We investigate the accuracy of ex ante assessments of vulnerability to poverty using cross-sectional data and panel … vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and … high mobility. -- vulnerability ; poverty ; ROC ; German panel data …

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 …

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 … models to predict poverty under these different scenarios. It finds that the quality of predictions and the choice of the …

We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and … vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and … high mobility in and out of poverty. …

Poverty statistics are conventionally compiled using data from household income and expenditure survey or living … standards survey. This study examines an alternative approach in estimating poverty by investigating whether readily available … geospatial data can accurately predict the spatial distribution of poverty in Thailand. In particular, geospatial data examined …