Inequalitrees

Inequalitrees – A Novel Look at Socio-Economic Inequalities using Machine Learning Techniques and Integrated Data Sources

SDSN Bolivia, together with the University of Trento in Italy, the ifo Institute in Germany, and the Institute for Human Development in India won a 4-year, 1.5 million Euro grant from the Fondazione Compagnia di San Paolo to investigate the levels, drivers and spatial distribution of unfair socio-economic inequalities within and between countries, focusing on Bolivia, Germany, India and Italy.

We adopt a multidimensional, interdisciplinary and cross-national approach, by analyzing inequality of opportunity and poverty in three key individual outcomes (education, income and health) in four countries (Bolivia, Germany, India, Italy), and integrating contributions from economics, sociology, geography, and computer science. We will look not only at how different socio-economic conditions shape life opportunities across the countries, but we will also map in detail within-country variations in socioeconomic inequalities. A key innovative feature of our project consists in the application of cutting-edge machine learning techniques to integrate and analyze large scale datasets from various sources, including national and international surveys, administrative and register data, as well as innovative data extracted from satellite images. The combination of various data sources and the application of machine learning and spatial regression methods promise significant progress in understanding the environmental and institutional features that countervail the existence of unfair socio-economic inequalities.

For more information, please visit the project website: https://inequalitrees.eu/