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A Test of Screening Discrimination with Employer Learning

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  • Joshua C. Pinkston

Abstract

This paper tests for the presence of screening discrimination, a type of statistical discrimination that occurs when employers are less able to evaluate the ability of workers from one group than from another. Using data from the 2000 release of the NLSY79, the author examines wage equations in a framework of employer learning to test the hypothesis that the market receives less reliable productivity signals at labor market entry from black men than from white men. The estimation results support this hypothesis. Variables that are difficult for employers to observe, such as the AFQT score, had less influence on the wages of black men (and easily observed variables had more influence) than on the wages of white men. The influence of hard-to-observe variables on wages, however, increased faster with experience for black men.

Suggested Citation

  • Joshua C. Pinkston, 2006. "A Test of Screening Discrimination with Employer Learning," ILR Review, Cornell University, ILR School, vol. 59(2), pages 267-284, January.
    • Handle: RePEc:sae:ilrrev:v:59:y:2006:i:2:p:267-284
    DOI: 10.1177/001979390605900205
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    References listed on IDEAS

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    1. Oettinger, Gerald S, 1996. "Statistical Discrimination and the Early Career Evolution of the Black-White Wage Gap," Journal of Labor Economics, University of Chicago Press, vol. 14(1), pages 52-78, January.
    2. Lundberg, Shelly J & Startz, Richard, 1983. "Private Discrimination and Social Intervention in Competitive Labor Markets," American Economic Review, American Economic Association, vol. 73(3), pages 340-347, June.
    3. Shelly J. Lundberg, 1991. "The Enforcement of Equal Opportunity Laws Under Imperfect Information: Affirmative Action and Alternatives," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(1), pages 309-326.
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    Cited by:

    1. Brück-Klingberg, Andrea & Burkert, Carola & Garloff, Alfred & Seibert, Holger & Wapler, Rüdiger, 2011. "Does higher education help immigrants find a job? : A survival analysis," IAB-Discussion Paper 201106, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Hornig, Stephan O. & Rottmann, Horst & Wapler, Rüdiger, 2011. "Sorting on the labour market: A literature overview and theoretical framework," Weidener Diskussionspapiere 27, University of Applied Sciences Amberg-Weiden (OTH).
    3. Light, Audrey & McGee, Andrew, 2015. "Does employer learning vary by schooling attainment? The answer depends on how career start dates are defined," Labour Economics, Elsevier, vol. 32(C), pages 57-66.
    4. Yariv Fadlon, 2015. "Statistical Discrimination and the Implication of Employer-Employee Racial Matches," Journal of Labor Research, Springer, vol. 36(2), pages 232-248, June.
    5. Daniel Auer, 2022. "Firing discrimination: Selective labor market responses of firms during the COVID-19 economic crisis," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-30, January.
    6. Charness, Gary & Cobo-Reyes, Ramón & Meraglia, Simone & Sánchez, Ángela, 2020. "Anticipated Discrimination, Choices, and Performance: Experimental Evidence," European Economic Review, Elsevier, vol. 127(C).
    7. Audrey Light & Andrew McGee, 2015. "Employer Learning and the “Importance†of Skills," Journal of Human Resources, University of Wisconsin Press, vol. 50(1), pages 72-107.
    8. Emiko Usui & Seik Kim, 2013. "Employer Learning, Job Mobility, and Wage Dynamics," 2013 Meeting Papers 912, Society for Economic Dynamics.
    9. Audrey Light & Andrew McGee, 2011. "Employer Learning and the “Importance” of Skills," Working Papers 11-02, Ohio State University, Department of Economics.
    10. Ashley C. Craig, 2023. "Optimal Income Taxation with Spillovers from Employer Learning," American Economic Journal: Economic Policy, American Economic Association, vol. 15(2), pages 82-125, May.
    11. Joanna N. Lahey & Douglas R. Oxley, 2021. "Discrimination at the Intersection of Age, Race, and Gender: Evidence from an Eye‐Tracking Experiment," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(4), pages 1083-1119, September.
    12. Keng, Shao-Hsun, 2020. "Gender bias and statistical discrimination against female instructors in student evaluations of teaching," Labour Economics, Elsevier, vol. 66(C).
    13. Seik Kim & Emiko Usui, 2021. "Employer learning, job changes, and wage dynamics," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 1286-1307, July.
    14. Lena Hensvik & Oskar Nordström Skans, 2016. "Social Networks, Employee Selection, and Labor Market Outcomes," Journal of Labor Economics, University of Chicago Press, vol. 34(4), pages 825-867.
    15. Wang, Jun & Li, Bo, 2020. "Does employer learning with statistical discrimination exist in China? Evidence from Chinese Micro Survey Data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 319-333.
    16. Lehdonvirta, Vili & Kässi, Otto & Hjorth, Isis & Barnard, Helena & Graham, Mark, 2018. "The Global Platform Economy: A New Offshoring Institution Enabling Emerging-Economy Microproviders," SocArXiv jt4z7, Center for Open Science.
    17. ZHANGALIYEVA, Aigerim & NAKABAYASHI, Masaki, 2013. "Legacy of Czar: The Russian Dual System of Schooling and Signaling," ISS Discussion Paper Series (series F) f163, Institute of Social Science, The University of Tokyo, revised 04 Sep 2019.
    18. James Fain, 2016. "Screening Discrimination in a Broader Context," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(4), pages 276-294, October.
    19. Mari, Gabriele & Luijkx, Ruud, 2020. "Gender, Parenthood, and Hiring Intentions in Sex-Typical Jobs: A Survey Experiment," SocArXiv kwdyp, Center for Open Science.

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