Ambiguity Types, Robust Learning and Natural Catastrophe Insurance: How Long-Term Contracts May Help

38 Pages Posted: 20 Jul 2012 Last revised: 28 May 2016

See all articles by Wenge Zhu

Wenge Zhu

Shanghai University of Finance and Economics

Howard Kunreuther

University of Pennsylvania - Operations, Information and Decisions Department; National Bureau of Economic Research (NBER)

Erwann Michel-Kerjan

University of Pennsylvania - The Wharton School - Center for Risk Management

Date Written: July 19, 2012

Abstract

Motivated by the results of the field experiment in the United Sates to distinguish two sources of ambiguity and its relation with the robust learning theory, we propose an insurance pricing formula to accommodate the ambiguity types in the robust learning framework. Based on the field experiment results and the data of the yield spread of catastrophe linked securities as well as their expected loss, our empirical test separates the magnitudes of different types of ambiguity aversion over different times for different periods. A related four-period model is then established to discuss long-term insurance (LTI) as an alternative to the standard annual insurance policy.

Keywords: Ambiguity Types, Robust Learning, Insurance Pricing, Esscher Transform, LTI

JEL Classification: C93, D81, D83

Suggested Citation

Zhu, Wenge and Kunreuther, Howard C. and Michel-Kerjan, Erwann, Ambiguity Types, Robust Learning and Natural Catastrophe Insurance: How Long-Term Contracts May Help (July 19, 2012). Available at SSRN: https://ssrn.com/abstract=2113828 or http://dx.doi.org/10.2139/ssrn.2113828

Wenge Zhu (Contact Author)

Shanghai University of Finance and Economics ( email )

AK Shanghai

Howard C. Kunreuther

University of Pennsylvania - Operations, Information and Decisions Department ( email )

3730 Walnut Street
558 & 559 Jon M. Huntsman Hall
Philadelphia, PA 19104-5340
United States
212-854-0423 (Phone)
215-573-2130 (Fax)

National Bureau of Economic Research (NBER)

Erwann Michel-Kerjan

University of Pennsylvania - The Wharton School - Center for Risk Management ( email )

Jon M Huntsman Hall, Suite 500
3730 Walnut Street
Philadelphia, PA 19104-6365
United States

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