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The gender-dependent structure of wages in Hungary: results using machine learning techniques

Author

Listed:
  • Olga Takács

    (Corvinus University of Budapest, Hungary, H-1093 Budapest, Fővám Square 8)

  • János Vincze

    (Corvinus University of Budapest, Hungary , H-1093 Budapest, Fővám Square 8 and Centre for Economic and Regional Studies, Institute of Economics, (KRTK KTI),)

Abstract

This paper reports the results of a Blinder-Oaxaca style decomposition analysis on Hungarian matched employer-employee data to study the gender pay-gap. We carry out the decomposition by Random Forest regressions. The raw gap in our horizon (2008-2016) is increasing, but we find that the wage structure effects are rather stable, thus the rise in the gap is due to the disappearance of the formerly negative composition effects. Graphical analysis sheds light on interesting non-linear relationships; some of them can be readily interpreted by the previous literature. A Classification and Regression Tree analysis suggests that complicated interaction patterns exist in the data. We identify segments of the Hungarian labour market that are most and least exposed to gender-dependent wage determination. Our findings lend support to the idea that an important part of the gender wage gap is attributable to monopsonistic competition with gender-dependent supply elasticities.

Suggested Citation

  • Olga Takács & János Vincze, 2020. "The gender-dependent structure of wages in Hungary: results using machine learning techniques," CERS-IE WORKING PAPERS 2044, Institute of Economics, Centre for Economic and Regional Studies.
    • Handle: RePEc:has:discpr:2044
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    References listed on IDEAS

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    More about this item

    Keywords

    Gender pay gap ; Blinder-Oaxaca decomposition; Random Forest Regression Hungary;
    All these keywords.

    JEL classification:

    • J7 - Labor and Demographic Economics - - Labor Discrimination
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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