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 measurement of multidimensional poverty has been advocated by most welfare scholars and is experiencing a growth in interest, partly explained by controversial debates that have emerged across academics and practitioners. This paper follows one of the least explored approaches-Multiple...

The measurement of multidimensional poverty has been advocated by most welfare scholars and is experiencing a growth in interest, partly explained by controversial debates that have emerged across academics and practitioners. This paper follows one of the least explored approaches -- Multiple...

The increasing growth of forced displacement worldwide has led to the stronger interest of various stakeholders in measuring poverty among refugee populations. However, refugee data remain scarce, particularly in relation to the measurement of income, consumption, or expenditure. This paper...

The increasing growth of forced displacement worldwide has led to the stronger interest of various stakeholders in measuring poverty among refugee populations. However, refugee data remain scarce, particularly in relation to the measurement of income, consumption, or expenditure. This paper...