Reliable detection of forecasting skill is slow and resource-intensive. Forecasters need to answer dozens of questions, which may take months or years to resolve. To accelerate this process, we propose the Full Accuracy Score (FAS), a measure that combines the strengths of ground-truth-based...

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...