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Defaults, denials, and discrimination in mortgage lending

Author

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  • Geoffrey M. B. Tootell

Abstract

The results of the study of discrimination in mortgage lending by Munnell, Browne, McEneaney, and Tootell (1992) have been questioned by some who claim that the authors failed to control adequately for the expected profitability of each loan. Critics assert that an examination of default rates for minorities and whites would explain the disparate treatment minorities received in obtaining mortgage loans. ; This article will demonstrate that studies of denials are a valid approach to testing for discrimination and that, in fact, examination of defaults cannot, in general, reveal much about the issue. Since studies of defaults leave out the observations that are most important to the examination of discrimination, denied applications, they cannot compare the profitability of rejected minority applications to accepted white ones. Only by including these observations, as is done in studies of denials, can definitive evidence about discrimination be found.

Suggested Citation

  • Geoffrey M. B. Tootell, 1993. "Defaults, denials, and discrimination in mortgage lending," New England Economic Review, Federal Reserve Bank of Boston, issue Sep, pages 45-51.
    • Handle: RePEc:fip:fedbne:y:1993:i:sep:p:45-51
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    File URL: http://www.bostonfed.org/economic/neer/neer1993/neer593d.pdf
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    Citations

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    Cited by:

    1. Douglas D. Evanoff & Lewis M. Segal, 1996. "CRA and fair lending regulations: resulting trends in mortgage lending," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 20(Nov), pages 19-46.
    2. Block, Walter & Snow, Nicholas & Stringham, Edward, 2008. "Banks, insurance companies, and discrimination," MPRA Paper 26035, University Library of Munich, Germany.
    3. Geoffrey M. B. Tootell, 1996. "Can studies of application denials and mortgage defaults uncover taste-based discrimination?," Working Papers 96-10, Federal Reserve Bank of Boston.
    4. Stanley D. Longhofer & Stephen R. Peters, 1998. "Beneath the rhetoric: clarifying the debate on mortgage lending discrimination," Economic Review, Federal Reserve Bank of Cleveland, vol. 34(Q IV), pages 2-13.
    5. Fidel Ezeala-Harrison & Glenda Glover & Jane Shaw-Jackson, 2008. "Housing Loan Patterns Toward Minority Borrowers in Mississippi: Analysis of Some Micro Data Evidence of Redlining," The Review of Black Political Economy, Springer;National Economic Association, vol. 35(1), pages 43-54, March.
    6. Dawkins, Mark C., 2002. "Simultaneity bias in mortgage lending: A test of simultaneous equations models on bank-specific data," Journal of Banking & Finance, Elsevier, vol. 26(8), pages 1593-1613, August.
    7. Stanley D. Longhofer & Stephen R. Peters, 1998. "Self-selection and discrimination in credit markets," Working Papers (Old Series) 9809, Federal Reserve Bank of Cleveland.
    8. Helen F. Ladd, 1998. "Evidence on Discrimination in Mortgage Lending," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 41-62, Spring.
    9. Paul S. Calem & Stanley D. Longhofer, 2000. "Anatomy of a fair-lending exam: the uses and limitations of statistics," Working Papers (Old Series) 0003R, Federal Reserve Bank of Cleveland.
    10. Song Han, 2001. "On the Economics of Discrimination in Credit Markets," Finance and Economics Discussion Series 2002-02, Board of Governors of the Federal Reserve System (U.S.).
    11. Song Han, 2004. "Discrimination in Lending: Theory and Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 29(1), pages 5-46, July.
    12. Judith Robinson, 2002. "Race, Gender, and Familial Status: Discrimination in One US Mortgage Lending Market," Feminist Economics, Taylor & Francis Journals, vol. 8(2), pages 63-85.
    13. Paul S. Calem & Stanley D. Longhofer, 2000. "Anatomy of a fair-lending exam: the uses and limitations of statistics," Finance and Economics Discussion Series 2000-15, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    Keywords

    Mortgages;

    Statistics

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