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Estimating the Returns to Education in Argentina Using Quantile Regression Analysis: 1992-2002

Author

Listed:
  • Ariel Fiszbein

    (World Bank)

  • Paula Inés Giovagnoli

    (Center for Distribution, Labor and Social Studies (CEDLAS), UNLP)

  • Harry Anthony Patrinos

    (World Bank)

Abstract

There are countless estimates of the average returns to education which looks at the effect of an additional year of schooling on the conditional mean distribution of salaries. Recent international works suggest that there are variations from the average return to education across the population. That is why in this paper we examine this possibility for the case of Argentina over a ten year period. We estimate returns to schooling at different quantiles of the conditional distribution of wages using quantile regression method. We test whether there is individual heterogeneity in returns to education and find that: over time, while males have higher returns to schooling at the higher quantile, women’s returns are highest at the lowest quantile. The evidence is suggesting that while lower ability women may benefit more from schooling the reverse is true for men. Our findings have potential implications for the expansion of educational opportunities in Argentina.

Suggested Citation

  • Ariel Fiszbein & Paula Inés Giovagnoli & Harry Anthony Patrinos, 2007. "Estimating the Returns to Education in Argentina Using Quantile Regression Analysis: 1992-2002," Económica, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 0(1-2), pages 53-72, January-D.
    • Handle: RePEc:lap:journl:555
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    Cited by:

    1. Fasih,Tazeen & Patrinos,Harry Anthony & Shafiq,M. Najeeb, 2020. "Economic Crises and Returns to University Education in Middle-Income Countries : Stylized Facts and COVID-19 Projections," Policy Research Working Paper Series 9472, The World Bank.
    2. Anuneeta Mitra, 2016. "Education and earning linkages of regular and casual workers in India: a quantile regression approach," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 18(1), pages 147-174, October.
    3. Psacharopoulos, George & Collis, Victoria & Patrinos, Harry Anthony & Vegas, Emiliana, 2020. "Lost Wages: The COVID-19 Cost of School Closures," GLO Discussion Paper Series 548, Global Labor Organization (GLO).
    4. Javier Alejo & Leonardo Gasparini & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2024. "A decomposition method to evaluate the ‘paradox of progress’, with evidence for Argentina," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 22(2), pages 453-472, June.
    5. Chuang, Yih-chyi & Lai, Wei-wen, 2010. "Heterogeneity, comparative advantage, and return to education: The case of Taiwan," Economics of Education Review, Elsevier, vol. 29(5), pages 804-812, October.

    More about this item

    Keywords

    Returns to schooling; wages; quantile regressions;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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