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

Tasks

This research project investigates the levels and main drivers of two key manifestations of socio-economic inequality, poverty and inequality of opportunity, by adopting a multidimensional, interdisciplinary and cross-national approach. Together with the German Aerospace Center (DLR) and researchers from Italy, India and Bolivia, we study the levels of inequality of opportunity and poverty in educational, income and health-related outcomes in the selected countries. One special focus is on the spatial distribution of inequality of opportunity and poverty within these countries, and the project will try to understand which contextual and institutional characteristics affect the spatial distribution of socio-economic inequalities.

Methods

On the methodological side, the project will investigate how Machine Learning tools can serve to measure poverty and inequality of opportunity both at a small scale level and across countries. In this context, Machine Learning tools will be used to integrate data from different sources, to extract information from non-standard data sources, especially satellite imagery, and to estimate measures of inequality of opportunity and poverty.

Data and other sources

We will use administrative and survey data. Furthermore, we will use information from satellite images and other geospatial data.

Results

The results of this research project will be communicated on a dedicated website.