OLS models are the predominant choice for poverty predictions in a variety of contexts such as proxy-means tests, poverty mapping or cross-survey imputations. This paper compares the performance of econometric and machine learning models in predicting poverty using alternative objective...

Poverty prediction models are used by economists to address missing data issues in a variety of contexts such as poverty profiling, targeting with proxy-means tests, cross-survey imputations such as poverty mapping, or vulnerability analyses. Based on the models used by this literature, this...

The idea that high levels of economic inequality negatively affect the rate and sustainability of economic growth is quite popular in the scientific literature. Therefore, it is usually proposed to take some regulative measures to reduce economic inequality in order to boost economic growth....

Earlier research on poverty failed to provide us with consistent measures of its prevalence across space and time. This is due to the limitations of the available sources and to the difficulty of applying to them the poverty definitions of modern social science. This article discusses different...