Deleting a Signal: Evidence from Pre-employment Credit Checks

Alexander Bartik () and Scott T. Nelson
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Scott T. Nelson: University of Chicago, Booth School of Business

The Review of Economics and Statistics, 2025, vol. 107, issue 1, 152-171

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.

Date: 2025
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