prediction of poverty, random forest is rarely used. Comparing out-of-sample predictions in surveys for same year in six … selected by stepwise and Lasso), suggesting that this method could contribute to better poverty predictions. However, none of … the methods consistently provides accurate predictions of poverty over time, highlighting that technical model fitting by …

to use the classification of households based on Leyden poverty line including the differences in goals of credit by 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 …

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 …