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Deleting a Signal: Evidence from Pre-employment Credit Checks

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  • Alexander W. Bartik

    (University of Illinois at Urbana-Champaign)

  • Scott T. Nelson

    (University of Chicago, Booth School of Business)

Abstract

We study the removal of information from a market, such as a job-applicant screening tool. We characterize how removal harms groups with relative advantage in that information: typically those for whom the banned information is most precise relative to alternative signals. We illustrate this using recent bans on employers’ use of credit report data. Bans decrease job-finding rates for Black job-seekers by 3 percentage points and increase involuntary separations for Black new hires by 4 percentage points, primarily because other screening tools, such as interviews, have around 60% higher standard deviation of signal noise for Black relative to white job-seekers.

Suggested Citation

  • Alexander W. Bartik & Scott T. Nelson, 2025. "Deleting a Signal: Evidence from Pre-employment Credit Checks," The Review of Economics and Statistics, MIT Press, vol. 107(1), pages 152-171, January.
    • Handle: RePEc:tpr:restat:v:107:y:2025:i:1:p:152-171
    DOI: 10.1162/rest_a_01406
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