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

Authors


  • Martin Spindler is at the Max Planck Institute for Social Law and Social Policy, Munich, Germany. Joachim Winter is at the University of Munich, Economics Department, Munich, Germany. Steffen Hagmayer, is at the HUK Coburg Insurance Group, Coburg, Germany. The authors can be contacted via e-mail: spindler@mea.mpisoc.mpg.de, joachim.winter@lrz.unimuenchen.de, andsteffen.hagmayer@huk-coburg.de. Martin Spindler gratefully acknowledges financial support from the Deutsche Forschungsgemeinschaft through GRK 801 and in particular from The Geneva Association through a research grant. We thank Bernard Salanié and Andreas Richter for valuable comments and discussions, and Thomas Yee for assistance in applying the R package VGAM.We are grateful to participants of the EEA/ESEM annual meeting 2011 in Oslo, of the annual conference of the German Economic Association (VfS) 2011 in Frankfurt am Main and of the annual seminar of the EGRIE 2011 in Vienna. Parts of this paper were written while Martin Spindler was visiting Columbia University, which he thanks for its hospitality. We thank Editors Georges Dionne and Keith Crocker and an anonymous reviewer for valuable comments that helped to improve the paper.

Abstract

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.

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