India Studies in Business and Economics Predicting Inequality of Opportunity Poverty Using Machine Learning

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. 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. 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.