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The convergence of the gender pay gap: An alternative estimation approach

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  • Castagnetti, Carolina
  • Rosti, Luisa
  • Töpfer, Marina

Abstract

So far, little work has been done on directly estimating differences of wage gaps. Stud- ies estimating pay differentials, generally compare them across different subsamples. This comparison does not allow to conduct any inference or, in the case of decompositions, to confront the respective decomposition components across subsamples. We propose an exten- sion of an Oaxaca-Blinder type decomposition based on the omitted variable bias formula to directly estimate the change in pay gaps across subsamples. The method proposed can be made robust to the index-number problem of the standard Oaxaca-Blinder decomposition and to the indeterminacy problem of the intercept-shift approach. Using Italian micro data, we estimate the difference in the gender pay gap across time (2005 and 2014). By applying our proposed decomposition, we find that the convergence of the gender pay gap over time is only driven by the catching-up of women in terms of observable characteristics, while the impact of anti-discrimination legislation is found to be negligible.

Suggested Citation

  • 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.
  • Handle: RePEc:zbw:hohdps:142017
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    More about this item

    Keywords

    Pay Gap; Omitted Varibale Bias Formula; Oaxaca-Blinder Decomposition;
    All these keywords.

    JEL classification:

    • J7 - Labor and Demographic Economics - - Labor Discrimination
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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