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 …

The at-risk-of-poverty rate is one of the three indicators used for monitoring progress towards the Europe 2020 poverty … policies. However, due to complicated nature of the European Union Statistics on Income and Living Conditions (EU-SILC) poverty …") the current at-risk-of-poverty rate for the European Union (EU) countries based on EU-SILC microdata from a previous …

The at-risk-of-poverty rate is one of the three indicators used for monitoring progress towards the Europe 2020 poverty …, estimates of the number of people at risk of poverty are published with a significant delay. This paper extends and updates … previous work on estimating ('nowcasting') indicators of poverty risk using the tax-benefit microsimulation model EUROMOD. The …

The at-risk-of-poverty rate is one of the three indicators used for monitoring progress towards the Europe 2020 poverty …-SILC), estimates of the number of people at risk of poverty are published with a 2 to 3 year delay. This paper presents a method of … estimating ('nowcasting') the current distribution of income between households, including the at-risk-of-poverty rate, using a …