Predicting Inequality of Opportunity and Poverty in India Using Machine Learning

Erscheinungsjahr 2025
ISBN: 978-981-962543-7
Verlag: Springer Nature Singapore

Buch, Englisch, 169 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 457 g

Reihe: India Studies in Business and Economics

This open-access book combines traditional economic methods with newer machine learning techniques such as regression trees and random forests to analyse data and provide an in-depth analysis of inequality of opportunity and poverty in India. Using data from national surveys and unique sources like night-time satellite images and location data of points of interest, it explores different aspects of inequality and poverty. The book adopts a unique interdisciplinary approach, blending theories and methods from sociology, economics, geography, anthropology, and computer science to explore three key aspects of human well-being: income, health, and education, focusing on regional disparities. It aims to offer practical insights for policymakers and researchers who want to address social and economic inequalities in India.

Zielgruppe

Research

Autoren/Hrsg.

Mehta, Balwant Singh

Dhote, Siddharth

Srivastava, Ravi

Fachgebiete

• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsprognose
• Wirtschaftswissenschaften Volkswirtschaftslehre Wohlfahrtsökonomie
• Wirtschaftswissenschaften Volkswirtschaftslehre Internationale Wirtschaft Entwicklungsökonomie & Emerging Markets
• Wirtschaftswissenschaften Volkswirtschaftslehre Wirtschaftspolitik, politische Ökonomie
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Arbeitsmarkt

Inhaltsverzeichnis

Introduction.- Concept and Measurement of IOp.- Decomposition of Inequality of Opportunity.- Predicting Poverty with Machine Learning and Geospatial Data.- Inequality of Opportunity in Education.- Inequality of Opportunity in Health Care Services.- Conclusion and Way Forward.

Über Autor(innen)

Balwant Singh Mehta is Professor at the Institute for Human Development (IHD), New Delhi, India. He holds a Ph.D. from Jamia Millia Islamia, New Delhi, and postdoctoral in Economics from ICSSR, New Delhi. He has authored 10 books and published over 75 articles, in national and international journals. His primary research area includes employment and labour, poverty, inequality, child well-being, education and technology. In recognition of his scholarly contributions, he was selected as ‘Amy Mahan International Fellow by the UPF, Spain (2010-11); awarded a ‘Research Fellowship by SIRCA, Singapore (2009-10); and selected as an Emerging Researcher by the International Development Research Centre (IDRC), Canada (2009). He has also received alumni status from the International Training Centre of the ILO. Prof Mehta serves as an Associate Editor of (Springer), and regularly contributes opinion pieces and editorials to national dailies.

Ravi Srivastava is Director, Centre for Employment Studies, at Institute for Human Development, New Delhi, India. He was earlier Professor of Economics, and Chairperson, Centre for the Study of Regional Development, Jawaharlal Nehru University, India. He holds a Ph.D. from the University of Cambridge, U.K. His main areas of research and publication include labour and employment, migration, social protection, rural poverty and development, and the informal sector. Prof. Srivastava has published six books, five monographs, more than one hundred and ten papers, and has carried out nearly forty major research projects sponsored by agencies such as UNICEF, ILO, The World Bank, ESRC (UK), UNFPA, University Grants Commission, Indian Council for Social Science Research, Shastri Indo-Canadian Foundation and others.

Siddharth Dhote is Senior Research Associate, at Institute for Human Development, New Delhi, India. He has completed his masters in Development Studies from the International Institute for Social Studies in The Hague. His main research interests focus on social justice, poverty, inequality, employment and labour market.