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A decomposition method to evaluate the "paradox of progress", with evidence for Argentina

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  • Walter Sosa Escudero
  • Javier Alejo
  • Leonardo Gasparini
  • Gabriel Montes Rojas

Abstract

The ‘paradox of progress’ is an empirical regularity that associates more education with larger income inequality. Two driving and competing factors behind this phenomenon are the convexity of the ‘Mincer equation’ (that links wages and education) and the heterogeneity in the returns to education, as captured by quantile regressions. We propose a joint least-squares and quantile regression statistical framework to derive a decomposition to evaluate the relative contribution of each explanation. We apply the proposed decomposition strategy to the case of Argentina 1992 to 2015.
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Suggested Citation

  • Walter Sosa Escudero & Javier Alejo & Leonardo Gasparini & Gabriel Montes Rojas, 2021. "A decomposition method to evaluate the "paradox of progress", with evidence for Argentina," Asociación Argentina de Economía Política: Working Papers 4523, Asociación Argentina de Economía Política.
    • Handle: RePEc:aep:anales:4523
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    1. Sebastián Galiani & Rocío Titiunik, 2005. "Changes in the Panamanian Wage Structure: A Quantile Regression Analysis," Económica, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 0(1-2), pages 3-27, January-D.
    2. Aysit Tansel & Fatma Bircan Bodur, 2012. "Wage Inequality and Returns to Education in Turkey: A Quantile Regression Analysis," Review of Development Economics, Wiley Blackwell, vol. 16(1), pages 107-121, February.
    3. Staneva, Anita & Arabsheibani, Reza & Murphy, Philip D., 2010. "Returns to Education in Four Transition Countries: Quantile Regression Approach," IZA Discussion Papers 5210, Institute of Labor Economics (IZA).
    4. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2005. "Rising Wage Inequality: The Role of Composition and Prices," NBER Working Papers 11628, National Bureau of Economic Research, Inc.
    5. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    6. Xulia GonzÂlez & Daniel Miles, 2001. "Wage inequality in a developing country: decrease in minimum wage or increase in education returns," Empirical Economics, Springer, vol. 26(1), pages 135-148.
    7. Ariel Fiszbein & Paula Inés Giovagnoli & Harry Anthony Patrinos, 2007. "Estimating the Returns to Education in Argentina Using Quantile Regression Analysis: 1992-2002," Económica, Instituto de Investigaciones Económicas, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 0(1-2), pages 53-72, January-D.
    8. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    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. José A. F. Machado & José Mata, 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, May.
    11. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
    12. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.
    13. Sattinger, Michael, 1993. "Assignment Models of the Distribution of Earnings," Journal of Economic Literature, American Economic Association, vol. 31(2), pages 831-880, June.
    14. 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.
    15. Moshe Buchinsky, 2001. "Quantile regression with sample selection: Estimating women's return to education in the U.S," Empirical Economics, Springer, vol. 26(1), pages 87-113.
    16. Gabriel Montes-Rojas & Lucas Siga & Ram Mainali, 2017. "Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(3), pages 245-255, September.
    17. Jan Tinbergen, 1972. "The Impact Of Education On Income Distribution," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 18(3), pages 255-265, September.
    18. 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.
    19. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    20. Evangelos M. Falaris, 2008. "A Quantile Regression Analysis of Wages in Panama," Review of Development Economics, Wiley Blackwell, vol. 12(3), pages 498-514, August.
    21. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    22. John Ariza & Gabriel Montes-Rojas, 2019. "Decomposition methods for analyzing inequality changes in Latin America 2002–2014," Empirical Economics, Springer, vol. 57(6), pages 2043-2078, December.
    23. repec:bla:revinw:v:18:y:1972:i:3:p:255-65 is not listed on IDEAS
    24. Luis Beccaria & Roxana Maurizio & Gustavo V�zquez, 2015. "Recent decline in wage inequality and formalization of the labour market in Argentina," International Review of Applied Economics, Taylor & Francis Journals, vol. 29(5), pages 677-700, September.
    25. Diego Battistón & Carolina García-Domench & Leonardo Gasparini, 2014. "Could an Increase in Education Raise Income Inequality? Evidence for Latin America," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 51(1), pages 1-39, May.
    26. Francois Bourguignon & Francisco H.G. Ferreira & Nora Lustig, 2005. "The Microeconomics of Income Distribution Dynamics in East Asia and Latin America," World Bank Publications - Books, The World Bank Group, number 14844.
    27. Sergio P. Firpo & Nicole M. Fortin & Thomas Lemieux, 2018. "Decomposing Wage Distributions Using Recentered Influence Function Regressions," Econometrics, MDPI, vol. 6(2), pages 1-40, May.
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    More about this item

    Keywords

    inequality; quantile regression; education;
    All these keywords.

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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