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

Listed author(s):
  • Jean Pinquet

    ()

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

  • Pierre-André Chiappori

    ()

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

  • Jaap Abbring

    ()

  • James J Heckman

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.

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Paper provided by HAL in its series Post-Print with number hal-00397115.

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Date of creation: 19 Apr 2003
Publication status: Published in Journal of the European Economic Association, Wiley, 2003, 1 (2), pp.512-521
Handle: RePEc:hal:journl:hal-00397115
Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00397115
Contact details of provider: Web page: https://hal.archives-ouvertes.fr/

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