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Using Matched Employer–Employee Data to Study Labor Market Discrimination

In: Handbook on the Economics of Discrimination

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  • Judith K. Hellerstein
  • David Neumark

Abstract

Discrimination's dynamic nature means that no single theory, method, data or study should be relied upon to assess its magnitude, causes, or remedies. Despite some gains in our understanding, these remain active areas of debate among researchers, practitioners and policymakers. The specially commissioned papers in this volume, all by distinguished contributors, present the full range of issues related to this complex and challenging problem.

Suggested Citation

  • Judith K. Hellerstein & David Neumark, 2006. "Using Matched Employer–Employee Data to Study Labor Market Discrimination," Chapters, in: William M. Rodgers III (ed.), Handbook on the Economics of Discrimination, chapter 2, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:2634_2
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    References listed on IDEAS

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    Cited by:

    1. BROSIUS Jacques & RAY Jean-Claude & VERHEYDEN Bertrand & WILLIAMS Donald R., 2014. "Wage differentials between natives and cross-border workers within and across establishments," LISER Working Paper Series 2014-04, Luxembourg Institute of Socio-Economic Research (LISER).
    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. repec:dau:papers:123456789/4377 is not listed on IDEAS
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.

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    More about this item

    Keywords

    Business and Management; Economics and Finance; Social Policy and Sociology;
    All these keywords.

    JEL classification:

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

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