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Adverse Selection and Moral Hazard In Insurance: Can Dynamic Data Help to Distinguish? Author info | Abstract | Publisher info | Download info | Related research | Statistics Jaap H. Abbring (Free University,)
James J. Heckman (University of Chicago,)
Pierre-André Chiappori (University of Chicago,)
Jean Pinquet (Université Paris X-Nanterre,)
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A standard problem of applied contracts theory is to empirically distinguish between adverse selection and moral hazard. We show that dynamic insurance data allow to distinguish moral hazard from dynamic selection on unobservables. In the presence of moral hazard, experience rating implies negative occurrence dependence: individual claim intensities decrease with the number of past claims. We discuss econometric tests for the various types of data that are typically available. Finally, we argue that dynamic data also allow to test for adverse selection, even if it is based on asymmetric learning. (JEL: D82, G22, C41, C14) Copyright (c) 2003 The European Economic Association.
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Article provided by MIT Press in its journal Journal of the European Economic Association .
Volume (Year): 1 (2003)
Issue (Month): 2-3 (04/05)
Pages: 512-521
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Handle: RePEc:tpr:jeurec:v:1:y:2003:i:2-3:p:512-521Contact details of provider: Web page: http://www.mitpressjournals.org/jeea
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