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Skills and Wage Inequality: Evidence from PIAAC

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  • Marco Paccagnella

    (OECD)

Abstract

This paper exploits data from the Survey of Adult Skills (PIAAC) to shed light on the link between measured cognitive skills (proficiency), (formal) educational attainment and labour market outcomes. After presenting descriptive statistics on the degree of dispersion in the distributions of proficiency and wages, the paper shows that the cross-country correlation between these two dimensions of inequality is very low and, if anything, negative. As a next step, the paper provides estimates of the impact of both proficiency and formal education at different parts of the distribution of earnings. Formal education is found to have a larger impact on inequality, given that returns to education are in general much higher at the top than at the bottom of the distribution. The profile of returns to proficiency, by contrary, is much flatter. This is consistent with the idea that PIAAC measures rather general skills, while at the top end of the distribution the labour market rewards specialised knowledge that is necessarily acquired through tertiary and graduate education. Finally, a decomposition exercise shows that composition effects are able to explain a very limited amount of the observed cross-country differences in wage inequality. This suggests that economic institutions, by shaping the way personal characteristics are rewarded in the labour market, are the main determinants of wage inequality. Ce document exploite les données de l'Évaluation des compétences des adultes (PIAAC) pour tenter de mieux comprendre le lien entre les compétences cognitives mesurées (le niveau de compétence), le niveau de formation (dans le cadre institutionnel) et les résultats sur le marché du travail. Après la présentation de statistiques descriptives sur le degré de dispersion des distributions des niveaux de compétence et des revenus, le document montre que la corrélation internationale entre ces deux dimensions d’inégalité est très faible et, le cas échéant, négative. Le document présente ensuite des estimations de l'incidence à la fois du niveau de compétence et du niveau de formation dans le cadre institutionnel à différents points de la distribution des revenus. Le niveau de formation dans le cadre institutionnel s’avère avoir une incidence plus importante sur l'inégalité, les rendements de l'éducation étant en général bien plus élevés dans la partie supérieure de la distribution que dans sa partie inférieure. Les rendements du niveau de compétence présentent, en revanche, un profil beaucoup plus plat. Ce constat concorde avec le fait que le PIAAC évalue des compétences plutôt générales, tandis qu’au sommet de la distribution, le marché du travail récompense des connaissances spécialisées nécessairement acquises dans l'enseignement supérieur et universitaire. Enfin, un exercice de décomposition montre que les effets de composition ne sont en mesure d'expliquer qu’un nombre très limité des différences d'inégalité des revenus observées entre les pays. Ce constat laisse penser qu’en façonnant la manière dont les caractéristiques personnelles sont récompensées sur le marché du travail, les institutions économiques sont les principaux déterminants de l'inégalité des revenus.

Suggested Citation

  • Marco Paccagnella, 2015. "Skills and Wage Inequality: Evidence from PIAAC," OECD Education Working Papers 114, OECD Publishing.
  • Handle: RePEc:oec:eduaab:114-en
    DOI: 10.1787/5js4xfgl4ks0-en
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    File URL: https://doi.org/10.1787/5js4xfgl4ks0-en
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    Cited by:

    1. Sonja Jovicic, 2016. "Wage inequality, skill inequality, and employment: evidence and policy lessons from PIAAC," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-26, December.
    2. Mane, Ferran & Miravet, Daniel, 2016. "Using the job requirements approach and matched employer-employee data to investigate the content of individuals' human capital," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 49(2), pages 133-155.
    3. Stijn Broecke & Glenda Quintini & Marieke Vandeweyer, 2018. "Wage Inequality and Cognitive Skills: Reopening the Debate," NBER Chapters, in: Education, Skills, and Technical Change: Implications for Future US GDP Growth, pages 251-286, National Bureau of Economic Research, Inc.
    4. Stijn Broecke, 2016. "Do skills matter for wage inequality?," IZA World of Labor, Institute of Labor Economics (IZA), pages 232-232, February.
    5. John P. Martin, 2018. "Skills for the 21st Century: Findings and Policy Lessons from the OECD Survey of Adult Skills," Working Papers 201803, Geary Institute, University College Dublin.
    6. Lorenzo Cappellari & Paolo Castelnovo & Daniele Checchi & Marco Leonardi, 2017. "Skilled or Educated? Educational Reforms, Human Capital, and Earnings," Research in Labor Economics, in: Solomon W. Polachek & Konstantinos Pouliakas & Giovanni Russo & Konstantinos Tatsiramos (ed.), Skill Mismatch in Labor Markets, volume 45, pages 173-197, Emerald Publishing Ltd.
    7. Frank Levy, 2017. "Comments," NBER Chapters, in: Education, Skills, and Technical Change: Implications for Future US GDP Growth, pages 287-292, National Bureau of Economic Research, Inc.
    8. Perry Anja & Rammstedt Beatrice, 2016. "The Research Data Center PIAAC at GESIS," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(5), pages 581-593, October.
    9. Sonja Jovicic, 2015. "Wage Inequality, Skill Inequality, and Employment: Evidence from PIAAC," Schumpeter Discussion Papers SDP15007, Universitätsbibliothek Wuppertal, University Library.
    10. Giuseppe Croce, 2016. "La rincorsa mancata. Istruzione e cambiamento tecnologico in Italia a confronto con le altre economie avanzate," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 2016(106), pages 77-99.

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