Abstract
This paper demonstrates that education can be an effective policy instrument to mitigate economic inequality among marginalized gender and identity groups in developing countries. We characterize the disparities in economic opportunity between gender, identity (ethnic or religious), and gender-by-identity groups in relation to disparities in educational attainment. We employ a Oaxaca-Blinder decomposition to determine the extent to which these gaps are attributable to education inequality. The analysis covers 18 countries from Eastern Europe, Latin America, and Sub Saharan Africa. We show that about half of the identity group disparities are explained by gaps in education and only about 15–17% of the gender employment and wage gap. However, on aggregate, eliminating identity group and gender education disparities, relative to the most advantaged, yield substantial increases in the total number of salaried workers and in the total wage bill.
The authors are grateful for helpful comments and discussions from John Gillies, Steve Luke, Allison Marier, Pauline Rose and participants at the 60th Comparative and International Education Society Conference.
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Notes
- 1.
Income Gini coefficient data are drawn Standardized World Income Inequality Database (SWIID) and education Gini coefficients are extracted from the Education Policy and Data Center’s (EPDC) Education Inequality and Conflict (EIC) database.
- 2.
- 3.
For a survey of the returns to schooling literature in the United States refer to Card (1999). For a review of the international returns to schooling literature, see Cohn and Addison (1998), Psacharopoulos and Hinchliffe (1973), Psacharopoulos (1981, 1985, 1994), and Psacharopoulos and Patrinos (2004).
- 4.
For the purposes of this paper, we will refer to the parameter difference portion of the Oaxaca-Blinder decomposition as the ‘discrimination’ effect since this particular parameter is of secondary importance to our argument.
- 5.
Ethnic groups in Bolivia, Guatemala, Mexico, and Peru are identified as Indigenous or Non-Indigenous. Groups in Paraguay are determined based on main spoken language. Groups in Brazil are based on race.
- 6.
We follow definitions used in the IPUMS data where education attainment is defined as: completed less than primary school, completed primary school, completed secondary school, and completed postsecondary school.
- 7.
Monthly wages are measured net of income taxes and converted to 2010 PPP dollars.
- 8.
- 9.
Refer to Figures A.1a, A.1b, and A.1c in the Appendix for exact proportional ethnic or religious breakdowns, by country.
- 10.
Please refer to the “STEP skills measurement surveys: Innovative tools for assessing skills” World Bank Discussion paper for more information on the sample and instrument design.
- 11.
We rely on the International Standard Classification of Education (ISCED) as published by the UNESCO Institute of Statistics (UIS) to determine education completion levels in each country.
- 12.
This is mostly due to differences in the nature of economic activity between the different regions. Sub Saharan countries tend to report a relatively high labor force participation because of a high rate of participation in unpaid agricultural work, which is not as prevalent in other regions.
- 13.
Because the decomposition technique requires only two groups to be compared at a time, we iterate through all pairwise combinations comparing the most educated ethnic/religious group in a given country with every other ethnic/religious group; the same goes for the gender-by-ethnic/religious group analysis.
- 14.
Highest level of education completed, less than primary, is the reference category.
- 15.
The foregone number of women in salaried employment are calculated as the percentage point gain in salaried employment among women multiplied by the total number of adult women in each country.
- 16.
As a specific example, in South Africa, we show that the opportunity cost of maintaining is about 1.3 million potential salaried workers and 116 billion dollars (PPP) in foregone earnings.
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Omoeva, C., Moussa, W., Gale, C. (2018). The Economic Costs of Educational Inequality in Developing Countries. In: BenDavid-Hadar, I. (eds) Education Finance, Equality, and Equity. Education, Equity, Economy, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-90388-0_10
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