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

Author

Listed:
  • Georges Dionne
  • Pierre-Carl Michaud
  • Maki Dahchour

Abstract

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.

Suggested Citation

  • Georges Dionne & Pierre-Carl Michaud & Maki Dahchour, 2010. "Separating Moral Hazard from Adverse Selection and Learning in Automobile Insurance: Longitudinal Evidence from France," Cahiers de recherche 1035, CIRPEE.
  • Handle: RePEc:lvl:lacicr:1035
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    References listed on IDEAS

    as
    1. Dionne, Georges & Doherty, Neil A, 1994. "Adverse Selection, Commitment, and Renegotiation: Extension to and Evidence from Insurance Markets," Journal of Political Economy, University of Chicago Press, vol. 102(2), pages 209-235, April.
    2. Pierre‐André Chiappori & Bruno Jullien & Bernard Salanié & François Salanié, 2006. "Asymmetric information in insurance: general testable implications," RAND Journal of Economics, RAND Corporation, vol. 37(4), pages 783-798, December.
    3. Chiappori, Pierre-Andre & Durand, Franck & Geoffard, Pierre-Yves, 1998. "Moral hazard and the demand for physician services: First lessons from a French natural experiment," European Economic Review, Elsevier, vol. 42(3-5), pages 499-511, May.
    4. Puelz, Robert & Snow, Arthur, 1994. "Evidence on Adverse Selection: Equilibrium Signaling and Cross-Subsidization in the Insurance Market," Journal of Political Economy, University of Chicago Press, vol. 102(2), pages 236-257, April.
    5. Jaap Abbring & Pierre-André Chiappori & Tibor Zavadil, 2008. "Better Safe than Sorry? Ex Ante and Ex Post Moral Hazard in Dynamic Insurance Data," Tinbergen Institute Discussion Papers 08-075/3, Tinbergen Institute.
    6. Amy Finkelstein & James Poterba, 2004. "Adverse Selection in Insurance Markets: Policyholder Evidence from the U.K. Annuity Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 183-208, February.
    7. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
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    11. Crocker, Keith J & Snow, Arthur, 1986. "The Efficiency Effects of Categorical Discrimination in the Insurance Industry," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 321-344, April.
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    14. Pierre-Andre Chiappori & Bernard Salanie, 2000. "Testing for Asymmetric Information in Insurance Markets," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 56-78, February.
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    17. Thomas de Garidel-Thoron, 2005. "Welfare-Improving Asymmetric Information in Dynamic Insurance Markets," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 121-150, February.
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    19. Hyojoung Kim & Doyoung Kim & Subin Im & James W. Hardin, 2009. "Evidence of Asymmetric Information in the Automobile Insurance Market: Dichotomous Versus Multinomial Measurement of Insurance Coverage," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(2), pages 343-366, June.
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    More about this item

    Keywords

    Moral hazard; adverse selection; learning; dynamic insurance contracting; panel data; empirical test;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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