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Detailed RIF decomposition with selection: The gender pay gap in Italy

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  • Töpfer, Marina

Abstract

In this paper, we estimate the gender pay gap along the wage distribution using a detailed decomposition approach based on unconditional quantile regressions. Non-randomness of the sample leads to biased and inconsistent estimates of the wage equation as well as of the components of the wage gap. Therefore, the method is extended to account for sample selection problems. The decomposition is conducted by using Italian microdata. Accounting for labor market selection may be particularly relevant for Italy given a comparably low female labor market participation rate. The results suggest not only differences in the income gap along the wage distribution (in particular glass ceiling), but also differences in the contribution of selection effects to the pay gap at different quantiles.

Suggested Citation

  • Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
  • Handle: RePEc:zbw:hohdps:262017
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    1. Piazzalunga, Daniela & Di Tommaso, Maria Laura, 2015. "The increase of gender wage gap in Italy during the 2008-2012 economic crisis," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201532, University of Turin.
    2. Ghosh, Pallab Kumar, 2014. "The contribution of human capital variables to changes in the wage distribution function," Labour Economics, Elsevier, vol. 28(C), pages 58-69.
    3. Daniela Piazzalunga & Maria Laura Di Tommaso, 2015. "The increase of the gender wage gap in Italy during the 2008-2012 economic crisis," Working Papers 381, ECINEQ, Society for the Study of Economic Inequality.
    4. Wolfgang HÄRDLE & Joel L. HOROWITZ, 1994. "Testing a Parametric Model against a Semiparametric Model," SFB 373 Discussion Papers 1994,6, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Henderson,Daniel J. & Parmeter,Christopher F., 2015. "Applied Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521279680, April.
    6. Horowitz, Joel L. & Härdle, Wolfgang, 1994. "Testing a Parametric Model Against a Semiparametric Alternative," Econometric Theory, Cambridge University Press, vol. 10(05), pages 821-848, December.
    7. Chzhen, Yekaterina & Mumford, Karen, 2011. "Gender gaps across the earnings distribution for full-time employees in Britain: Allowing for sample selection," Labour Economics, Elsevier, vol. 18(6), pages 837-844.
    8. Albrecht, James & van Vuuren, Aico & Vroman, Susan, 2009. "Counterfactual distributions with sample selection adjustments: Econometric theory and an application to the Netherlands," Labour Economics, Elsevier, vol. 16(4), pages 383-396, August.
    9. Michael Bar & Seik Kim & Oksana Leukhina, 2015. "Gender Wage Gap Accounting: The Role of Selection Bias," Demography, Springer;Population Association of America (PAA), vol. 52(5), pages 1729-1750, October.
    10. Wayne A. Grove & Andrew Hussey & Michael Jetter, 2011. "The Gender Pay Gap Beyond Human Capital: Heterogeneity in Noncognitive Skills and in Labor Market Tastes," Journal of Human Resources, University of Wisconsin Press, vol. 46(4), pages 827-874.
    11. Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
    12. Dora L. Costa & Matthew E. Kahn, 2008. "Learning from the Past," NBER Chapters,in: Heroes and Cowards: The Social Face of War National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    Gender Pay Gap; Detailed Decomposition; Unconditional Quantile Regression; Sample Selection;

    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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