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Using Matched Employer-Employee Data to Study Labor Market Discrimination

Author

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  • Hellerstein, Judith K.

    (University of Maryland)

  • Neumark, David

    (University of California, Irvine)

Abstract

Wage gaps between individuals of difference races, sexes, and ethnicities have been documented and replicated extensively, and have generated a long history in labor economics research of empirical tests for labor market discrimination. The most widely-used approach to test for labor market discrimination is based on wage regressions estimated at the level of individual workers, with the estimate of discrimination inferred from the residual race, sex, or ethnic group differential in wages that remains unexplained after including a wide array of proxies for productivity. What is absent from the residual wage approach – and in our view leaves the approach vulnerable to being regarded as uninformative regarding discrimination – is any directly observable measure of productivity with which to adjust differentials in wages in trying to infer whether a particular group suffers from discrimination. The ideal solution would be individual-level productivity data that can be compared with wages. Any of the variables that differ across groups and are unobserved in the residual wage regression approach should affect wages and productivity equally, and hence not bias the test. However, such data are extremely rare, in large part because individual productivity is often unobservable and seldom measured. This chapter focuses on the use of matched employer-employee data sets to carry out a version of this ideal test, but at the establishment level. When these data sets permit the measurement of the demographic characteristics of establishments' workforces, as well as the estimation of production functions, they can be used to infer productivity differentials between workers in different groups. Comparisons of these productivity differentials with wage differentials then provide versions of the ideal test for discrimination at the establishment level. In addition to providing tests of discrimination, matched employer-employee data sets have proven useful in studying other questions that arise in the economics of discrimination, including measuring labor market segregation and assessing its consequences, and examining hypotheses or predictions that are central to economic models of discrimination.

Suggested Citation

  • Hellerstein, Judith K. & Neumark, David, 2005. "Using Matched Employer-Employee Data to Study Labor Market Discrimination," IZA Discussion Papers 1555, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp1555
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    2. Azmat, Ghazala & Petrongolo, Barbara, 2014. "Gender and the labor market: What have we learned from field and lab experiments?," Labour Economics, Elsevier, vol. 30(C), pages 32-40.
    3. David Neumark, 2012. "Detecting Discrimination in Audit and Correspondence Studies," Journal of Human Resources, University of Wisconsin Press, vol. 47(4), pages 1128-1157.
    4. Kumar, Krishna B. & Mahmud, Minhaj & Nataraj, Shanthi & Cho, Yoon Y., 2019. "Employer and Employee Preferences for Worker Benefits: Evidence from a Matched Survey on the Bangladesh Informal Sector," IZA Discussion Papers 12064, Institute of Labor Economics (IZA).
    5. Judith K. Hellerstein & Melissa Mcinerney & David Neumark, 2010. "Spatial Mismatch, Immigrant Networks, and Hispanic Employment in the United States," Annals of Economics and Statistics, GENES, issue 99-100, pages 141-167.
    6. Mohamed Jellal & Christophe Nordman & Francois-Charles Wolff, 2008. "Evidence on the glass ceiling effect in France using matched worker-firm data," Applied Economics, Taylor & Francis Journals, vol. 40(24), pages 3233-3250.
    7. Yahmed, Sarra Ben, 2017. "Gender wage discrimination and trade openness. Prejudiced employers in an open industry," ZEW Discussion Papers 17-047, ZEW - Leibniz Centre for European Economic Research.
    8. Carolina Castagnetti & Luisa Rosti, 2012. "Unfair tournaments: gender stereotyping and wage discrimination among Italian graduates," DEM Working Papers Series 010, University of Pavia, Department of Economics and Management.
    9. repec:dau:papers:123456789/4377 is not listed on IDEAS
    10. Ederington, Josh & Sandford, Jeremy, 2016. "Employer discrimination and market structure: Does more concentration mean more discrimination?," International Journal of Industrial Organization, Elsevier, vol. 48(C), pages 1-33.
    11. Tony Fang & John S. Heywood, 2010. "Immigration, Ethnic Wage Differentials and Output Pay in Canada," British Journal of Industrial Relations, London School of Economics, vol. 48(1), pages 109-130, March.
    12. Stephen Pudney & Nikolaos Theodoropoulos, 2006. "Firm-Specific Gender and Ethnicity Pay Differentials in Britain," University of Cyprus Working Papers in Economics 9-2006, University of Cyprus Department of Economics.
    13. Merkuryeva, Irina S. & Paramonova, Elena N. & Bitina, Julia M. & Gilchenok, Veronika L., 2006. "Economic analysis based on matched employer-employee data: Methodology of data collection and research," Working Papers 805, Graduate School of Management, St. Petersburg State University.
    14. Mary Hallward-Driemeier & Bob Rijkers & Andrew Waxman, 2017. "Can Minimum Wages Close the Gender Wage Gap?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(2), pages 310-334, June.

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    Keywords

    matched employer-employee data; labor market discrimination;

    JEL classification:

    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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