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Why is the rate of return to schooling higher for women than for men?

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  • Dougherty, Christopher

Abstract

The rate of return to schooling appears to be nearly two percentage points greater for females than for males in the National Longitudinal Survey of Youth data set, despite the fact that females tend to earn less, both absolutely and controlling for personal characteristics. A survey of previous studies reporting wage equations reveals that a higher return to female schooling appears to be the norm, although it has not attracted comment. This paper considers various explanations. The most important involves the detrimental impact of discrimination and other factors that cause women to accept wage offers that undervalue their characteristics. It is hypothesized that the better educated is a woman, the more able and willing she is to overcome the se handicaps and compete with men in the labour market, and an index of discrimination disaggregated by years of schooling is constructed using Oaxaca decompositions. This index is indeed negatively correlated with schooling and it accounts for about one half of the differential in the male and female schooling coefficients. Next considered is the possibility that part of the differential could be attributable to male-female differences in the quality of educational attainment, as proxied by their academic outcomes in high school. The NLSY females did indeed perform better than the males, but there is little association between academic attainment and Earnings and allowing for it made no difference to the estimate of the differential in the returns to schooling. The third explanation considered is that women choose to work in sectors where education is relatively highly valued. Controlling for this effect does indeed account for much of the remaining differential.

Suggested Citation

  • Dougherty, Christopher, 2003. "Why is the rate of return to schooling higher for women than for men?," LSE Research Online Documents on Economics 20034, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:20034
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    Cited by:

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    2. Mathias Kuepie & Christophe Nordman, 2011. "Éducation et marchés du travail à Brazzaville et Pointe Noire (Congo-Brazzaville)," Working Papers DT/2011/11, DIAL (Développement, Institutions et Mondialisation).
    3. Claudia Gutierrez, 2008. "Analysis of Poverty and Inequality in Bolivia,1999-2005: A Microsimulation Approach," Development Research Working Paper Series 01/2008, Institute for Advanced Development Studies.
    4. Francesco Pastore & Alina Verashchagina, 2006. "The Distribution of Wages in Belarus," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 48(2), pages 351-376, June.
    5. Christophe Nordman & François Roubaud, 2005. "Reassessing the Gender Wage Gap: Does Labour Force Attachment Really Matter? Evidence from Matched Labour Force and Biographical Surveys in Madagascar," Working Papers 16, ECINEQ, Society for the Study of Economic Inequality.
    6. Mamun, Shamsul Arifeen Khan & Taylor, Brad R. & Nghiem, Son & Rahman, Mohammad Mafizur & Khanam, Rasheda, 2021. "The private returns to education in rural Bangladesh," International Journal of Educational Development, Elsevier, vol. 84(C).
    7. Fleisher, Belton M. & Sabirianova, Klara & Wang, Xiaojun, 2005. "Returns to skills and the speed of reforms: Evidence from Central and Eastern Europe, China, and Russia," Journal of Comparative Economics, Elsevier, vol. 33(2), pages 351-370, June.
    8. repec:ilo:ilowps:423895 is not listed on IDEAS
    9. Francesco Pastore, 2009. "School-to-Work Transitions in Mongolia," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 6(2), pages 245-264, December.
    10. Kuepie, Mathias & Nordman, Christophe J. & Roubaud, François, 2009. "Education and earnings in urban West Africa," Journal of Comparative Economics, Elsevier, vol. 37(3), pages 491-515, September.
    11. Gimpelson, Vladimir & Kapeliushnikov, Rostislav, 2017. "Age and Education in the Russian Labour Market Equation," IZA Discussion Papers 11126, Institute of Labor Economics (IZA).
    12. Amy Y. C. Liu, 2006. "Changing wage structure and education in Vietnam, 1992–98," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 14(4), pages 681-706, October.
    13. Christophe J. Nordman & François Roubaud, 2009. "Reassessing the Gender Wage Gap in Madagascar: Does Labor Force Attachment Really Matter?," Economic Development and Cultural Change, University of Chicago Press, vol. 57(4), pages 785-808, July.
    14. Polachek, Solomon W., 2008. "Earnings Over the Life Cycle: The Mincer Earnings Function and Its Applications," Foundations and Trends(R) in Microeconomics, now publishers, vol. 4(3), pages 165-272, April.
    15. Cid, Alejandro & Ferrés, Daniel, 2010. "The coexistence of Degree-Premium and High-Dropout Rates in the Uruguayan Secondary Education: an Incentives Problem," MPRA Paper 39912, University Library of Munich, Germany.
    16. repec:dau:papers:123456789/7386 is not listed on IDEAS

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    More about this item

    Keywords

    returns to education; wage equations;

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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