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Adverse selection and moral hazard in insurance: can dynamic data help to distinguish?

Author

Listed:
  • Jean Pinquet

    () (CECO - Laboratoire d'économétrie de l'École polytechnique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique)

  • Pierre-André Chiappori

    () (Department of Economics Columbia University - Columbia University [New York])

  • Jaap Abbring

    ()

  • James J Heckman

Abstract

A standard problem of applied contract theory is to empirically distinguish between adverse selection and moral hazard. We show that dynamic insurance data allows to distinguish moral hazard from dynamic selection on unobservables. In the presence of moral hazard, experience rating implies negative occurence dependence: individual intensities decrease with the number of past claims. We discuss econometric tests for the various type of data that are typically available. Finaly, we argue that dynamic data also allow to test for adverse selection, even if it is based on asymmetric learning.

Suggested Citation

  • Jean Pinquet & Pierre-André Chiappori & Jaap Abbring & James J Heckman, 2003. "Adverse selection and moral hazard in insurance: can dynamic data help to distinguish?," Post-Print hal-00397115, HAL.
  • Handle: RePEc:hal:journl:hal-00397115
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00397115
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    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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