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What a quantile approach can tell us about returns to education in Europe

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  • Juan Prieto-Rodriguez
  • Carlos Pestana Barros
  • Jose Vieira

Abstract

This paper seeks to analyse the relationship between wages and education at a European level, using a quantile regression in order to be able to extend the study along the whole wage distribution. This analysis is carried out for a sample of 14 European countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain and the United Kingdom), using the European Community Household Panel data-set. The paper aims to investigate whether the relationship between wages and education at European level is homogeneous and stable through time by running regressions for average and current (log)wages. Policy implications are derived.

Suggested Citation

  • Juan Prieto-Rodriguez & Carlos Pestana Barros & Jose Vieira, 2008. "What a quantile approach can tell us about returns to education in Europe," Education Economics, Taylor & Francis Journals, vol. 16(4), pages 391-410.
    • Handle: RePEc:taf:edecon:v:16:y:2008:i:4:p:391-410
    DOI: 10.1080/09645290801977033
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    References listed on IDEAS

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    1. David Card, 1994. "Earnings, Schooling, and Ability Revisited," Working Papers 710, Princeton University, Department of Economics, Industrial Relations Section..
    2. repec:fth:prinin:331 is not listed on IDEAS
    3. David Card, 1994. "Earnings, Schooling, and Ability Revisited," Working Papers 710, Princeton University, Department of Economics, Industrial Relations Section..
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    Citations

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    Cited by:

    1. Aysit Tansel & Fatma Bircan Bodur, 2012. "Wage Inequality and Returns to Education in Turkey: A Quantile Regression Analysis," Review of Development Economics, Wiley Blackwell, vol. 16(1), pages 107-121, February.
    2. Corrado Andini, 2022. "Tertiary education for all and wage inequality: policy insights from quantile regression," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(6), pages 1281-1296, November.
    3. Rafal Kierzenkowski & Isabell Koske, 2012. "Less Income Inequality and More Growth – Are they Compatible? Part 8. The Drivers of Labour Income Inequality – A Literature Review," OECD Economics Department Working Papers 931, OECD Publishing.
    4. Jean-Marc Fournier & Isabell Koske, 2012. "Less Income Inequality and More Growth – Are they Compatible? Part 7. The Drivers of Labour Earnings Inequality – An Analysis Based on Conditional and Unconditional Quantile Regressions," OECD Economics Department Working Papers 930, OECD Publishing.
    5. Jean-Marc Fournier & Isabell Koske, 2012. "The determinants of earnings inequality: evidence from quantile regressions," OECD Journal: Economic Studies, OECD Publishing, vol. 2012(1), pages 7-36.
    6. José Vieira & Carolina Constância & João Teixeira, 2020. "Education and risk compensation in wages: a quantile regression approach," Applied Economics Letters, Taylor & Francis Journals, vol. 27(3), pages 194-198, February.
    7. Jabłoński Łukasz, 2019. "Inequality in Economics: The Concept, Perception, Types, and Driving Forces," Journal of Management and Business Administration. Central Europe, Sciendo, vol. 27(1), pages 17-43, March.
    8. Marco Biagetti & Sergio Scicchitano, 2012. "Returns to Schooling in Europe: Evidence From Quantile Regression on EU-SILC Data," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 2(5), pages 1-9, October.
    9. Aysit Tansel & Fatma Bircan Bodur, 2012. "Wage Inequality and Returns to Education in Turkey: A Quantile Regression Analysis," Review of Development Economics, Wiley Blackwell, vol. 16(1), pages 107-121, February.

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