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Human Capital and Economic Growth: A Quantile Regression Approach

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  • Miles, W.

Abstract

A number of previous studies (Barro and Sala-i-Martin, Grier) have attempted to gauge the differential impact of regressors such as human capital and investment on the performance of fast and slow growing economies. To date, most such studies impose a single marginal impact on all countries for each such determinant by estimating only one regression coefficient for the whole sample. This paper seeks to determine whether there are different payoffs to fast and slow growing countries from growth determinants, and employs the technique of quantile regression, a method frequently used in many labor and other microeconomic studies. Results indicate that human capital in particular has a larger marginal benefit for countries that have experienced fast growth, but little significant impact on slow growing nations. Policy implications, however, are not clear-cut and require careful consideration.

Suggested Citation

  • Miles, W., 2004. "Human Capital and Economic Growth: A Quantile Regression Approach," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 4(2).
  • Handle: RePEc:eaa:aeinde:v:4:y:2004:i:1_9
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    File URL: http://www.usc.es/economet/reviews/aeid421.pdf
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    References listed on IDEAS

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    1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    2. Raul A. Barreto & Anthony W. Hughes, 2004. "Under Performers and Over Achievers: A Quantile Regression Analysis of Growth," The Economic Record, The Economic Society of Australia, vol. 80(248), pages 17-35, March.
    3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    4. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    5. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 107(2), pages 407-437.
    6. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, May.
    7. Guisan, M.Carmen & Aguayo, Eva & Exposito, Pilar, 2001. "Economic growth and cycles: Cross-country models of education, industry and fertility and international comparisons," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 1(1), pages 9-37.
    8. Levine, Ross & Renelt, David, 1992. "A Sensitivity Analysis of Cross-Country Growth Regressions," American Economic Review, American Economic Association, vol. 82(4), pages 942-963, September.
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    Citations

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    Cited by:

    1. Marta Simões & João Sousa Andrade & Adelaide Duarte, 2012. "Convergence and Growth: Portugal in the EU 1986-2010," GEMF Working Papers 2012-13, GEMF, Faculty of Economics, University of Coimbra.
    2. João Sousa Andrade & Adelaide Duarte & Marta Simões, 2014. "A Quantile Regression Analysis of Growth and Convergence in the EU: Potential Implications for Portugal," Notas Económicas, Faculty of Economics, University of Coimbra, issue 39, pages 48-72, June.
    3. Marcio Laurini, 2007. "A note on the use of quantile regression in beta convergence analysis," Economics Bulletin, AccessEcon, vol. 3(52), pages 1-8.

    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • I2 - Health, Education, and Welfare - - Education
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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