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The measurement of the disparate impact of a particular de facto discriminatory policy on a minority or otherwise legally protected group has been of importance since passage of the Civil Rights Act of 1964. When the data available for the measurement of disparate impact, as embodied in the so-called “disparity ratio,” come from samples, a statistical approach naturally suggests itself. This article reviews both the law and statistics literature with regard to statistical inference applicable to the disparity ratio and related measures of disparate impact. From that review, three primary approaches are evaluated, the difference in so-called “rejection” rates for the protected and non-protected groups, their ratio (the disparity ratio), and the natural logarithm of the disparity ratio. For various reasons, the direct ratio estimator is recommended for use in all but small samples, where the log-ratio approach is to be preferred. The main points are illustrated with two fair housing examples, one being the possible discriminatory effect by race owing to a landlord’s refusal to accept Section 8 housing vouchers in lieu of cash rent, and the other being the effects of occupancy restrictions on families with children. Various methodological issues that arise in the application of these three estimation approaches are addressed in the context of the more complex sample designs that underlie the data utilized.

Statistical Approaches for Assessing Disparate Impact in Fair Housing Cases