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Gender Wage Gap Accounting: The Role of Selection Bias

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  • Michael Bar
  • Seik Kim
  • Oksana Leukhina

Abstract

Mulligan and Rubinstein ( 2008 ) (MR) argued that changing selection of working females on unobservable characteristics, from negative in the 1970s to positive in the 1990s, accounted for nearly the entire closing of the gender wage gap. We argue that their female wage equation estimates are inconsistent. Correcting this error substantially weakens the role of the rising selection bias (39 % versus 78 %) and strengthens the contribution of declining discrimination (42 % versus 7 %). Our findings resonate better with related literature. We also explain why our finding of positive selection in the 1970s provides additional support for MR’s main hypothesis that an exogenous rise in the market value of unobservable characteristics contributed to the closing of the gender gap. Copyright Population Association of America 2015

Suggested Citation

  • Michael Bar & Seik Kim & Oksana Leukhina, 2015. "Gender Wage Gap Accounting: The Role of Selection Bias," Demography, Springer;Population Association of America (PAA), vol. 52(5), pages 1729-1750, October.
    • Handle: RePEc:spr:demogr:v:52:y:2015:i:5:p:1729-1750
    DOI: 10.1007/s13524-015-0418-x
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    Cited by:

    1. Matthias Westphal & Daniel A Kamhöfer & Hendrik Schmitz, 2022. "Marginal College Wage Premiums Under Selection Into Employment," The Economic Journal, Royal Economic Society, vol. 132(646), pages 2231-2272.
    2. Töpfer, Marina & Castagnetti, Carolina & Rosti, Luisa, 2016. "Discriminate me - if you can! The Disappearance of the Gender Pay Gap among Public-Contest Selected Employees," VfS Annual Conference 2016 (Augsburg): Demographic Change 145905, Verein für Socialpolitik / German Economic Association.
    3. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    4. Ulf Nielsson & Herdis Steingrimsdottir, 2018. "The signalling value of education across genders," Empirical Economics, Springer, vol. 54(4), pages 1827-1854, June.
    5. Masayuki Hirukawa & Di Liu & Irina Murtazashvili & Artem Prokhorov, 2023. "DS-HECK: double-lasso estimation of Heckman selection model," Empirical Economics, Springer, vol. 64(6), pages 3167-3195, June.
    6. Ben Sand & Chris Bidner, 2016. "Job Prospects and Pay Gaps: Theory and Evidence on the Gender Gap from U.S. Cities," Discussion Papers dp16-14, Department of Economics, Simon Fraser University.
    7. Brendon McConnell, 2022. "Racial Sentencing Disparities and Differential Progression Through the Criminal Justice System: Evidence From Linked Federal and State Court Data," Papers 2203.14282, arXiv.org, revised Apr 2022.
    8. Michael Bar & Nishanlang Khonglah, 2022. "Racial differences in access to mortgage lending: comparison across major institutions," SN Business & Economics, Springer, vol. 2(8), pages 1-26, August.
    9. Töpfer, Marina, 2017. "Detailed RIF Decomposition with Selection - The Gender Pay Gap in Italy," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168422, Verein für Socialpolitik / German Economic Association.
    10. Castagnetti, Carolina & Rosti, Luisa & Töpfer, Marina, 2017. "The convergence of the gender pay gap: An alternative estimation approach," Hohenheim Discussion Papers in Business, Economics and Social Sciences 14-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    11. Carolina Castagnetti & Luisa Rosti & Marina Töpfer, 2020. "Discriminate me — If you can! The disappearance of the gender pay gap among public‐contest selected employees in Italy," Gender, Work and Organization, Wiley Blackwell, vol. 27(6), pages 1040-1076, November.

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