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Education, Gender and Earnings in France and Germany: Level and Dispersion Effects

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  • Lauer, Charlotte

Abstract

This paper analyses the relationship between education, gender and earnings in France and Germany. The model chosen here enables to estimate the impact of education not only on the expected earnings level but also on their dispersion, taking gender-specific sample selectivity into account. The results indicate that the completion of a minimum level of general instruction yields an earnings premium that cannot compensated by a vocational degree. Moreover, education affects the uncertainty of earnings. General qualifications are found to increase the earnings risk, vocational one to reduce it. More education, especially tertiary education, yields a high earnings premium but is associated with the highest earnings uncertainty. Women enjoy a higher earnings premium for education than men and though they face overall a higher earnings uncertainty, they can - more than men - reduce this risk by investing in their education.

Suggested Citation

  • Lauer, Charlotte, 2004. "Education, Gender and Earnings in France and Germany: Level and Dispersion Effects," ZEW Discussion Papers 04-54, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:2192
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    References listed on IDEAS

    as
    1. Lauer, Charlotte, 2003. "Education and Unemployment: A French-German Comparison," ZEW Discussion Papers 03-34, ZEW - Leibniz Centre for European Economic Research.
    2. William W. Gould & Jeffrey Pitblado & Brian Poi, 2010. "Maximum Likelihood Estimation with Stata," Stata Press books, StataCorp LP, edition 4, number ml4.
    3. Ch. LAUER & A.M. WEBER, 2003. "Employment of Mothers after Childbirth : A French-German Comparison," Working Papers ERMES 0309, ERMES, University Paris 2.
    4. Pedro Telhado Pereira & Pedro Silva Martins, 2000. "Does education reduce wage inequality? Quantile regressions evidence from fifteen European countries," Nova SBE Working Paper Series wp379, Universidade Nova de Lisboa, Nova School of Business and Economics.
    5. Lauer, Charlotte, 2001. "Educational attainment: a French-German comparison," ZEW Dokumentationen 01-02, ZEW - Leibniz Centre for European Economic Research.
    6. James J. Heckman & Lance J. Lochner & Petra E. Todd, 2003. "Fifty Years of Mincer Earnings Regressions," NBER Working Papers 9732, National Bureau of Economic Research, Inc.
    7. Hildegard Brauns & Walter Müller & Susanne Steinmann, 1997. "Educational Expansion and Returns to Education. A Comparative Study on Germany, France, the UK, and Hungary," MZES Working Papers 23, MZES.
    8. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    9. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
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    Cited by:

    1. Farrukh Bashir & Ismat Nasim & Muhammad Junaid Nasrullah, 2017. "Does Education level lead to Higher Earnings of Farmers and Businessmen in Pakistan? A Case Study of District Bahawalnagar," Pakistan Journal of Humanities and Social Sciences, International Research Alliance for Sustainable Development (iRASD), vol. 5(2), pages :140-163, December.
    2. Ion Pohoata & Gabriel Cariman & Vladimir-Mihai Crupenschi, 2017. "Demographic Optimum in the Context of Migration. The German Case," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 19(46), pages 654-654, August.

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    More about this item

    Keywords

    education; earnings; heteroscedasticity;
    All these keywords.

    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • I2 - Health, Education, and Welfare - - Education

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