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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 pre-employment credit screening through adverse selection in labor and credit markets. Workers differ in an unobservable characteristic that induces a positive correlation between labor productivity and repayment rates in credit markets. Firms therefore prefer to hire workers with good credit because it correlates with high productivity. A poverty trap may arise, in which an unemployed worker with poor credit has a low job finding rate, but cannot improve her credit without a job. In our calibrated economy, this manifests as a large and persistent wage loss from default, equivalent to 2.3% per month over ten years. Banning employer credit checks eliminates the poverty trap, but pools job seekers and reduces matching efficiency: average unemployment duration rises by 13% for the most productive workers after employers are banned from using credit histories to screen potential hires.

Suggested Citation

  • Dean Corbae & Andrew Glover, 2018. "Employer Credit Checks: Poverty Traps versus Matching Efficiency," NBER Working Papers 25005, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:25005
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    Cited by:

    1. Gajendran Raveendranathan & Georgios Stefanidis, 2025. "The Unprecedented Fall In U.S. Revolving Credit," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 66(1), pages 393-451, February.
    2. 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.
    3. 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.
    4. Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," Working Papers 2019-056, Human Capital and Economic Opportunity Working Group.
    5. Sasha Indarte & Martin Kanz, 2024. "Debt relief for households in developing economies," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 40(1), pages 139-159.
    6. Exler, Florian & Tertilt, Michèle, 2020. "Consumer Debt and Default: A Macro Perspective," IZA Discussion Papers 12966, Institute of Labor Economics (IZA).
    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. Christa Gibbs & Benedict Guttman-Kenney & Donghoon Lee & Scott Nelson & Wilbert van der Klaauw & Jialan Wang, 2025. "Consumer Credit Reporting Data," Journal of Economic Literature, American Economic Association, vol. 63(2), pages 598-636, June.
    10. Laura Blattner & Scott Nelson, 2021. "How Costly is Noise? Data and Disparities in Consumer Credit," Papers 2105.07554, arXiv.org.
    11. Stefania Albanesi & Domonkos F. Vamossy, 2024. "Credit Scores: Performance and Equity," NBER Working Papers 32917, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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