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The distributive effects of education: an unconditional quantile regression approach

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  • 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.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 42933.

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Date of creation: 2011
Date of revision: 2012
Handle: RePEc:pra:mprapa:42933

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Keywords: unconditional quantile regression; income inequality; education; Argentina;

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References

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  1. Buchinsky, Moshe, 1994. "Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression," Econometrica, Econometric Society, Econometric Society, vol. 62(2), pages 405-58, March.
  2. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, Econometric Society, vol. 46(1), pages 33-50, January.
  3. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, Elsevier, vol. 12(4), pages 577-590, August.
  4. Javier Alejo, 2006. "Desigualdad Salarial en el Gran Buenos Aires: Una Aplicación de Regresión por Cuantiles en Microdescomposiciones," CEDLAS, Working Papers, CEDLAS, Universidad Nacional de La Plata 0036, CEDLAS, Universidad Nacional de La Plata.
  5. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521845731.
  6. SErgio Firpo & Nicole M. Fortin & Thomas Lemieux, 2006. "Unconditional Quantile Regressions," Textos para discussão 533, Department of Economics PUC-Rio (Brazil).
  7. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, Econometric Society, vol. 69(5), pages 1127-60, September.
  8. Walter Sosa Escudero & Sergio Petralia, 2010. "“I Can Hear the Grass Grow”: The Anatomy of Distributive Changes in Argentina," CEDLAS, Working Papers, CEDLAS, Universidad Nacional de La Plata 0106, CEDLAS, Universidad Nacional de La Plata.
  9. Martins, Pedro S. & Pereira, Pedro T., 2004. "Does education reduce wage inequality? Quantile regression evidence from 16 countries," Labour Economics, Elsevier, Elsevier, vol. 11(3), pages 355-371, June.
  10. 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., John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
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Cited by:
  1. Cobb-Clark, Deborah A. & Kassenböhmer, Sonja C. & Sinning, Mathias, 2013. "Locus of Control and Savings," IZA Discussion Papers 7837, Institute for the Study of Labor (IZA).

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