Abstract #301719

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JSM 2003 Abstract #301719
Activity Number: 4
Type: Invited
Date/Time: Sunday, August 3, 2003 : 2:00 PM to 3:50 PM
Sponsor: Business & Economics Statistics Section
Abstract - #301719
Title: A Test of Discrimination Robust to Functional Misspecification
Author(s): Douglas A. McManus*+ and Marsha Courchane
Companies: Freddie Mac and Welch Consulting
Address: 8200 Jones Branch Dr., MS-484, McLean, VA, 22102,
Keywords: fair lending testing ; misspecification ; econometrics
Abstract:

It is important for both legal and policy reasons to have an objective, empirically based standard for testing the presence of discrimination. A key difficulty in developing such a test is that we are forced to specify aspects of the model such as functional form and error distribution for computational ease and typically without an empirical basis. Such ad hoc aspects of the specification result in inference that is conditional on the model, meaning that the rejection of equal treatment is typically valid only if the underlying model is correctly specified. Thus the effects of model misspecification can mask differential treatment or can result in the appearance of differential treatment when there is no intrinsic difference in the treatment of two populations. To address this limitation of existing tests of discrimination, this paper develops a test for discrimination that remains valid under a very wide range of functional misspecifications.

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