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Employer Credit Checks: Poverty Traps versus Matching Efficiency

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  • Dean Corbae
  • Andrew Glover

Abstract

We develop a framework to understand the effects of pre-employment credit screening in both labor and credit markets. People differ in both their propensity to default on debt and the profits they create for firms that employ them. In our calibrated economy, workers with a low default probability are highly productive and therefore generate more profits for their employers; thus, firms create more jobs for those with good credit. However, using credit reports to screen job applicants creates a poverty trap: an unemployed worker with poor credit has a low job-finding rate and cannot improve their credit without a job. In the calibrated economy, this manifests as an endogenous loss in the present value of lifetime wages that is roughly half of the amount widely used in quantitative models of consumer default. Banning employer credit checks eliminates the poverty trap, but job seekers with good and bad credit now apply to the same jobs, which reduces matching efficiency. As a result, average job-finding rates fall 1.3 percent for high-productivity workers and rise by 1.7 percent for low-productivity workers.

Suggested Citation

  • Dean Corbae & Andrew Glover, 2023. "Employer Credit Checks: Poverty Traps versus Matching Efficiency," Research Working Paper RWP 23-01, Federal Reserve Bank of Kansas City.
  • Handle: RePEc:fip:fedkrw:95644
    DOI: 10.18651/RWP2023-01
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    Cited by:

    1. Gajendran Raveendranathan & Georgios Stefanidis, 2020. "The Unprecedented Fall in U.S. Revolving Credit," Department of Economics Working Papers 2020-05, McMaster University.
    2. Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," NBER Working Papers 26165, National Bureau of Economic Research, Inc.
    3. Satyajit Chatterjee & Dean Corbae & Kyle Dempsey & José‐Víctor Ríos‐Rull, 2023. "A Quantitative Theory of the Credit Score," Econometrica, Econometric Society, vol. 91(5), pages 1803-1840, September.
    4. Kristle R. Cortes & Andrew Glover & Murat Tasci, 2022. "The Unintended Consequences of Employer Credit Check Bans for Labor Markets," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 997-1009, December.
    5. Exler, Florian & Tertilt, Michèle, 2020. "Consumer Debt and Default: A Macro Perspective," IZA Discussion Papers 12966, Institute of Labor Economics (IZA).
    6. Stefania Albanesi & Domonkos F. Vamossy, 2024. "Credit Scores: Performance and Equity," Papers 2409.00296, arXiv.org.
    7. Tertilt, Michèle & Exler, Florian & Livshits, Igor & MacGee, Jim, 2020. "Consumer Credit with Over-Optimistic Borrowers," CEPR Discussion Papers 15570, C.E.P.R. Discussion Papers.
    8. Tertilt, Michèle & Exler, Florian, 2020. "Consumer Debt and Default: A Macroeconomic Perspective," CEPR Discussion Papers 14425, C.E.P.R. Discussion Papers.
    9. Laura Blattner & Scott Nelson, 2021. "How Costly is Noise? Data and Disparities in Consumer Credit," Papers 2105.07554, arXiv.org.

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    More about this item

    Keywords

    pre-employment credit screening; consumer default; adverse selection; credit;
    All these keywords.

    JEL classification:

    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

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