IDEAS home Printed from https://ideas.repec.org/a/eme/jespps/jes-05-2022-0313.html
   My bibliography  Save this article

Tertiary education for all and wage inequality: policy insights from quantile regression

Author

Listed:
  • Corrado Andini

Abstract

Purpose - The aim is to assess how a policy of tertiary education for all affects the shape of the unconditional earnings distribution. Design/methodology/approach - The paper discusses the quantile-regression literature looking at the link between education and wage inequality, also proving new evidence based on unconditional quantile regressions. Findings - The findings support the idea that a policy of tertiary education for all increases the overall level of wage inequality. Research limitations/implications - The research has implications for public policy and administration. Among the limitations, the paper does not deal with distributional aspects related to other outcomes (e.g. health outcomes) of the policy of interest. Practical implications - The analysis highlights a series of potential government interventions aimed at reducing the wage-inequality externalities of the policy of interest. Social implications - A policy of tertiary education for all, by itself, is not useful to fight wage inequality. Originality/value - This paper belongs to the small group of studies using unconditional quantile regressions to study the link between education and wage inequality. It is the first study specifically looking at the distributional effects of a policy of tertiary education for all.

Suggested Citation

  • 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.
    • Handle: RePEc:eme:jespps:jes-05-2022-0313
    DOI: 10.1108/JES-05-2022-0313
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/JES-05-2022-0313/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://www.emerald.com/insight/content/doi/10.1108/JES-05-2022-0313/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1108/JES-05-2022-0313?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    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. Budría, Santiago & Moro-Egido, Ana I., 2008. "Education, educational mismatch, and wage inequality: Evidence for Spain," Economics of Education Review, Elsevier, vol. 27(3), pages 332-341, June.
    3. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4, National Bureau of Economic Research, Inc.
    4. Joop Hartog & Pedro Pereira & Jose Vieira, 2001. "Changing returns to education in Portugal during the 1980s and early 1990s: OLS and quantile regression estimators," Applied Economics, Taylor & Francis Journals, vol. 33(8), pages 1021-1037.
    5. 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.
    6. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
    7. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    8. Barro, Robert J. & Lee, Jong Wha, 2013. "A new data set of educational attainment in the world, 1950–2010," Journal of Development Economics, Elsevier, vol. 104(C), pages 184-198.
    9. Amanda Gosling & Stephen Machin & Costas Meghir, 2000. "The Changing Distribution of Male Wages in the U.K," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 67(4), pages 635-666.
    10. Corrado Andini, 2010. "A dynamic Mincer equation with an application to Portuguese data," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2091-2098.
    11. Buchinsky, Moshe, 1994. "Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression," Econometrica, Econometric Society, vol. 62(2), pages 405-458, March.
    12. 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.
    13. Javier Alejo & Maria Florencia Gabrielli & Walter Sosa-Escudero, 2014. "The Distributive Effects of Education: An Unconditional Quantile Regression Approach," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 29(1), pages 53-76, April.
    14. Bernd Fitzenberger & Claudia Kurz, 2003. "New insights on earnings trends across skill groups and industries in West Germany," Empirical Economics, Springer, vol. 28(3), pages 479-514, July.
    15. Corrado Andini, 2010. "Within-groups wage inequality and schooling: further evidence for Portugal," Applied Economics, Taylor & Francis Journals, vol. 42(28), pages 3685-3691.
    16. Paolo Naticchioni & Andrea Ricci & Emiliano Rustichelli, 2010. "Far away from a skill-biased change: falling educational wage premia in Italy," Applied Economics, Taylor & Francis Journals, vol. 42(26), pages 3383-3400.
    17. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    18. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    19. Fersterer, Josef & Winter-Ebmer, Rudolf, 2003. "Are Austrian returns to education falling over time?," Labour Economics, Elsevier, vol. 10(1), pages 73-89, February.
    20. Lee, Sokbae, 2007. "Endogeneity in quantile regression models: A control function approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1131-1158, December.
    21. Corrado Andini, 2009. "Wage Bargaining and the (Dynamic) Mincer Equation," Economics Bulletin, AccessEcon, vol. 29(3), pages 1842-1849.
    22. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    23. Jacob A. Mincer, 1974. "Schooling and Earnings," NBER Chapters, in: Schooling, Experience, and Earnings, pages 41-63, National Bureau of Economic Research, Inc.
    24. Omar Arias & Walter Sosa-Escudero & Kevin F. Hallock, 2001. "Individual heterogeneity in the returns to schooling: instrumental variables quantile regression using twins data," Empirical Economics, Springer, vol. 26(1), pages 7-40.
    25. Chernozhukov, Victor & Hansen, Christian & Jansson, Michael, 2007. "Inference approaches for instrumental variable quantile regression," Economics Letters, Elsevier, vol. 95(2), pages 272-277, May.
    26. Corrado Andini, 2007. "The total impact of schooling on within-groups wage inequality in Portugal," Applied Economics Letters, Taylor & Francis Journals, vol. 15(2), pages 85-90.
    27. Giorgio Brunello & Margherita Fort & Guglielmo Weber, 2009. "Changes in Compulsory Schooling, Education and the Distribution of Wages in Europe," Economic Journal, Royal Economic Society, vol. 119(536), pages 516-539, March.
    28. Chernozhukov, Victor & Hansen, Christian, 2006. "Instrumental quantile regression inference for structural and treatment effect models," Journal of Econometrics, Elsevier, vol. 132(2), pages 491-525, June.
    29. Fatih Guvenen, 2009. "An Empirical Investigation of Labor Income Processes," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(1), pages 58-79, January.
    30. 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.
    31. José A. F. Machado & José Mata, 2001. "Earning functions in Portugal 1982-1994: Evidence from quantile regressions," Empirical Economics, Springer, vol. 26(1), pages 115-134.
    32. Ghosh, Pallab Kumar, 2014. "The contribution of human capital variables to changes in the wage distribution function," Labour Economics, Elsevier, vol. 28(C), pages 58-69.
    33. Thomas Lemieux, 2006. "Increasing Residual Wage Inequality: Composition Effects, Noisy Data, or Rising Demand for Skill?," American Economic Review, American Economic Association, vol. 96(3), pages 461-498, June.
    34. Moshe Buchinsky, 2001. "Quantile regression with sample selection: Estimating women's return to education in the U.S," Empirical Economics, Springer, vol. 26(1), pages 87-113.
    35. Corrado Andini, 2007. "Returns to education and wage equations: a dynamic approach," Applied Economics Letters, Taylor & Francis Journals, vol. 14(8), pages 577-579.
    36. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    37. Colm Harmon & Hessel Oosterbeek & Ian Walker, 2003. "The Returns to Education: Microeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 17(2), pages 115-156, April.
    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. Choi, Seonkyung & Li, Huihui & Ogawa, Keiichi, 2023. "Upper secondary vocational education and decent work in Indonesia: A gender comparison," International Journal of Educational Development, Elsevier, vol. 101(C).
    2. Petra Sauer & Philippe Van Kerm & Daniele Checchi, 2023. "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.

