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Testing for Adverse Selection in Insurance Markets


Alma Cohen


Tel Aviv University - Eitan Berglas School of Economics; Harvard Law School; National Bureau of Economic Research (NBER)

Peter Siegelman


University of Connecticut - School of Law


Journal of Risk and Insurance, Vol. 77, Issue 1, pp. 39-84, March 2010

Abstract:     
This article reviews and evaluates the empirical literature on adverse selection in insurance markets. We focus on empirical work that seeks to test the basic coverage-risk prediction of adverse selection theory - that is, that policyholders who purchase more insurance coverage tend to be riskier. The analysis of this body of work, we argue, indicates that whether such a correlation exists varies across insurance markets and pools of insurance policies. We discuss various reasons why a coverage-risk correlation may not be found in some pools of insurance policies. The presence of a coverage-risk correlation can be explained either by moral hazard or adverse selection, and we discuss methods for distinguishing between them. Finally, we review the evidence on learning by policyholders and insurers.

Number of Pages in PDF File: 46

Accepted Paper Series


Date posted: February 8, 2010  

Suggested Citation

Cohen, Alma and Siegelman, Peter, Testing for Adverse Selection in Insurance Markets. Journal of Risk and Insurance, Vol. 77, Issue 1, pp. 39-84, March 2010. Available at SSRN: http://ssrn.com/abstract=1548165 or http://dx.doi.org/10.1111/j.1539-6975.2009.01337.x

Contact Information

Alma Cohen
Tel Aviv University - Eitan Berglas School of Economics ( email )
Ramat Aviv, Tel Aviv, 69978
Israel
Harvard Law School ( email )
Cambridge, MA 02138
United States
(617) 496-4099 (Phone)
(617) 812-0554 (Fax)
National Bureau of Economic Research (NBER) ( email )
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Peter Siegelman
University of Connecticut - School of Law ( email )
65 Elizabeth Street
Hartford, CT 06105
United States
860-570-5238 (Phone)
860-570-5242 (Fax)
Feedback to SSRN (Beta)


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