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

Chang-Chih Chen () and Chia-Chien Chang ()
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Chang-Chih Chen: Jiangxi Normal University
Chia-Chien Chang: National Kaohsiung University of Applied Science

The Journal of Real Estate Finance and Economics, 2019, vol. 58, issue 1, No 6, 133-157

Abstract: 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 on 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; G1; G2 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11146-016-9569-9

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