On the robustness of racial discrimination findings in mortgage lending studies
Judith Clarke (),
Nilanjana Roy and
Marsha Courchane ()
Applied Economics, 2009, vol. 41, issue 18, 2279-2297
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.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
Working Paper: On the Robustness of Racial Discrimination Findings in Mortgage Lending Studies (2005)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:41:y:2009:i:18:p:2279-2297
Ordering information: This journal article can be ordered from
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().