Hunter York
Emmanuela Gakidou, University of Washington, Seattle
Educational attainment is an essential social determinant of health outcomes. There have been several attempts to characterize the educational composition of countries via school enrollment ratios, censuses, and surveys. While these papers have allowed for comparisons of between-country inequality in access to education, few attempts have been made to produce comprehensive measures of inequalities within countries, and no attempts have been made to produce mean attainment estimates for individuals under 15 years of age. We use a multi-stage modeling process followed by a machine learning algorithm to construct complete time series of modeled distributions of educational attainment. These estimates show that increases in educational attainment and decreases in inequality are ubiquitous, but progress is generally being made at a slower pace for females compared to males. These changes are rooted in increased access to primary education that is not mirrored by increases in secondary and tertiary education.
Presented in Session 8. Economy, Labor Force, Education, & Inequality