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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...
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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...
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The paper discusses the main issues related to negative and zero incomes that are relevant for the measurement of poverty. It shows the prevalence of non-positive incomes in high- and middle-income countries, provides an analysis of the sources and structure of these incomes, outlines the...
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