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Banning information in hiring decisions

Author

Listed:
  • Anthony M. Marino

    (University of Southern California)

Abstract

Over the past decade, federal, state and local governments have restricted the types and uses of information in hiring and promotion decisions. Examples include the banning of credit reports and criminal records. This paper presents a simple microeconomic model of a competitive labor market and studies the economic effects of information bans. The key trade off is between allocative efficiency and helping a labor type with an undesirable characteristic. We compare information bans to direct subsidies. Moreover, we discuss the case where the ban creates negative feedback on the perceptions of firms considering workers of the bad type.

Suggested Citation

  • Anthony M. Marino, 2020. "Banning information in hiring decisions," Journal of Regulatory Economics, Springer, vol. 58(1), pages 33-58, August.
    • Handle: RePEc:kap:regeco:v:58:y:2020:i:1:d:10.1007_s11149-020-09410-3
    DOI: 10.1007/s11149-020-09410-3
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    References listed on IDEAS

    as
    1. Clifford, Robert & Shoag, Daniel, 2016. ""No More Credit Score": Emplyer Credit Check Bans and Signal Substitution," Working Paper Series 16-008, Harvard University, John F. Kennedy School of Government.
    2. Cherrie Bucknor & Alan Barber, 2016. "The Price We Pay: Economic Costs of Barriers to Employment for Former Prisoners and People Convicted of Felonies," CEPR Reports and Issue Briefs 2016-07, Center for Economic and Policy Research (CEPR).
    3. Kristle Romero Cortes & Andrew Glover & Murat Tasci, 2016. "The Unintended Consequences of Employer Credit Check Bans on Labor and Credit Markets," Working Papers 16-25R2, Federal Reserve Bank of Cleveland.
    4. Jennifer L. Doleac & Benjamin Hansen, 2016. "Does “Ban the Box” Help or Hurt Low-Skilled Workers? Statistical Discrimination and Employment Outcomes When Criminal Histories are Hidden," NBER Working Papers 22469, National Bureau of Economic Research, Inc.
    5. Amanda Agan & Sonja Starr, 2018. "Ban the Box, Criminal Records, and Racial Discrimination: A Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 191-235.
    6. Robert Clifford & Daniel Shoag, 2016. "“No more credit score”: employer credit check bans and signal substitution," Working Papers 16-10, Federal Reserve Bank of Boston.
    7. Young†Chul Kim & Glenn C. Loury, 2018. "Collective Reputation And The Dynamics Of Statistical Discrimination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(1), pages 3-18, February.
    8. Joseph J. Sabia & Taylor Mackay & Thanh Tam Nguyen & Dhaval M. Dave, 2018. "Do Ban the Box Laws Increase Crime?," NBER Working Papers 24381, National Bureau of Economic Research, Inc.
    9. Jennifer Doleac & Benjamin Hansen, 2016. "Does “Ban the Box†Help or Hurt Low-Skilled Workers? Statistical Discrimination and Employment Outcomes when Criminal Histories are Hidden," Working Papers id:11170, eSocialSciences.
    10. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Banning; Information;

    JEL classification:

    • J2 - Labor and Demographic Economics - - Demand and Supply of Labor
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation

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