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The Distributive Effects of Education: An Unconditional Quantile Regression Approach

Author

Listed:
  • Javier Alejo

    (National University of La Plata and CEDLAS)

  • Maria Florencia Gabrielli

    (National University of Cuyo and CONICET)

  • Walter Sosa-Escudero

    (University of San Andrés and CONICET)

Abstract

We use recent quantile regression methods (UQR) to study the distributive effects of education in Argentina. Standard methods usually focus in mean effects, or explore distributive effects by either making stringent modeling assumptions, and/or through counter-factual decompositions that requires several temporal observations. An empirical case shows the flexibility and usefulness of UQR methods. Our application for the case of Argentina shows that educations contributed positively to increased inequality in Argentina, mostly due the effect of strongly heterogeneous effects of education on earnings.

Suggested Citation

  • 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.
    • Handle: RePEc:ila:anaeco:v:29:y:2014:i:1:p:53-76
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    References listed on IDEAS

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    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.
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    3. Walter Sosa Escudero & Sergio Petralia, 2010. "“I Can Hear the Grass Grow”: The Anatomy of Distributive Changes in Argentina," CEDLAS, Working Papers 0106, CEDLAS, Universidad Nacional de La Plata.
    4. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
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    9. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    10. repec:ran:wpaper:824 is not listed on IDEAS
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    Citations

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    Cited by:

    1. 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.
    2. repec:zbw:rwirep:0455 is not listed on IDEAS
    3. Dai Binh Tran & Sasiwimon Warunsiri Paweenawat, 2023. "The returns to education and wage penalty from overeducation: New evidence from Vietnam," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1267-1290, October.
    4. Schreurs, Eloi & Peeters, Ludo & Van Passel, Steven, 2014. "Analyzing the impacts of soil contamination and urban development pressure on farmland values: Unconditional quantile regression estimation," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182741, European Association of Agricultural Economists.
    5. Ebru Çaglayan Akay & Fulden Komuryakan, 2021. "What Do Conditional and Unconditional Quantile Regression Models Tell Us Something Different About Wage Inequality in Turkey?," Journal of Economy Culture and Society, Istanbul University, Faculty of Economics, vol. 64(64), pages 257-277, December.
    6. Deborah A. Cobb-Clark & Sonja C. Kassenboehmer & Mathias G. Sinning, 2013. "Locus of Control and Savings," Ruhr Economic Papers 0455, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    7. Cobb-Clark, Deborah A. & Kassenboehmer, Sonja C. & Sinning, Mathias G., 2016. "Locus of control and savings," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 113-130.
    8. Stefan Schneck, 2018. "The Effect of Self-Employment on Income Inequality," SOEPpapers on Multidisciplinary Panel Data Research 999, DIW Berlin, The German Socio-Economic Panel (SOEP).
    9. Roxana Maurizio & Luis Beccaria & Ana Monsalvo, 2022. "Labour Formalization and Inequality: The Distributive Impact of Labour Formalization in Latin America since 2000," Development and Change, International Institute of Social Studies, vol. 53(1), pages 117-165, January.
    10. Darío Judzik & Lucía Trujillo & Soledad Villafañe, 2017. "A tale of two decades: Income inequality and public policy in Argentina (1996-2014)," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 36(72), October.
    11. Tiiu Paas & Maryna Tverdostup, 2016. "Assessment of labour market returns in the case of gender unique human capital," ERSA conference papers ersa16p157, European Regional Science Association.
    12. Stefan Schneck, 2020. "Self-employment as a source of income inequality," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 10(1), pages 45-64, March.
    13. 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.

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    More about this item

    Keywords

    Unconditional quantile regression; income inequality; education; Argentina;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • D3 - Microeconomics - - Distribution

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