Using High-Frequency Evaluations to Estimate Disparate Treatment: Evidence from Mortgage Loan Officers

73 Pages Posted: 2 Mar 2021 Last revised: 5 Mar 2025

See all articles by Marco Giacoletti

Marco Giacoletti

Marshall School of Business

Rawley Heimer

Arizona State University (ASU) - W.P. Carey School of Business

Edison G. Yu

Federal Reserve Bank of Philadelphia

Date Written: March 01, 2025

Abstract

We examine the Black mortgage approval gap in the U.S., leveraging confidential HMDA data to uncover a novel pattern: The approval gap, 2.4 percentage points to start the month, reduces to approximately zero at month’s end. Exploring mechanisms, underperforming loan officers and lending institutions with more performance-induced turnover amplify the within-month approval gap decrease. Demand-side factors, such as borrower financial constraints, also increase month-end origination volume but explain less than half of the Black approval gap reduction. Our findings emphasize the role of commercial incentives in reducing disparate treatment, aligning with Becker’s “costs of discrimination” theory (1957).

Keywords: Performance Incentives, Lending Discrimination, Loan Officers, Mortgages, Shadow Banking

Suggested Citation

Giacoletti, Marco and Heimer, Rawley and Yu, Edison G., Using High-Frequency Evaluations to Estimate Disparate Treatment: Evidence from Mortgage Loan Officers (March 01, 2025). Available at SSRN: https://ssrn.com/abstract=3795547 or http://dx.doi.org/10.2139/ssrn.3795547

Marco Giacoletti

Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA California 90089
United States

Rawley Heimer

Arizona State University (ASU) - W.P. Carey School of Business ( email )

Tempe, AZ 85287-3706
United States

Edison G. Yu (Contact Author)

Federal Reserve Bank of Philadelphia ( email )

Ten Independence Mall
Philadelphia, PA 19106-1574
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
656
Abstract Views
2,733
Rank
86,097
PlumX Metrics