data to perform tests of asymmetric information in the French automobile insurance market for the 1995-1997 period. This market is characterized by the presence of a regulated experience-rating scheme (bonus-malus). We demonstrate that the result of the test depends crucially on how the dynamic process between insurance claims and contract choice is modelled. We apply a Granger causality test controlling for the unobservables. We find evidence of moral hazard which we distinguish from adverse selection using a multivariate dynamic panel data model. Experience rating appears to lead high risk policyholders to choose contracts that involve less coverage over time. These policyholders respond to contract changes by increasing their unobservable efforts to reduce claims.Automobile insurance, road safety, asymmetric information, experience rating, moral hazard, adverse selection, dynamic panel data models, Granger causality test

Separating Moral Hazard from Adverse Selection and Learning in Automobile Insurance: Longitudinal Evidence from France

The identification of information problems in different markets is a challenging issue in the economic literature. In this paper, we study the identification of moral hazard from adverse selection and learning within the context of a multi-period dynamic model. We extend the model of Abbring et al. (2003) to include learning and insurance coverage choice over time. We derive testable empirical implications for panel data. We then perform tests using longitudinal data from France during the period 1995-1997. We find evidence of moral hazard among a sub-group of policyholders with less driving experience (less than 15 years). Policyholders with less than 5 years of experience have a combination of learning and moral hazard, whereas no residual information problem is found for policyholders with more than 15 years of experience.Moral hazard, adverse selection, learning, dynamic insurance contracting, panel data, empirical test