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Quantile Regression Evidence on Italian Education Returns

  • Pamela Giustinelli

    ()

    (University of Verona)

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    This study intends to provide some updated empirical evidence on Italian Education Returns through Quantile Regression. Such a methodology enables us to explore the (Quantile Treatment) Effect of Schooling on the (shape of) income conditional distribution (viewed as reflecting the distribution of unobservable ability), and to analyze indirectly the education-ability interaction in the generation of human capital, and its effect on earnings. We obtain estimates displaying a U-shaped pattern, i.e. higher returns at the highest and lowest quantiles of income, suggesting substitution among human capital factors for low ability individuals, and complementarity for high ability earners.

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    File URL: http://www.rivistapoliticaeconomica.it/2004/nov-dic/GiustinelliING.pdf
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    Article provided by SIPI Spa in its journal Rivista di Politica Economica.

    Volume (Year): 94 (2004)
    Issue (Month): 6 (November-December)
    Pages: 49-100

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    Handle: RePEc:rpo:ripoec:v:94:y:2004:i:6:p:49-100
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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.
    2. 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.
    3. Card, David & Krueger, Alan B, 1992. "Does School Quality Matter? Returns to Education and the Characteristics of Public Schools in the United States," Journal of Political Economy, University of Chicago Press, vol. 100(1), pages 1-40, February.
    4. David Card, 2000. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," NBER Working Papers 7769, National Bureau of Economic Research, Inc.
    5. Buchinsky, Moshe, 1995. "Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study," Journal of Econometrics, Elsevier, vol. 68(2), pages 303-338, August.
    6. Hause, John C, 1972. "Earnings Profile: Ability and Schooling," Journal of Political Economy, University of Chicago Press, vol. 80(3), pages S108-S38, Part II, .
    7. Honore, Bo E & Hu, Luojia, 2004. "On the Performance of Some Robust Instrumental Variables Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 30-39, January.
    8. Mwabu, Germano & Schultz, T Paul, 1996. "Education Returns across Quantiles of the Wage Function: Alternative Explanations for Returns to Education by Race in South Africa," American Economic Review, American Economic Association, vol. 86(2), pages 335-39, May.
    9. 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.
    10. Ichino, Andrea & Winter-Ebmer, Rudolf, 1998. "Lower and Upper Bounds of Returns to Schooling: An Exercise in IV estimation with Different Instruments," CEPR Discussion Papers 2007, C.E.P.R. Discussion Papers.
    11. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
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