Inequality of Opportunity in Education

Balwant Singh Mehta (), Ravi Srivastava () and Siddharth Dhote ()
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Balwant Singh Mehta: Institute for Human Development
Ravi Srivastava: Institute for Human Development
Siddharth Dhote: Institute for Human Development

Chapter Chapter 5 in Predicting Inequality of Opportunity and Poverty in India Using Machine Learning, 2025, pp 111-133 from Springer

Abstract: Abstract This chapter studies inequality of opportunity in education in India and the key factors contributing these disparities. Using the ex-ante approach and machine learning algorithms, it analyses years of schooling as the outcome variable drawing from Periodic Labour Force Survey (PLFS) data. Input variables include gender, social group, parents’ education and occupation, and geographic region. The results reveal significant educational gap between rural and urban areas, as well as across gender and social groups. Gini coefficient of 0.22 indicate significant educational inequality, with about one-third of it stemming from circumstances beyond an individual’s control. Among all, parental education and geographical location emerge as the primary factors contributing to educational inequality. The study highlight the need for targeted policies to improve educational schools in underserved region, support marginalized communities, and promote gender equality.

Keywords: Educational Inequality; India; Machine Learning; Parental Education; Regional Disparities (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isbchp:978-981-96-2544-4_5

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DOI: 10.1007/978-981-96-2544-4_5

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