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Do Lenders Still Discriminate? A Robust Approach for Assessing Differences in Menus / David Hao Zhang, Paul S. Willen.

NBER Working papers Available online

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Format:
Book
Author/Creator:
Zhang, David Hao.
Contributor:
National Bureau of Economic Research.
Willen, Paul S.
Series:
Working Paper Series (National Bureau of Economic Research) no. w29142.
NBER working paper series no. w29142
Language:
English
Physical Description:
1 online resource: illustrations (black and white);
Place of Publication:
Cambridge, Mass. National Bureau of Economic Research 2021.
Summary:
Motivated by the assessment of racial discrimination in mortgage pricing, we introduce a new methodology for comparing the menus of options borrowers face based on their choices. First, we show how standard regression-based approaches for assessing discrimination in the menus context can lead to misleading and contradictory results. Second, we propose a new methodology that is robust these problems based on relatively weak economic assumptions. More specifically, we use pairwise dominance relationships in choices supplemented by restrictions on the range of plausible menus to define (1) a test statistic for equality in menus and (2) a difference in menus (DIM) metric for assessing whether one group of borrowers would prefer to switch to another group's menus. Our statistics are robust to arbitrary heterogeneity in borrower preferences across racial groups, are sharp in terms of identification, and can be efficiently computed using Optimal Transport methods. Third, we devise a new approach for inference on the value of Optimal Transport problems based on directional differentiation. Fourth, we use our methodology to estimate mortgage pricing differentials by race on a novel data set linking 2018--2019 Home Mortgage Disclosure Act (HMDA) data to Optimal Blue rate locks. We find robust evidence for mortgage pricing differentials by race, particularly among Conforming mortgage borrowers who are relatively creditworthy.
Notes:
Print version record
August 2021.

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