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Monopoly and Information Advantage in the Residential Mortgage Market

Author

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  • Jie Gan
  • Timothy J. Riddiough

Abstract

Information advantage and entry deterrence incentives are investigated as they affect lending outcomes and competitive structure of the U.S. residential mortgage market. In the model, when assessing a loan applicant, the incumbent monopoly lender employs a proprietary screening technology to produce a privately observed estimate of loan credit quality. When faced with potential competitive entry, the incumbent signals poor credit quality by charging high prices to higher-quality borrowers. Market structure and loan pricing strategy are derived endogenously, where the incumbent deters entry first by segmenting consumers into prime and sub-prime loan markets and second by charging prime market borrowers a uniform rate that is higher than the risk-based monopoly rate. Empirical implications of the model are identified, and evidence is presented that is consistent with predictions. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org., Oxford University Press.

Suggested Citation

  • Jie Gan & Timothy J. Riddiough, 2008. "Monopoly and Information Advantage in the Residential Mortgage Market," The Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2677-2703, November.
    • Handle: RePEc:oup:rfinst:v:21:y:2008:i:6:p:2677-2703
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    File URL: http://hdl.handle.net/10.1093/revfin/hhm005
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    Cited by:

    1. Bo Liu & James D. Shilling & Tien Foo Sing, 2020. "Large Banks and Efficient Banks: how Do they Influence Credit Supply and Default Risk?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 57(1), pages 1-28, February.
    2. Cerqueiro, Geraldo & Degryse, Hans & Ongena, Steven, 2011. "Rules versus discretion in loan rate setting," Journal of Financial Intermediation, Elsevier, vol. 20(4), pages 503-529, October.
    3. Diego A. Restrepo-Tobón & Subal C. Kumbhakar, 2013. "Profit efficiency of U.S. commercial banks: a decomposition," Documentos de Trabajo de Valor Público 10939, Universidad EAFIT.
    4. Fasano, Francesco & Cappa, Francesco, 2022. "How do banking fintech services affect SME debt?," Journal of Economics and Business, Elsevier, vol. 121(C).
    5. Tim Zhang, 2022. "Uniform Mortgage Regulation and Distortion in Capital Allocation [Loan originations and defaults in the mortgage crisis: the role of the middle class]," Review of Finance, European Finance Association, vol. 26(4), pages 1011-1050.
    6. Ming Pu & Gang-Zhi Fan & Yongheng Deng, 2014. "Breakeven Determination of Loan Limits for Reverse Mortgages under Information Asymmetry," The Journal of Real Estate Finance and Economics, Springer, vol. 48(3), pages 492-521, April.
    7. Danny Ben-Shahar, 2008. "Default, Credit Scoring, and Loan-to-Value: a Theoretical Analysis under Competitive and Non-Competitive Mortgage Markets," Journal of Real Estate Research, American Real Estate Society, vol. 30(2), pages 161-190.
    8. Jesse M. Keenan & Jacob T. Bradt, 2020. "Underwaterwriting: from theory to empiricism in regional mortgage markets in the U.S," Climatic Change, Springer, vol. 162(4), pages 2043-2067, October.
    9. An, Xudong & Deng, Yongheng & Gabriel, Stuart A., 2011. "Asymmetric information, adverse selection, and the pricing of CMBS," Journal of Financial Economics, Elsevier, vol. 100(2), pages 304-325, May.
    10. Francesco Fasano & Tiziana Rocca, 2024. "Does the bank-firm human relationship still matter for SMEs? The game-changing role of digitalization," Small Business Economics, Springer, vol. 62(1), pages 159-178, January.
    11. Chavaz, Matthieu, 2016. "Dis-integrating credit markets: diversification, securitization, and lending in a recovery," Bank of England working papers 617, Bank of England.

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