machine learning

Mapping the dimensions of poverty through big data, socioeconomic surveys and machine learning in Cambodia

We use new big data sources, the Cambodia Socio-Economic Survey, and machine learning methods to predict and map multidimensional poverty in Cambodia.

Lack of Global Convergence and the Formation of Multiple Welfare Clubs across Countries: An Unsupervised Machine Learning Approach

The paper incorporates some recent developments from the unsupervised machine learning literature to re-evaluate the cross-country convergence hypothesis in a context beyond GDP. The application of a distribution-based clustering algorithm suggests the formation of three local convergence clubs.