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The Gender Pay Gap in the US: A Matching Study

Author

Listed:
  • Meara, Katie
  • Pastore, Francesco
  • Webster, Allan

Abstract

This study examines the gender wage gap in the US using two separate cross-sections from the Current Population Survey (CPS). The extensive literature on this subject includes papers which use wage decompositions to divide gender wag gaps into “explained” and “unexplained” components. Problems with this approach include the heterogeneity of the sample data. In order to address the difficulties of comparing like with like this study uses a number of different matching techniques to obtain estimates of the gap. By controlling for a wide range of other influences, in effect, we estimate the direct effect of simply being female on wages. However, to form a complete picture, one should consider that gender wages are affected by a number of other factors such as parenthood, gender segregation, part-time working and unionization. This means that it is not just the core “like for like” comparison between male and female wages that matters but also how gender wage differences interact with other relevant risk factors which are more common for women. That these interactions exist has already been discussed in the literature but evidence that precisely or systematically estimates such effects remains scarce. The most innovative contribution of this study is to do that. Our findings imply that the idea of a single uniform gender pay gap is perhaps less useful than an understanding of how gender wages are shaped by multiple different forces.

Suggested Citation

  • Meara, Katie & Pastore, Francesco & Webster, Allan, 2019. "The Gender Pay Gap in the US: A Matching Study," GLO Discussion Paper Series 363, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:363
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    File URL: https://www.econstor.eu/bitstream/10419/200093/1/GLO-DP-0363.pdf
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    More about this item

    Keywords

    gender pay; Current Population Survey; part-time working; gender segregation; unionization; sample selection bias; matching; IPWRA; USA;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • K38 - Law and Economics - - Other Substantive Areas of Law - - - Human Rights Law; Gender Law

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