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 functions and stochastic dominance analysis based on coverage curves. It finds …

This paper evaluates different methods for nowcasting country-level poverty rates, including methods that apply … methods are evaluated by withholding measured poverty rates and determining how accurately the methods predict the held … 1,000+ variables. This GDP-based approach outperforms all models that predict poverty rates directly, even when the last …

This paper evaluates different methods for nowcasting country-level poverty rates, including methods that apply … methods are evaluated by withholding measured poverty rates and determining how accurately the methods predict the held … on 1,000+ variables. This GDP-based approach outperforms all models that predict poverty rates directly, even when the …

, significant poverty reduction, and relatively little inequality. Using disaggregated provincial-level data of Vietnam from 2002 to … 2010, this study verifies the relationship between sectoral composition of growth and poverty reduction with the … consideration of initial inequality. The estimation results suggest that industrial sector growth is a strong driver of poverty …