Understanding Educational Inequality in India: The Impact of Social and Demographic Determinants

Tuesday, 8 July 2025: 10:00
Location: FSE001 (Faculty of Education Sciences (FSE))
Oral Presentation
Mohammed Illias SHEIKH, Independent Researcher, India
Mausam GARG, Independent Researcher, India
Poulomi CHOWDHURY, University of Canberra, Australia
Background: Education has been a long-known important factor for human development, contributing to the betterment of individuals significantly by ameliorating the level of remuneration and living standards through raising skills and self-determination. However, despite its importance, educational inequality persists, particularly in diverse contexts like India, where disparities are shaped by a complex interplay of social and demographic factors. Understanding these inequalities and their underlying causes is essential for addressing the gaps in access to quality education and ensuring more equitable outcomes.

Objective: To assess the changes in educational inequality and the contribution of social and demographic factors.

Data Source: This study utilizes data from three rounds of the National Sample Survey (NSS): the 64th round (2007–2008), the 71st round (2014), and the 75th round (2017–2018).

Methods: The Education Gini index is used to measure the extent of educational inequality over time. The decomposition method analyzes "within-group" and "between-group" inequality. A Tobit regression model is applied to examine the factors influencing average years of schooling (AYS). Finally, a regression-based Shapley decomposition approach identifies the factors contributing to educational inequality.

Results: The AYS improved over the period, reaching 7.7 years by 2018. While educational inequality declined between 2007 and 2018, the Gini index remains concentrated around 38%. The decomposition of the Gini index and Shapley regression approach reveal that the within-group component and rural-urban divide are the primary contributors to educational inequality. The Tobit model highlights that factors such as digital exposure, household occupation, wealth quintile, and household size significantly impact educational attainment.

Conclusion: The study emphasizes the need to improve education in rural areas by focusing on enhancing school infrastructure, promoting e-learning, improving educational quality, and increasing parental involvement.