Statistical Evidence of Mortgage Redlining? A Cautionary Tale
AbstractStatistical analyses of mortgage redlining at the neighborhood level have fueled the debate over the existence of racial redlining in mortgage lending, both "proving" and "disproving" that redlining exists, depending upon the type of model used. In this paper, we compare results of different statistical models using data for the Washington, DC metropolitan area to determine their usefulness in providing statistical evidence on this issue. After demonstrating the sensitivity of single-equation models to specification error, we estimate a simultaneous equations model of mortgage credit flows. This model makes it possible to analyze differences in the supply and demand for mortgage credit by the racial composition of the community. We conclude that most, if not all, statistical evidence of racial redlining based on aggregate loan data is at best inconclusive, and more likely, misleading.
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Bibliographic InfoArticle provided by American Real Estate Society in its journal Journal of Real Estate Research.
Volume (Year): 11 (1996)
Issue (Month): 1 ()
Contact details of provider:
Postal: American Real Estate Society Clemson University School of Business & Behavioral Science Department of Finance 401 Sirrine Hall Clemson, SC 29634-1323
Web page: http://www.aresnet.org/
Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323
Find related papers by JEL classification:
- L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services
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- Anthony M.J. Yezer & Robert F. Phillips & Robert P. Trost, 1994.
"Bias in estimates of discrimination and default in mortgage lending: the effects of simultaneity and self-selection,"
Federal Reserve Bank of Philadelphia, pages 197-222.
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- Alicia H. Munnell, 1992.
"Mortgage lending in Boston: interpreting HMDA data,"
92-7, Federal Reserve Bank of Boston.
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- Harrison, David M., 2001. "The Importance of Lender Heterogeneity in Mortgage Lending," Journal of Urban Economics, Elsevier, vol. 49(2), pages 285-309, March.
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