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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, Instituto de Investigaciones Económicas, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 0(1-2), pages 53-72, January-D.
    • Handle: RePEc:akh:journl:556
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    File URL: https://revistas.unlp.edu.ar/Economica/article/view/5496/4501
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    Cited by:

    1. 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.
    2. Patrinos, Harry Anthony & Rivera, Angelica, 2025. "Education and Earnings in Arkansas," GLO Discussion Paper Series 1621, Global Labor Organization (GLO).
    3. World Bank & UNESCO, 2023. "Education Finance Watch 2023," World Bank Publications - Reports 40610, The World Bank Group.
    4. Psacharopoulos,George & Collis,Victoria & Patrinos,Harry Anthony & Vegas,Emiliana, 2020. "Lost Wages : The COVID-19 Cost of School Closures," Policy Research Working Paper Series 9246, The World Bank.
    5. Xuan Hoang, Trung, 2024. "The Long-Term and Gender-Equalizing Impacts of the Islamic Republic of Iran-Iraq War in 1980–88 on School Access and Labor Market Performance," Policy Research Working Paper Series 10691, The World Bank.
    6. 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.
    7. repec:aep:anales:4523 is not listed on IDEAS
    8. 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.

    More about this item

    Keywords

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    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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