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

Abstract

We develop tests for discrimination that we apply to 25 years of mortgage lending. Our tests limit the scope for omitted variables in a conventional benchmarking test by combining high-frequency mortgage evaluations with the notion that economic incentives can mitigate subjective biases. Loan officers have monthly volume quotas that constrain their subjectivity on loans processed at month-end. Concurrently, applicant characteristics are time-invariant within-month. We estimate that loan officers’ subjectivity contributes to at least half of the unexplained Black approval gap. The within-month approval gap is smaller for shadow banks, but not for FinTech lenders or banks in concentrated markets.