Estimating Unfair Inequality in Educational Achievement: Methodology and Application for Unmarried Women in India

ABSTRACT

Education is a fundamental driver of human capital accumulation, playing a critical role in shaping labor market outcomes, earnings, and economic inequality. While previous work decomposed wealth inequality into fair and unfair components, the novelty of this study lies in extending this framework to educational inequality, which is inherently ordinal in NFHS data. Evidence indicates that people care less about inequality in general and more about whether it stems from fair or unfair factors. We propose a parallel methodology to measure and scale fair and unfair inequalities in educational outcomes. We examine the evolution of these inequalities among unmarried women across India and its states. Using NFHS‐4 (2015–16) and NFHS‐5 (2019–21), we construct a pseudo‐panel dataset to assess unfair inequality through equality of opportunity. Our empirical analysis has three parts. First, we quantify fair and unfair educational inequality across 26 Indian states between the two survey rounds. Second, we examine the robustness of our findings using alternative ordinal measures of educational attainment, with results consistently indicating an increase in unfair educational inequality at both national and state levels. Third, we employ Shapley decomposition to identify the relative contribution of individual circumstance factors. Our findings highlight the need for policies that address circumstantial disadvantages faced by unmarried women to promote more equitable educational opportunities.