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Under-specified Models and Detection of Discrimination: A Case Study of Mortgage Lending

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Abstract

This study examines how omitted variables affect underwriting models the OCC estimates during fair lending examinations. The purpose is to assess the effects of omitted variable bias common to most studies of discrimination in mortgage lending. The results show omitted variables have an important impact on both the estimate of the effect of race and on the identification of outliers for review. Further, there appears to be no consistent patterns to the direction of these impacts. This suggests that it is inappropriate to make generalizations concerning the direction of bias based on assumptions about correlations between omitted variables and race.

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Authors and Affiliations

  1. Risk Analysis Division, Office of the Comptroller of the Currency, 250 E Street, S.W., Washington, D.C., 20219, USA

    Jason Dietrich

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  1. Jason Dietrich
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Correspondence to Jason Dietrich.

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Dietrich, J. Under-specified Models and Detection of Discrimination: A Case Study of Mortgage Lending. J Real Estate Finan Econ 31, 83–105 (2005). https://doi.org/10.1007/s11146-005-0995-3

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  • DOI: https://doi.org/10.1007/s11146-005-0995-3

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