This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

On the Robustness of Racial Discrimination Findings in Mortgage Lending Studies

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Judith A. Clarke () (Department of Economics, University of Victoria)
Marsha J. Courchane (ERS Group, Washington D.C.)
Nilanjana Roy () (Department of Economics, University of Victoria)

Additional information is available for the following registered author(s):

Abstract

The binary logistic regression or logit link model is commonly used to test for racial disparate treatment in fairlending studies undertaken by government agencies, including the Office of the Comptroller of the Currency (OCC) and the Federal Reserve Board (FRB). Ensuring race neutrality in lending remains a concern of regulators and consumer advocates. Improving the understanding of any shortcomings of either bank internal models or regulatory agency models will enable those participants in the mortgage industry to better serve the needs of consumers. We explore this issue using five bank studies undertaken by the OCC. We consider the impact of the logit link assumption, as this determines how race affects the likelihood of loan approval, by moving to three other links: probit, gompit and complementary log log; the latter two are examples of asymmetric links. As our data sets have been obtained using stratified sampling procedures, which has been typical at the OCC, rather than being drawn via simple random sampling, moving away from the logit link complicates estimation; it is no longer possible to use a standard estimation command with an adjustment for stratum effects. Our results reveal that the choice of link function, despite exhibiting similar sample fit, can influence findings of disparate treatment at the nominal level of significance commonly accepted as the legal standard. We also find that the use of a resampling method, which aims to better approximate the finite sample null distribution, for obtaining p-values typically leads to support for discrimination more often than arises from use of the standard normal approximation.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://web.uvic.ca/econ/ewp0516.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0516.

Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Length: 36 pages
Date of creation: 14 Oct 2005
Date of revision:
Handle: RePEc:vic:vicewp:0516

Note: ISSN 1485-6441
Contact details of provider:
Postal: PO Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2
Phone: (250)721-8540
Fax: (250)721-6214
Web page: http://web.uvic.ca/econ
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (David Giles).

Related research
Keywords: Logit Fair lending Stratified sampling Binary response Semi-parametric maximum likelihood Pseudo log-likelihood Profile log-likelihood Without replacement resampling Bootstrapping

Other versions of this item:

This paper has been announced in the following NEP Reports: References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Harrison, Glenn W, 1998. "Mortgage Lending in Boston: A Reconsideration of the Evidence," Economic Inquiry, Oxford University Press, vol. 36(1), pages 29-38, January.
  2. Russell Davidson & James G. MacKinnon, 2001. "Bootstrap Tests: How Many Bootstraps?," Working Papers 1036, Queen's University, Department of Economics. [Downloadable!]
    Other versions:
  3. 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. [Downloadable!] (restricted)
  4. Munnell, Alicia H. & Geoffrey M. B. Tootell & Lynn E. Browne & James McEneaney, 1996. "Mortgage Lending in Boston: Interpreting HMDA Data," American Economic Review, American Economic Association, vol. 86(1), pages 25-53, March.
    Other versions:
  5. 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. [Downloadable!] (restricted)
  6. 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. [Downloadable!]
  7. J. Neuhaus, 2002. "The analysis of retrospective family studies," Biometrika, Oxford University Press for Biometrika Trust, vol. 89(1), pages 23-37, March.
  8. Cosslett, Stephen R, 1981. "Maximum Likelihood Estimator for Choice-Based Samples," Econometrica, Econometric Society, vol. 49(5), pages 1289-1316, September. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? Springer Verlag was the first commercial publisher to be listed on RePEc.

This page was last updated on 2008-9-25.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.