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On the Robustness of Racial Disrcimination Findings in Motgage Lending Studies

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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 paper examines whether 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. We find that discrimination findings are reasonably robust to the range of examined link functions, which supports the 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

Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0604.

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Length: 33 pages
Date of creation: 08 Sep 2006
Date of revision:
Handle: RePEc:vic:vicewp:0604

Note: ISSN 1485-6441
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Related research

Keywords: Logit; Mortgage lending discrimination; Fair lending; Stratified sampling; Binary response; Semiparametric maximum likelihood; Pseudo log-likelihood; Profile log-likelihood; Bootstrapping;

This paper has been announced in the following NEP Reports:

References

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  1. Jason Dietrich, 2005. "The effects of sampling strategies on the small sample properties of the logit estimator," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(6), pages 543-554.
  2. Blackburn, McKinley L. & Vermilyea, Todd, 2004. "Racial disparities in bank-specific mortgage lending models," Economics Letters, Elsevier, vol. 85(3), pages 379-383, December.
  3. 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.
  4. Russell Davidson & James G. MacKinnon, 2001. "Bootstrap Tests: How Many Bootstraps?," Working Papers 1036, Queen's University, Department of Economics.
  5. 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.
  6. J.S. Cramer, 1998. "Predictive Performance of the Binary Logit Model in Unbalanced Samples," Tinbergen Institute Discussion Papers 98-085/4, Tinbergen Institute.
  7. Kennedy, Peter E, 2002. " Sinning in the Basement: What Are the Rules? The Ten Commandments of Applied Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 16(4), pages 569-89, September.
  8. Calem, Paul S & Longhofer, Stanley D, 2002. "Anatomy of a Fair Lending Exam: The Uses and Limitations of Statistics," The Journal of Real Estate Finance and Economics, Springer, vol. 24(3), pages 207-37, May.
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