On the robustness of racial discrimination findings in mortgage lending studies

That mortgage lenders have complex underwriting standards, often differing legitimately from one lender to another, implies that any statistical model estimated to approximate these standards, for use in fair lending determinations, must be misspecified. Exploration of the sensitivity of disparate treatment findings from such statistical models is, thus, imperative. We contribute to this goal. This article examines whether the conclusions from several bank-specific studies, undertaken by the Office of the Comptroller of the Currency, are robust to changes in the link function adopted to model the probability of loan approval and to the approach used to approximate the finite sample null distribution for the disparate treatment hypothesis test. Our evidence, of discrimination findings that are reasonably robust to the range of examined link functions, suggests that regulators and researchers can be reasonably comfortable with their current use of the logit link. Based on several features of our results, we advocate regular use of a resampling method to determine p-values.