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The Occupational Feminization of Wages

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  • John T. Addison
  • Orgul D. Ozturk
  • Si Wang

Abstract

This article updates the 1995 study by Macpherson and Hirsch that used monthly Current Population Survey (CPS) data from 1973 to 1993 to examine the effects of occupational gender composition on earnings. In the updating process, the authors correct for biases in this data set that are attributable to the inclusion of imputed earners and the misreporting of occupation. They use CPS data from 1996 to 2010 to provide cross-sectional estimates of the impact of the feminization of occupations on wages, as well as its contribution to the gender wage gap. Longitudinal CPS data indicate that the negative effects of gender composition on earnings observed in cross-sectional data are lessened when researchers control for observed heterogeneity and are much reduced when controlling for unobserved heterogeneity. These findings are confirmed using much longer panels from the National Longitudinal Survey of Youth 1979 (NLSY79). Finally, the use of synthetic panels of aging cohorts suggests that wage penalties are largest for younger cohorts in predominantly female occupations.

Suggested Citation

  • John T. Addison & Orgul D. Ozturk & Si Wang, 2018. "The Occupational Feminization of Wages," ILR Review, Cornell University, ILR School, vol. 71(1), pages 208-241, January.
    • Handle: RePEc:sae:ilrrev:v:71:y:2018:i:1:p:208-241
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    References listed on IDEAS

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    1. Hirsch, Barry & Manzella, Julia, 2014. "Who Cares – and Does It Matter? Measuring Wage Penalties for Caring Work," IZA Discussion Papers 8388, Institute of Labor Economics (IZA).
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    Cited by:

    1. Addison, John T. & Chen, Liwen & Ozturk, Orgul Demet, 2017. "Occupational Match Quality and Gender over Two Cohorts," IZA Discussion Papers 11114, Institute of Labor Economics (IZA).
    2. John T. Addison & Liwen Chen & Orgul D. Ozturk, 2020. "Occupational Skill Mismatch: Differences by Gender and Cohort," ILR Review, Cornell University, ILR School, vol. 73(3), pages 730-767, May.
    3. Aleida Cobas-Valdés & Javier Fernández-Macho, 2021. "Gender Dissimilarities in Human Capital Transferability of Cuban Immigrants in the US: A Clustering Quantile Regression Coefficients Approach with Consideration of Implications for Sustainability," Sustainability, MDPI, vol. 13(21), pages 1-12, October.
    4. Harris, Jorgen, 2022. "Do wages fall when women enter an occupation?," Labour Economics, Elsevier, vol. 74(C).
    5. David L. Schaffer & Joseph M. Westenberg, 2019. "Time Flexibility, Women’s Wages, and the Gender Wage Gap," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(2), pages 217-239, June.
    6. Landmesser Joanna & Rusek Marian & Zajkowska Olga, 2021. "A Comparative Analysis of Men and Women’s Hourly Earnings in Poland with Particular Emphasis on the Education Sector," Folia Oeconomica Stetinensia, Sciendo, vol. 21(1), pages 18-30, June.
    7. André Cieplinski, 2018. "Supervision and Work Content: Industry level evidence," Department of Economics University of Siena 776, Department of Economics, University of Siena.

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    More about this item

    Keywords

    wages; gender composition; gender wage gap;
    All these keywords.

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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