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

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We use a new methodology to assess mortgage pricing discrimination faced by minority borrowers. We identify a “menu problem” that comes from the multidimensional nature of mortgage pricing: When getting a mortgage, borrowers can choose to avoid closing costs and pay a high interest rate or contribute to closing costs to get a lower rate. While data on both dimensions of mortgage pricing are by now often available, intuitively attractive metrics of lender pricing discrimination used in the literature can lead to both false and contradictory results. For example, it is sometimes observed that conditional on rate, minority borrowers pay the same closing costs as white borrowers, but conditional on closing costs, minority borrowers pay a higher rate. Though generally underappreciated, the menu problem is broadly relevant in economic assessments of differences in opportunity given data on outcomes. We develop a solution to the menu problem by defining (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, both based on pairwise dominance relationships in the data. Our proposed solution is robust to arbitrary heterogeneity in borrower preferences across racial groups. We show how our metrics can be computed using methods from optimal transport and also devise a new procedure for hypothesis testing in this class of problems based on directional differentiation. Finally, we implement our methodology on a data set linking 2018–2019 Home Mortgage Disclosure Act (HMDA) data to Optimal Blue rate locks, and present novel results on mortgage pricing discrimination.

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  • Paul S. Willen & David Hao Zhang, 2020. "Do Lenders Still Discriminate? A Robust Approach for Assessing Differences in Menus," Working Papers 20-19, Federal Reserve Bank of Boston.
  • Handle: RePEc:fip:fedbwp:89606
    DOI: 10.29412/res.wp.2020.19
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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

    Keywords

    mortgage pricing discrimination; minority borrowers; Home Mortgage Disclosure Act;
    All these keywords.

    JEL classification:

    • 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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