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The distributive effects of education: an unconditional quantile regression approach

Author

Listed:
  • Alejo, Javier
  • Gabrielli, Florencia
  • Sosa Escudero, Walter

Abstract

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

Suggested Citation

  • Alejo, Javier & Gabrielli, Florencia & Sosa Escudero, Walter, 2011. "The distributive effects of education: an unconditional quantile regression approach," MPRA Paper 42933, University Library of Munich, Germany, revised 2012.
  • Handle: RePEc:pra:mprapa:42933
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    File URL: https://mpra.ub.uni-muenchen.de/42933/1/MPRA_paper_42933.pdf
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    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. Javier Alejo, 2006. "Desigualdad Salarial en el Gran Buenos Aires: Una Aplicación de Regresión por Cuantiles en Microdescomposiciones," CEDLAS, Working Papers 0036, CEDLAS, Universidad Nacional de La Plata.
    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.
    5. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    6. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.
    7. 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.
    8. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    9. 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.
    10. repec:ran:wpaper:824 is not listed on IDEAS
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    Citations

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    Cited by:

    1. Andini, Corrado, 2017. "Tertiary Education for All and Wage Inequality: Policy Insights from Quantile Regression," IZA Policy Papers 132, Institute for the Study of Labor (IZA).
    2. repec:zbw:rwirep:0455 is not listed on IDEAS
    3. 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.
    4. 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.
    5. repec:col:000093:015844 is not listed on IDEAS
    6. 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.

    More about this item

    Keywords

    unconditional quantile regression; income inequality; education; Argentina;

    JEL classification:

    • D3 - Microeconomics - - Distribution
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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