IDEAS home Printed from https://ideas.repec.org/p/oec/eduaab/114-en.html
   My bibliography  Save this paper

Skills and Wage Inequality: Evidence from PIAAC

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://doi.org/10.1787/5js4xfgl4ks0-en
    Download Restriction: no
    File URL: https://libkey.io/10.1787/5js4xfgl4ks0-en?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Joseph G. Altonji & Charles R. Pierret, 2001. "Employer Learning and Statistical Discrimination," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 313-350.
    2. Lawrence F. Katz & Kevin M. Murphy, 1992. "Changes in Relative Wages, 1963–1987: Supply and Demand Factors," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(1), pages 35-78.
    3. David Card & Thomas Lemieux, 2001. "Can Falling Supply Explain the Rising Return to College for Younger Men? A Cohort-Based Analysis," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(2), pages 705-746.
    4. Miles Corak, 2013. "Income Inequality, Equality of Opportunity, and Intergenerational Mobility," Journal of Economic Perspectives, American Economic Association, vol. 27(3), pages 79-102, Summer.
    5. Hanushek, Eric A. & Schwerdt, Guido & Wiederhold, Simon & Woessmann, Ludger, 2015. "Returns to skills around the world: Evidence from PIAAC," European Economic Review, Elsevier, vol. 73(C), pages 103-130.
    6. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    7. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    8. Freeman R B. & Machin, S. J. & Viarengo, M.G, 2011. "Inequality of Educational Outcomes: International Evidence from PISA," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 11(3).
    9. Francine D. Blau & Lawrence M. Kahn, 2005. "Do Cognitive Test Scores Explain Higher U.S. Wage Inequality?," The Review of Economics and Statistics, MIT Press, vol. 87(1), pages 184-193, February.
    10. Andrea Brandolini & Eliana Viviano, 2016. "Behind and beyond the (head count) employment rate," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 657-681, June.
    11. Dirk Van Damme, 2014. "How Closely is the Distribution of Skills Related to Countries' Overall Level of Social Inequality and Economic Prosperity?," OECD Education Working Papers 105, OECD Publishing.
    12. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    13. John Jerrim & Lindsey Macmillan, 2014. "Income inequality, intergenerational mobility and the Great Gatsby Curve: is education the key?," DoQSS Working Papers 14-18, Quantitative Social Science - UCL Social Research Institute, University College London.
    14. Richard B. Freeman & Stephen Machin & Martina Viarengo, 2010. "Variation in Educational Outcomes and Policies across Countries and of Schools within Countries," NBER Working Papers 16293, National Bureau of Economic Research, Inc.
    15. 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.
    16. Blau, Francine D & Kahn, Lawrence M, 1996. "International Differences in Male Wage Inequality: Institutions versus Market Forces," Journal of Political Economy, University of Chicago Press, vol. 104(4), pages 791-836, August.
    17. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    18. Isabell Koske & Jean-Marc Fournier & Isabelle Wanner, 2012. "Less Income Inequality and More Growth – Are They Compatible? Part 2. The Distribution of Labour Income," OECD Economics Department Working Papers 925, OECD Publishing.
    19. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    20. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2008. "Trends in U.S. Wage Inequality: Revising the Revisionists," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 300-323, May.
    21. Andrea Brandolini & Alfonso Rosolia & Roberto Torrini, 2011. "The distribution of employees’ labour earnings in the European Union: Data, concepts and first results," Working Papers 198, ECINEQ, Society for the Study of Economic Inequality.
    22. Wojciech Kopczuk & Emmanuel Saez & Jae Song, 2010. "Earnings Inequality and Mobility in the United States: Evidence from Social Security Data Since 1937," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(1), pages 91-128.
    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. 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. Cristian Bonavida, 2022. "Lo que hacemos con lo que sabemos. Brechas de género en habilidades y tareas en América Latina," Asociación Argentina de Economía Política: Working Papers 4542, Asociación Argentina de Economía Política.
    5. Stijn Broecke, 2016. "Do skills matter for wage inequality?," IZA World of Labor, Institute of Labor Economics (IZA), pages 232-232, February.
    6. Martin, John P., 2018. "Skills for the 21st Century: Findings and Policy Lessons from the OECD Survey of Adult Skills," IZA Policy Papers 138, Institute of Labor Economics (IZA).
    7. Lorenzo Cappellari & Paolo Castelnovo & Daniele Checchi & Marco Leonardi, 2016. "Skilled or educated? Educational reforms, human capital and earnings," DISCE - Working Papers del Dipartimento di Economia e Finanza def053, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    8. Ujjaini Mukhopadhyay, 2021. "Differential Education Subsidy Policy and Wage Inequality Between Skilled, Semi-skilled and Unskilled Labour: A General Equilibrium Approach," Review of Development and Change, , vol. 26(1), pages 40-62, June.
    9. 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.
    10. Broecke, Stijn & Quintini, Glenda & Vandeweyer, Marieke, 2017. "Explaining international differences in wage inequality: Skills matter," Economics of Education Review, Elsevier, vol. 60(C), pages 112-124.
    11. 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.
    12. Sonja Jovicic, 2015. "Wage Inequality, Skill Inequality, and Employment: Evidence from PIAAC," Schumpeter Discussion Papers SDP15007, Universitätsbibliothek Wuppertal, University Library.
    13. 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.

