Academic journal article Journal of Risk and Insurance

Asymmetric Information in the Market for Automobile Insurance: Evidence from Germany

Academic journal article Journal of Risk and Insurance

Asymmetric Information in the Market for Automobile Insurance: Evidence from Germany

Article excerpt


Asymmetric information is an important phenomenon in insurance markets, but the empirical evidence on the extent of adverse selection and moral hazard is mixed. Because of its implications for pricing, contract design, and regulation, it is crucial to test for asymmetric information in specific insurance markets. In this article, we analyze a recent data set on automobile insurance in Germany, the largest such market in Europe. We present and compare a variety of statistical testing procedures. We find that the extent of asymmetric information depends on coverage levels and on the specific risks covered, which enhances the previous literature. Within the framework of Chiappori et al. (2006), we also test whether drivers have realistic expectations concerning their loss distribution, and we analyze the market structure.


Since Akerlof (1970), the consequences of asymmetric information, in particular, adverse selection and moral hazard, have been explored in a vast body of research. The initial gap between the theoretical developments and empirical studies of asymmetric information has recently become narrower. In particular, insurance markets have proved a fruitful and productive field for empirical studies, for two reasons. First, the data are well structured: insurance contracts are usually highly standardized, they can be described completely by a relatively small set of variables, and data on the insured person's claim history, that is, the occurrence of claims and the associated costs, are stored in the database of an insurance company. Second, insurance companies have hundreds of thousands or even millions of clients and therefore the samples are sufficiently large to conduct powerful statistical tests. The markets for automobile insurance, annuities and life insurance, crop insurance, as well as long-term care and health insurance provide large samples of standardized contracts for which performances are recorded and are well suited for testing the theoretical predictions of insurance theory. Chiappori and Salanie (1997) provide a detailed justification for using insurance data to test contract theory. Cohen and Siegelman (2010) present a comprehensive overview of approaches for testing for adverse selection in insurance markets, covering a large number of empirical studies in different insurance branches.

In statistical terms, the notion of asymmetric information implies a positive (conditional) correlation between coverage and risk. Several different methods that explain how to test for asymmetric information have been proposed in the literature. In this article, we apply an array of such tests to detailed contract-level data from the German car insurance market.

Our study contributes to the existing literature in several respects. First, we present the first study analyzing the German car insurance market. The German car insurance market is the largest in Europe and therefore for many insurance companies the most important sales market for their insurance policies. We had unique access to the data set of one of the largest insurance companies in the field of automobile insurance in Germany.

Second, the empirical literature has reached an almost complete consensus that asymmetric information is not prevalent in automobile insurance concerning coverage choices (e.g., deductible level). (1) Our analysis shows that this finding does not hold in general; in particular, we show that the institutional arrangements of a market and the structure of the contracts have a great influence on whether the insureds have an informational advantage that the can possibly exploit. Because of a special arrangement that holds in the car insurance in Germany, we can show that the extent of asymmetric information depends on the specific kinds of risks that are covered.

Third, we compare several tests for asymmetric information that have been proposed in the literature. …

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