    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. 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. Andini, Corrado, 2009. "How Fast Do Wages Adjust to Human-Capital Productivity? Dynamic Panel-Data Evidence from Belgium, Denmark and Finland," IZA Discussion Papers 4583, Institute of Labor Economics (IZA).
    3. Balestra, Simone & Backes-Gellner, Uschi, 2017. "Heterogeneous returns to education over the wage distribution: Who profits the most?," Labour Economics, Elsevier, vol. 44(C), pages 89-105.
    4. Andersson, Roland & Nabavi Larijani, Pardis & Wilhelmsson, Mats, 2013. "The impact of vocational education and training on income in Sweden," Working Paper Series 13/4, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    5. 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.
    6. Bartelsman, Eric & Dobbelaere, Sabien & Peters, Bettina, 2013. "Allocation of Human Capital and Innovation at the Frontier: Firm-Level Evidence on Germany and the Netherlands," IZA Discussion Papers 7540, Institute of Labor Economics (IZA).
    7. 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.
    8. 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.
    9. Angel de la Fuente & Antonio Ciccone, 2003. "Human capital in a global and knowledge-based economy," UFAE and IAE Working Papers 562.03, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    10. Tushar Agrawal, 2011. "Returns to education in India: Some recent evidence," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2011-017, Indira Gandhi Institute of Development Research, Mumbai, India.
    11. Paolo Naticchioni & Andrea Ricci & Emiliano Rustichelli, 2007. "Wage Structure, Inequality And Skill-Biased Change: Is Italy An Outlier?," Quaderni del Dipartimento di Economia, Finanza e Statistica 38/2007, Università di Perugia, Dipartimento Economia.
    12. Corrado Andini, 2010. "A dynamic Mincer equation with an application to Portuguese data," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2091-2098.
    13. Santiago Budría, 2011. "Are Educational Mismatches Responsible for the ‘Inequality Increasing Effect’ of Education?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 102(3), pages 409-437, July.
    14. 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.
    15. Derick R. C. Almeida & João A. S. Andrade & Adelaide Duarte & Marta Simões, 2022. "Human Capital Disparities and Earnings Inequality in The Portuguese Private Labour Market," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(1), pages 145-167, January.
    16. Anuneeta Mitra, 2016. "Education and earning linkages of regular and casual workers in India: a quantile regression approach," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 18(1), pages 147-174, October.
    17. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    18. Gurleen Popli & Okan Yılmaz, 2017. "Educational Attainment and Wage Inequality in Turkey," LABOUR, CEIS, vol. 31(1), pages 73-104, March.
    19. Selahattin Güriş & Ebru Çağlayan, 2012. "Returns to education and wages in Turkey: robust and resistant regression," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(5), pages 1407-1416, August.
    20. Corrado Andini, 2010. "Within-groups wage inequality and schooling: further evidence for Portugal," Applied Economics, Taylor & Francis Journals, vol. 42(28), pages 3685-3691.

    More about this item

    Keywords

    Education policy; Wage inequality; Quantile regression; I24; I28; J31; C21;
    All these keywords.

    JEL classification:

    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    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:eme:jespps:jes-05-2022-0313. 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: Emerald Support (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.