Retooling Poverty Targeting Using Out-of-Sample Validation and Machine Learning

Retooling Poverty Targeting Using Out-of-Sample Validation and Machine Learning

Proxy means test (PMT) poverty targeting tools have become common tools for beneficiary targeting and poverty assessment where full means tests are costly. Currently popular estimation procedures for generating these tools prioritize minimization o...

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Bibliographic Details
Main Authors: McBride, Linden, Nichols, Austin
Format: Working Paper
Language:English
en_US
Published: World Bank, Washington, DC 2016
Subjects:
targeting
proxy means testing
poverty
poverty assessment
Online Access:http://documents.worldbank.org/curated/en/2016/10/26839841/retooling-poverty-targeting-using-out-of-sample-validation-machine-learning
http://hdl.handle.net/10986/25166

Internet

http://documents.worldbank.org/curated/en/2016/10/26839841/retooling-poverty-targeting-using-out-of-sample-validation-machine-learning
http://hdl.handle.net/10986/25166

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