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Gender wage gap decomposition methods: Comparative analysis

Author

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  • Roshchin, Sergey

    (HSE University, Moscow, Russian Federation)

  • Yemelina, Natalya

    (HSE University, Moscow, Russian Federation)

Abstract

This study introduces a comparative analysis of the gender wage gap decomposition methods with the Russian Longitudinal Monitoring Survey (RLMS) data for 2018. To decompose the differences in average wages, approaches based on the Oaxaca–Blinder decomposition are used. Apart from the mean wages, the study focuses on other distribution statistics. Using the quantile regressions, the wage gap between men and women is decomposed for the distribution parameters such as median, lower and upper deciles. The decomposition estimates of conditional and unconditional (based on recentered influence functions) quantile regressions are compared.

Suggested Citation

  • Roshchin, Sergey & Yemelina, Natalya, 2021. "Gender wage gap decomposition methods: Comparative analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 62, pages 5-31.
  • Handle: RePEc:ris:apltrx:0417
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    References listed on IDEAS

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    Cited by:

    1. Ksenia V. Rozhkova & Natalya Yemelina & Sergey Yu. Roshchin, 2021. "Can Non-Cognitive Skills Explain The Gender Wage Gap In Russia? An Unconditional Quantile Regression Approach," HSE Working papers WP BRP 252/EC/2021, National Research University Higher School of Economics.

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    More about this item

    Keywords

    labour market; gender wage gap; decomposition; quantile regression; RIF-regression; selection correction;
    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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