IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-11-00489.html

Education and wage inequality in Europe

Author

Listed:
  • Marco Biagetti

    (Ministry of Economic Development, Department of Economic and Social Cohesion)

  • Sergio Scicchitano

    ("La Sapienza" University and Italian Ministry of Economic Development)

Abstract

In this paper we apply a quantile regression (QR) approach to the EU-SILC data set, in order to explore the connection between education and wage inequality in eight European countries. Our results corroborate the positive relation between wage increase and education and it holds true across the whole distribution. This effect is generally stronger at the highest quantiles of the distribution than at the lowest, implying that schooling increases wage dispersion. This evidence is found to be rather robust like the applied tests of linear hypothesis show.

Suggested Citation

  • Marco Biagetti & Sergio Scicchitano, 2011. "Education and wage inequality in Europe," Economics Bulletin, AccessEcon, vol. 31(3), pages 2620-2628.
    • Handle: RePEc:ebl:ecbull:eb-11-00489
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2011/Volume31/EB-11-V31-I3-P235.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Martins, Pedro S. & Pereira, Pedro T., 2004. "Does education reduce wage inequality? Quantile regression evidence from 16 countries," Labour Economics, Elsevier, vol. 11(3), pages 355-371, June.
    2. Wood Júnior, Thomaz, 1995. "Workers," RAE - Revista de Administração de Empresas, FGV-EAESP Escola de Administração de Empresas de São Paulo (Brazil), vol. 35(2), March.
    3. Santiago Budría & Pedro Telhado-Pereira, 2011. "Educational Qualifications And Wage Inequality: Evidence For Europe," Revista de Economia Aplicada, Universidad de Zaragoza, Departamento de Estructura Economica y Economia Publica, vol. 19(2), pages 5-34, Autumn.
    4. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    5. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-1044, September.
    6. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    7. Adrian Wood, 1997. "How Trade Hurt Unskilled Workers," Palgrave Macmillan Books, in: Jitendralal Borkakoti & Chris Milner (ed.), International Trade and Labour Markets, chapter 7, pages 140-168, Palgrave Macmillan.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. António Morgado & Tiago Neves Sequeira & Marcelo Santos & Alexandra Ferreira-Lopes & Ana Balcão Reis, 2016. "Measuring Labour Mismatch in Europe," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(1), pages 161-179, October.
    2. Marilena Furno & Francesco Caracciolo, 2025. "Propensity Score in the Tails and Returns to Education in Italy," Economies, MDPI, vol. 13(2), pages 1-28, February.
    3. Kiran Fahd & Sitalakshmi Venkatraman, 2019. "Racial Inclusion in Education: An Australian Context," Economies, MDPI, vol. 7(2), pages 1-12, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. LILLA Marco, 2007. "Income Inequality and Education Premia," IRISS Working Paper Series 2007-11, IRISS at CEPS/INSTEAD.
    3. Marco LILLA, 2008. "Income Inequality and Education from ECHP data," Working Papers 311, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    4. Petra Sauer & Philippe Van Kerm & Daniele Checchi, 2025. "Higher Education Expansion & Labour Income Inequality in High-income Countries: A Gender-specific Perspective," LIS Working papers 837, LIS Cross-National Data Center in Luxembourg.
    5. Aghion, Philippe & Howitt, Peter & Violante, Giovanni L, 2002. "General Purpose Technology and Wage Inequality," Journal of Economic Growth, Springer, vol. 7(4), pages 315-345, December.
    6. Michael Chletsos & Stelios Roupakias, 2020. "Education and wage inequality before and during the fiscal crisis: A quantile regression analysis for Greece 2006–2016," Review of Development Economics, Wiley Blackwell, vol. 24(4), pages 1333-1364, November.
    7. Patrinos, Harry Anthony & Ridao-Cano, Cris & Sakellariou, Chris, 2006. "Estimating the returns to education : accounting for heterogeneity in ability," Policy Research Working Paper Series 4040, The World Bank.
    8. Kazumichi Iwasa & Laixun Zhao, 2013. "Inequalities and Patience for Tomorrow," KIER Working Papers 847, Kyoto University, Institute of Economic Research.
    9. Carmen Aina & Irene Brunetti & Chiara Mussida & Sergio Scicchitano, 2023. "Distributional effects of COVID-19," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 13(1), pages 221-256, March.
    10. Kijima, Yoko, 2006. "Why did wage inequality increase? Evidence from urban India 1983-99," Journal of Development Economics, Elsevier, vol. 81(1), pages 97-117, October.
    11. Attanasio, Orazio & Goldberg, Pinelopi K. & Pavcnik, Nina, 2004. "Trade reforms and wage inequality in Colombia," Journal of Development Economics, Elsevier, vol. 74(2), pages 331-366, August.
    12. Santiago Budria, 2010. "Schooling and the distribution of wages in the European private and public sectors," Applied Economics, Taylor & Francis Journals, vol. 42(8), pages 1045-1054.
    13. G. Reza Arabsheibani & Francisco Galrao Carneiro & Andrew Henley, 2006. "Changes in human capital and earnings inequality: Recent evidence from Brazil," Journal of Development Studies, Taylor & Francis Journals, vol. 42(5), pages 837-867.
    14. Corrado Andini, 2010. "A dynamic Mincer equation with an application to Portuguese data," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2091-2098.
    15. Cristiano PERUGINI & Fabrizio POMPEI, 2009. "Technological change and income distribution in Europe," International Labour Review, International Labour Organization, vol. 148(1-2), pages 123-148, June.
    16. Saiah Lee, 2023. "Macroeconomic Conditions and Wage Inequality: Expanding and Analyzing the Worldwide Dataset," Annals of Economics and Finance, Society for AEF, vol. 24(2), pages 329-362, November.
    17. Andreas Behr & Ulrich Pötter, 2009. "Analysing Wage Differences between the USA and Germany Using Proportional Hazards Models," LABOUR, CEIS, vol. 23(2), pages 319-347, June.
    18. Marquis, Milton H. & Trehan, Bharat & Tantivong, Wuttipan, 2014. "The wage premium puzzle and the quality of human capital," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 100-110.
    19. Aleksandra Parteka, 2012. "Skilled-Unskilled Wage Gap Versus Evolving Trade And Labour Market Structures in the EU," Working Papers 1204, Instytut Rozwoju, Institute for Development.
    20. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • I2 - Health, Education, and Welfare - - Education
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ebl:ecbull:eb-11-00489. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: John P. Conley (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.