Charles Vanasse

Testing for Evidence of Adverse Selection in the Automobile Insurance Market: A Comment

We analyze jointly the distribution of automobile accidents and the choice of deductible. One prediction in the literature is that high risk individuals will choose small deductibles within risk classes, when there is asymmetrical information. We show, however, that risk classification is sufficient, in the sense that there is no residual adverse selection on risk types in the automobile insurance portfolio studied.

A Generalization of Automobile Insurance Rating Models

The objective of this paper is to provide an extension of well-known models of tarification in automobile insurance. The analysis begins by introducing a regression component in the Poisson Model in order to use all available information in the estimation of the distribution. In a second step, a random variable is introduced in the regression component of the Poisson model and a negative binomial model with a regression component is derived. The authors then present their main contribution by proposing a bonus-malus system which integrates a priori and a posteriori information on an individual basis. They then show how a multivariate net premium tables can be derived from the model. Examples of tables are presented. (A)

Debt, moral hazard and airline safety An empirical evidence

Abstract For many years, there has been a proliferation of theoretical articles on ex-ante moral hazard without any strong empirical measure of its effect on resource allocation. In this article, we present a detailed analysis of the relationship between the financial structure of airlines and the private safety decisions of managers. We show that an increase in the debt-equity ratio is theoretically ambiguous on safety: there is a trade-off between efficiency in investment and moral hazard. All estimated models do not reject the Poisson distribution assumption. Many financial variables are significant when explaining the distribution of accidents. More particularly, our results indicate that the moral hazard effect on safety is dominated by the investment effect for carriers in good financial conditions, while the moral hazard effect dominates for those experiencing financial difficulties.

Evidence of Adverse Selection in Automobile Insurance Markets

In this paper, we propose an empirical analysis of the presence of adverse selection in an insurance market. We first present a theroetical model of a market with adverse selection and we introduce different issues related to transaction costs, accident costs, risk aversion and moral hazard. We then discuss an econometric modeling based on latent variables and we derive its relationship with specification in the portfolio of an insurer.

Econometric Models of Accident Distributions

This paper deals with the econometrics of car accidents, that is, the estimation of the relative importance or significance of the factors explaining the number of accidents in a given period on an individual basis. The number of car accidents is a discrete variable and, therefore, represents a count process: the dependent variable takes only nonnegative integer values. Hence, the observed dependent variable is the number of accidents an individual i had in the period considered. The individual characteristics are considered exogenous or predetermined and may or may not be significant factors in explaining the number of accidents. We have estimated four categorical models (linear probability, probit, logit, and multinomial logit) and four count data models (Poisson and negative binomial models with and without individual characteristics in the regression component). It is difficult to compare the econometric results of the different models since some of these models are not nested. However, it is shown that the negative binomial model with a regression component produces a reasonable approximation of the true distribution of accidents. Different statistical tests reject the Poisson models (with and without a regression component) and the negative binomial model without individual characteristics. It is also observed that all estimated models provide the same qualitative results (essentially the same significant variables), but differ when predictions of either the probabilities of accident or the expected number of accidents were made. For quantitative predictions, it is important to select the appropriate model. Moreover, it is shown that, in all models, the individual’s past driving experience is a good predictor of risk. Finally, we apply the statistical results to a model of insurance rating in the presence of moral hazard.

The Role of Memory in Long-Term Contracting with Moral Hazard: Empirical Evidence in Automobile Insurance

This paper tests the efficiency associated with the role of memory in long-term contracting. Bonus-malus schemes in automobile insurance are examples of contracts that use memory. During the eighties different contributors (Lambert, 1983, Rogerson, 1985, Boyer, and Dionne, 1989) showed how multi-period contracting under moral hazard improves resource allocation. In particular, it was demonstrated that multi-period contracts with memory outperform those without memory under full commitment.

Inferring technological parameters from incomplete panel data

This paper contributes to production economics by providing a procedure to estimate cost models with incomplete panel data and by illustrating how this procedure can be implemented using a panel data set of trucking firms. Most panel data sets of firms presently available are incomplete for numerous reasons, including mergers, acquisitions, bankruptcies, incomplete surveys, etc. Hence, in this type of sample, when a firm is missing for at least one period, all the variables relevant to this firm are missing for the same period. Our method jointly considers the cost-input demand system and a bivariate probit selection model of entry to and exit from the sample. Random firm-specific effects are included in both the cost and selection models. The inclusion of random effects in the models makes their joint estimation more delicate. However, some restrictions are imposed on the distribution of the random variables in order to simplify the analysis. For instance, we assume that the variances and covariances of the random variables are constant over time. The method is applied to an incomplete panel of Ontario (Canada) trucking firms. A test for selectivity bias on this panel reveals potential bias related to exit but not to entry. Estimation results indicate that the bias can be reduced and even eliminated with an appropriate specification of the cost model, at least for the sample used.

Point-record incentives, asymmetric information and dynamic data

Road safety policies often use incentive mechanisms based on traffic violations to promote safe driving. These mechanisms are both monetary (fines, insurance premiums) and nonmonetary (point-record driving licenses). We analyze the effectiveness of these mechanisms in promoting safe driving. We derive their theoretical properties with respect to contract time and accumulated demerit points. These properties are then tested empirically in a model which separates moral hazard from unobserved heterogeneity. We do not reject the presence of moral hazard in the Quebec public insurance regime. Moreover, we verify that the experience rating introduced in 1992 did reduce the frequency of traffic violations by 15%. Lastly, we compare the effectiveness of the different incentive schemes and we derive monetary equivalents for traffic violations and license suspensions.