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

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  • Chang-Chih Chen

    (Jiangxi Normal University)

  • Chia-Chien Chang

    (National Kaohsiung University of Applied Science)

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.

Suggested Citation

  • Chang-Chih Chen & Chia-Chien Chang, 2019. "How Big are the Ambiguity-Based Premiums on Mortgage Insurances?," The Journal of Real Estate Finance and Economics, Springer, vol. 58(1), pages 133-157, January.
    • Handle: RePEc:kap:jrefec:v:58:y:2019:i:1:d:10.1007_s11146-016-9569-9
    DOI: 10.1007/s11146-016-9569-9
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