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Do Lenders Still Discriminate? A Robust Approach for Assessing Differences in Menus

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  • David Hao Zhang
  • Paul S. Willen

Abstract

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.

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  • David Hao Zhang & Paul S. Willen, 2021. "Do Lenders Still Discriminate? A Robust Approach for Assessing Differences in Menus," NBER Working Papers 29142, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29142
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    Cited by:

    1. Bartlett, Robert & Morse, Adair & Stanton, Richard & Wallace, Nancy, 2022. "Consumer-lending discrimination in the FinTech Era," Journal of Financial Economics, Elsevier, vol. 143(1), pages 30-56.
    2. Nicholas Tenev, 2024. "De-Biasing Models of Biased Decisions: A Comparison of Methods Using Mortgage Application Data," Papers 2405.00910, arXiv.org.
    3. Laura Blattner & Scott Nelson, 2021. "How Costly is Noise? Data and Disparities in Consumer Credit," Papers 2105.07554, arXiv.org.
    4. Aliprantis, Dionissi & Carroll, Daniel R. & Young, Eric R., 2024. "What explains neighborhood sorting by income and race?," Journal of Urban Economics, Elsevier, vol. 141(C).
    5. Sean Lewis-Faupel & Nicholas Tenev, 2024. "Racial and Ethnic Disparities in Mortgage Lending: New Evidence from Expanded HMDA Data," Papers 2405.00895, arXiv.org.
    6. Neil Bhutta & Aurel Hizmo & Daniel R. Ringo, 2022. "How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions," Finance and Economics Discussion Series 2022-067, Board of Governors of the Federal Reserve System (U.S.).
    7. James Conklin & Kristopher Gerardi & Lauren Lambie-Hanson, 2022. "Can Everyone Tap Into the Housing Piggy Bank? Racial Disparities in Access to Home Equity," FRB Atlanta Working Paper 2022-17, Federal Reserve Bank of Atlanta.
    8. Hurtado, Agustin & Sakong, Jung, 2022. "The effect of minority bank ownership on minority credit," Working Papers 325, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth

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