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Nowcasting Global Poverty

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 metho...

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Bibliographic Details
Main Authors: Mahler, Daniel Gerszon, Castaneda Aguilar, R. Andres, Newhouse, David
Language:English
Published: World Bank, Washington, DC 2021
Subjects:
POVERTY
NOWCASTING
MACHINE LEARNING
POVERTY MEASUREMENT
Online Access:http://documents.worldbank.org/curated/undefined/143231637760743360/Nowcasting-Global-Poverty
http://hdl.handle.net/10986/36636

Internet

http://documents.worldbank.org/curated/undefined/143231637760743360/Nowcasting-Global-Poverty
http://hdl.handle.net/10986/36636

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