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On the robustness of racial discrimination findings in mortgage lending studies

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  • Judith Clarke
  • Nilanjana Roy
  • Marsha Courchane

Abstract

That mortgage lenders have complex underwriting standards, often differing legitimately from one lender to another, implies that any statistical model estimated to approximate these standards, for use in fair lending determinations, must be misspecified. Exploration of the sensitivity of disparate treatment findings from such statistical models is, thus, imperative. We contribute to this goal. This article examines whether the conclusions from several bank-specific studies, undertaken by the Office of the Comptroller of the Currency, are robust to changes in the link function adopted to model the probability of loan approval and to the approach used to approximate the finite sample null distribution for the disparate treatment hypothesis test. Our evidence, of discrimination findings that are reasonably robust to the range of examined link functions, suggests that regulators and researchers can be reasonably comfortable with their current use of the logit link. Based on several features of our results, we advocate regular use of a resampling method to determine p-values.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 41 (2009)
Issue (Month): 18 ()
Pages: 2279-2297

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Handle: RePEc:taf:applec:v:41:y:2009:i:18:p:2279-2297

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  1. Jason Dietrich, 2005. "Under-specified Models and Detection of Discrimination: A Case Study of Mortgage Lending," The Journal of Real Estate Finance and Economics, Springer, vol. 31(1), pages 83-105, August.
  2. Day, Theodore E & Liebowitz, S J, 1998. "Mortgage Lending to Minorities: Where's the Bias?," Economic Inquiry, Western Economic Association International, vol. 36(1), pages 3-28, January.
  3. Alicia H. Munnell, 1992. "Mortgage lending in Boston: interpreting HMDA data," Working Papers 92-7, Federal Reserve Bank of Boston.
  4. Russell Davidson & James MacKinnon, 2000. "Bootstrap tests: how many bootstraps?," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 55-68.
  5. Stephen L. Ross & John Yinger, 2002. "The Color of Credit: Mortgage Discrimination, Research Methodology, and Fair-Lending Enforcement," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262182289, December.
  6. Mitchell Stengel & Dennis Glennon, 1999. "Evaluating Statistical Models of Mortgage Lending Discrimination: A Bank-Specific Analysis," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 27(2), pages 299-334.
  7. Harrison, Glenn W, 1998. "Mortgage Lending in Boston: A Reconsideration of the Evidence," Economic Inquiry, Western Economic Association International, vol. 36(1), pages 29-38, January.
  8. J. Neuhaus, 2002. "The analysis of retrospective family studies," Biometrika, Biometrika Trust, vol. 89(1), pages 23-37, March.
  9. Cosslett, Stephen R, 1981. "Maximum Likelihood Estimator for Choice-Based Samples," Econometrica, Econometric Society, vol. 49(5), pages 1289-1316, September.
  10. J.S. Cramer, 1998. "Predictive Performance of the Binary Logit Model in Unbalanced Samples," Tinbergen Institute Discussion Papers 98-085/4, Tinbergen Institute.
  11. Judith Clarke & Marsha Courchane, 2004. "Implications of Stratified Sampling for Fair Lending Binary Logit Models," The Journal of Real Estate Finance and Economics, Springer, vol. 30(1), pages 5-31, October.
  12. Lynn Elaine Browne & Geoffrey M.B. Tootell, 1995. "Mortgage lending in Boston: a response to the critics," New England Economic Review, Federal Reserve Bank of Boston, issue Sep, pages 53-78.
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Cited by:
  1. Anupam Nanda & Stephen L. Ross, 2008. "The Impact of Property Condition Disclosure Laws on Housing Prices: Evidence from an Event Study using Propensity Scores," Working papers 2008-39, University of Connecticut, Department of Economics.

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