RFS Advance Access originally published online on January 29, 2007
Review of Financial Studies 2008 21(6):2677-2703; doi:10.1093/revfin/hhm005
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Monopoly and Information Advantage in the Residential Mortgage Market
Hong Kong University of Science and Technology
University of Wisconsin—Madison
Send correspondence to Jie Gan, School of Business and Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong. E-mail: jgan{at}ust.hk
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Abstract |
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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.
We wish to thank for helpful comments: Brent Ambrose, Harold Bunce, Charles Calomiris, Kalok Chan, Sudipto Dasgupta, Theresa DiVenti, Scott Frame, Jed Frees, John Gardner, Don Hausch, Dwight Jaffee, Michael LaCour-Little, François Ortalo-Magné, David Rodda, William Segal, Kunal Sengupta, Chester Spatt, Skander Van den Heuvel, Robert Van Order, Wen Zhou, two anonymous HUD-sponsored reviewers, seminar participants at OFHEO, Simon Fraser University, the University of Southern California, and the University of Wisconsin–Madison, and conference participants at the 2004 American Finance Association meetings and the 2004 Financial Intermediation Research Society conference. We are particularly grateful to two anonymous referees and the editor, Matthew Spiegel, whose comments and suggestions have substantially improved the article. Finally, special thanks go to Brent Ambrose and Anthony Pennington-Cross, who shared their data with us and ran some of the regressions. Gan acknowledges financial support from the Hong Kong RGC Research Grant (HKUST6280/04H) and both authors acknowledge financial support from the Department of Housing and Urban Development.