• Media type: E-Book
  • Title: Using High-Frequency Evaluations to Estimate Discrimination : Evidence from Mortgage Loan Officers
  • Contributor: Giacoletti, Marco [VerfasserIn]; Heimer, Rawley [VerfasserIn]; Yu, Edison G. [VerfasserIn]
  • imprint: [S.l.]: SSRN, [2021]
  • Published in: Proceedings of Paris December 2021 Finance Meeting EUROFIDAI - ESSEC
  • Extent: 1 Online-Ressource (71 p)
  • Language: English
  • DOI: 10.2139/ssrn.3795547
  • Identifier:
  • Keywords: Performance Incentives ; Lending Discrimination ; Loan Officers ; Mortgages ; Shadow Banking
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments July 20, 2021 erstellt
  • Description: 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
  • Access State: Open Access