    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. Pallab Ghosh & Jae Lee, 2016. "Decomposition of Changes in Korean Wage Inequality, 1998–2007," Journal of Labor Research, Springer, vol. 37(1), pages 1-28, March.
    2. Pallab Kumar Ghosh & Jae Yoon Lee, 2016. "Decomposition of Changes in Korean Wage Inequality, 1998–2007," Journal of Labor Research, Springer, vol. 37(1), pages 1-28, March.
    3. 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.
    4. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    5. Shantanu Khanna & Deepti Goel & René Morissette, 2016. "Decomposition analysis of earnings inequality in rural India: 2004–2012," IZA Journal of Labor & Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-26, December.
    6. Henry S Farber & Daniel Herbst & Ilyana Kuziemko & Suresh Naidu, 2021. "Unions and Inequality over the Twentieth Century: New Evidence from Survey Data," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(3), pages 1325-1385.
    7. Koomen, Miriam & Backes-Gellner, Uschi, 2022. "Occupational tasks and wage inequality in West Germany: A decomposition analysis," Labour Economics, Elsevier, vol. 79(C).
    8. Giangregorio Luca & Fana Marta, 2021. "The structure of the labour market and wage inequality using RIF-OLS: the Italian case," JRC Working Papers on Labour, Education and Technology 2021-11, Joint Research Centre.
    9. Thomas Grandner & Dieter Gstach, 2015. "Decomposing wage discrimination in Germany and Austria with counterfactual densities," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(1), pages 49-76, February.
    10. Broecke, Stijn & Quintini, Glenda & Vandeweyer, Marieke, 2017. "Explaining international differences in wage inequality: Skills matter," Economics of Education Review, Elsevier, vol. 60(C), pages 112-124.
    11. Valentine Fays & Benoît Mahy & François Rycx, 2023. "Wage differences according to workers' origin: The role of working more upstream in GVCs," LABOUR, CEIS, vol. 37(2), pages 319-342, June.
    12. Huong Thu Le & Ha Trong Nguyen, 2018. "The evolution of the gender test score gap through seventh grade: new insights from Australia using unconditional quantile regression and decomposition," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-42, December.
    13. 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.
    14. Michel Lubrano & Abdoul Aziz Junior Ndoye, 2014. "Bayesian Unconditional Quantile Regression: An Analysis of Recent Expansions in Wage Structure and Earnings Inequality in the US 1992–2009," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(2), pages 129-153, May.
    15. Verdugo, Gregory, 2014. "The great compression of the French wage structure, 1969–2008," Labour Economics, Elsevier, vol. 28(C), pages 131-144.
    16. Ramos, Raul & Sanromá, Esteban & Simón, Hipólito, 2022. "Collective bargaining levels, employment and wage inequality in Spain," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 375-395.
    17. Ferreira, Francisco H. G. & Firpo, Sergio & Messina, Julián, 2017. "Ageing Poorly? Accounting for the Decline in Earnings Inequality in Brazil, 1995-2012," IZA Discussion Papers 10656, Institute of Labor Economics (IZA).
    18. Zhu, Rong, 2016. "Wage differentials between urban residents and rural migrants in urban China during 2002–2007: A distributional analysis," China Economic Review, Elsevier, vol. 37(C), pages 2-14.
    19. Collischon Matthias, 2019. "Is There a Glass Ceiling over Germany?," German Economic Review, De Gruyter, vol. 20(4), pages 329-359, December.
    20. Sonja C. Kassenboehmer & Mathias G. Sinning, 2014. "Distributional Changes in the Gender Wage Gap," ILR Review, Cornell University, ILR School, vol. 67(2), pages 335-361, April.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:oec:eduaab:114-en. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/deoecfr.html .

    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.