How Big are the Ambiguity-Based Premiums on Mortgage Insurance?

Journal of Real Estate Finance and Economics, Vol. 58(1), pages 133-157, 2019

Posted: 17 May 2019

See all articles by Chang-Chih Chen

Chang-Chih Chen

Wenlan school of Business at Zhongnan University of Economics and Law

Chia-Chien Chang

National Kaohsiung University of Applied Sciences

Date Written: April 17, 2019

Abstract

This paper studies how ambiguity aversion affects the pricing of mortgage insurance (MI). We consider pricing-kernel ambiguity arising from market incompleteness. This ambiguity model is applied to a standard framework of MI-ML (mortgage loan) structural pricing. Our quantitative results show that insurers' ambiguity aversion generates substantial positive effects of MI premium. Ambiguity impacts are highly sensitive to loan-to-value ratio, ambiguity magnitude, and the tightness of information constraints. By using the U.S. city-level housing and mortgage data, we estimate that, on average, ambiguity aversion increases MI premium rate by 77% (46 bps), and explains about 60%-90% of pricing errors.

Keywords: Ambiguity aversion; Mortgage insurance premium; Market incompleteness; Pricing kernel; Housing assets

JEL Classification: G1, G2

Suggested Citation

Chen, Chang-Chih and Chang, Chia-Chien, How Big are the Ambiguity-Based Premiums on Mortgage Insurance? (April 17, 2019). Journal of Real Estate Finance and Economics, Vol. 58(1), pages 133-157, 2019. Available at SSRN: https://ssrn.com/abstract=3373929

Chang-Chih Chen

Wenlan school of Business at Zhongnan University of Economics and Law ( email )

182# Nanhu Avenue, East Lake High-tech Development
Wuhan, Hubei 430073
China

Chia-Chien Chang (Contact Author)

National Kaohsiung University of Applied Sciences ( email )

Kaohsiung 80778
Taiwan

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