This paper evaluates different methods for nowcasting country-level poverty rates, including methods that apply statistical learning to large-scale country-level data obtained from the World Development Indicators and Google Earth Engine. The methods are evaluated by withholding measured poverty rates and determining how accurately the methods predict the held-out data. A simple approach that scales the last observed welfare distribution by a fraction...
Voir la suite
INFORMATION
TÉLÉCHARGER
RAPPORT COMPLET
Version officielle du document (peut inclure des signatures etc…)
-
Total Downloads** : 183
*La version texte est une version à reconnaissance optique de caractères non-corrigée. Cette version est fournie uniquement pour accommoder les utilisateurs disposant de connections lentes.