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Asymmetric Learning in Repeated Contracting: An Empirical Study

Alma Cohen

The Review of Economics and Statistics, 2012, vol. 94, issue 2, 419-432

Abstract: This paper uses a unique panel data set of an insurer's transactions with repeat customers. Consistent with the asymmetric learning hypothesis that repeated contracting enables sellers to obtain an informational advantage over their rivals, I find that the insurer makes higher profits in transactions with repeat customers who have a good claims history with the insurer, the insurer reduces the price charged to these repeat customers by less than the reduction in expected costs associated with such customers, and repeat customers with bad claim histories are more likely to flee their record by switching to other insurers. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Keywords: repeat customers; asymmetric information; asymmetric learning; adverse selection; insurance; market power (search for similar items in EconPapers)
JEL-codes: D40 D80 D82 D83 G22 L10 (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (15)

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The Review of Economics and Statistics is currently edited by Pierre Azoulay, Olivier Coibion, Will Dobbie, Raymond Fisman, Benjamin R. Handel, Brian A. Jacob, Kareen Rozen, Xiaoxia Shi, Tavneet Suri and Yi Xu

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