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Returns to Education and Gender Wage Gap Across Quantiles in Italy

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  • Marilena Furno

    (Università degli Studi di Napoli “Federico IIâ€)

Abstract

Various quantile regression approaches are implemented to analyze the characteristics of Italian data on earnings in the tails. A changing coefficients pattern across quantiles shows increasing returns to education along the wage distribution. A quantile decomposition approach shows that higher education grants higher return at all quantiles, thus implying additional, non-linear returns to higher education throughout the entire pattern of the earning distribution. Wage gender gap displays a decreasing pattern across quantiles, and it does not disappear at the higher quantiles. The southern workers penalty decreases across quantiles as well for highly educated workers.

Suggested Citation

  • Marilena Furno, 2020. "Returns to Education and Gender Wage Gap Across Quantiles in Italy," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(2), pages 145-169, June.
    • Handle: RePEc:psc:journl:v:12:y:2020:i:2:p:145-169
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    More about this item

    Keywords

    quantile regression; decomposition; returns to education; gender wage gap;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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