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Returns to education and gender gap

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  • Marilena Furno

Abstract

The Italian gender wage gap is related to a gap in returns to education which causes a sizable glass ceiling effect. The gap is detected by quantile regressions implemented in different subsets. Quantile regressions allow computation of both the average gap and the divergence in the tails of the wage distribution. Comparison of the equations estimated separately for men and women, reveals a divergence in wage determinants for the average and for all quantiles. The statistical relevance of this divergence is verified by a test of changing coefficients. By repeatedly implementing this test to compare subsets of different regions, cohorts, and education levels, it is possible to rank the factors affecting the gap and to pinpoint at which quantile their impact is greater. Gender turns out to be a relevant source of changes to the coefficients, particularly for the top quantiles, and the regional variable interacts with the returns to education gap, determining a sizeable glass ceiling on southern women's careers.

Suggested Citation

  • Marilena Furno, 2014. "Returns to education and gender gap," International Review of Applied Economics, Taylor & Francis Journals, vol. 28(5), pages 628-649, September.
  • Handle: RePEc:taf:irapec:v:28:y:2014:i:5:p:628-649
    DOI: 10.1080/02692171.2014.907243
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    References listed on IDEAS

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    1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    2. Monica Bozzano, 2014. "Assessing Gender Inequality among Italian Regions: The Italian Gender Gap Index," Rivista di Politica Economica, SIPI Spa, issue 1, pages 255-300, January-M.
    3. Giovanni Sulis, 2012. "Gender wage differentials in Italy: a structural estimation approach," Journal of Population Economics, Springer;European Society for Population Economics, vol. 25(1), pages 53-87, January.
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    5. Tindara Addabbo & Donata Favaro, 2011. "Gender wage differentials by education in Italy," Applied Economics, Taylor & Francis Journals, vol. 43(29), pages 4589-4605.
    6. Chiara Mussida & Matteo Picchio, 2014. "The gender wage gap by education in Italy," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(1), pages 117-147, March.
    7. Roberta Zizza, 2013. "The gender wage gap in Italy," Questioni di Economia e Finanza (Occasional Papers) 172, Bank of Italy, Economic Research and International Relations Area.
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    Cited by:

    1. Gail Pacheco & Chao Li & Bill Cochrane, 2017. "Empirical evidence of the gender pay gap in NZ," Working Papers 2017-05, Auckland University of Technology, Department of Economics.
    2. Andrea Cutillo & Marco Centra, 2017. "Gender-Based Occupational Choices and Family Responsibilities: The Gender Wage Gap in Italy," Feminist Economics, Taylor & Francis Journals, vol. 23(4), pages 1-31, October.
    3. Karlis Vilerts & Olegs Krasnopjorovs & Edgars Brekis, 2015. "Does Education Affect Wages During and After Economic Crisis? Evidence from Latvia (2006–2012)," Working Papers 2015/03, Latvijas Banka.
    4. 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.
    5. Mamiko Takeuchi, 2019. "Earnings gaps among higher-educated workers withinmain cities insemi-industrializedandnewly industrialized Asian countries," Discussion Papers in Economics and Business 19-06-Rev., Osaka University, Graduate School of Economics, revised Jul 2019.

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