Tracking poverty is predicated on the availability of comparable consumption data and reliable price deflators. However, regular series of strictly comparable data are only rarely available. Price deflators are also often missing or disputed. In response, poverty prediction methods that track...

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 in low-income countries is usually measured with large and infrequent household surveys. A challenge is to find methods to measure poverty more frequently. The objective of this study is to test a method for predicting poverty, based upon a statistical model utilizing consumption surveys...

The at-risk-of-poverty rate (AROP) is one of the three indicators used for monitoring progress towards the Europe 2020 poverty and social exclusion reduction target. Timeliness of this indicator is crucial for monitoring of the social situation and of the effectiveness of tax and benefit...