Deleting a Signal: Evidence from Pre-Employment Credit Checks

87 Pages Posted: 8 Apr 2016 Last revised: 28 Sep 2020

See all articles by Alexander Bartik

Alexander Bartik

University of Illinois at Urbana-Champaign - Department of Economics

Scott Nelson

University of Chicago - Booth School of Business

Date Written: March 7, 2016

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 70% higher standard deviation of signal noise for Black relative to white job-seekers.

Keywords: Employment Discrimination, Hiring, Firing, Signaling, Information Economics

JEL Classification: J680, J780, M510, J630, D040, D820, D830

Suggested Citation

Bartik, Alexander and Nelson, Scott, Deleting a Signal: Evidence from Pre-Employment Credit Checks (March 7, 2016). MIT Department of Economics Graduate Student Research Paper 16-01, Chicago Booth Research Paper No. 19-23, Available at SSRN: https://ssrn.com/abstract=2759560 or http://dx.doi.org/10.2139/ssrn.2759560

Alexander Bartik (Contact Author)

University of Illinois at Urbana-Champaign - Department of Economics ( email )

410 David Kinley Hall
1407 W. Gregory
Urbana, IL 61801
United States

Scott Nelson

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

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