Web: http://arxiv.org/abs/2206.11400

June 24, 2022, 1:10 a.m. | Emily Aiken, Guadalupe Bedoya, Joshua Blumenstock, Aidan Coville

cs.LG updates on arXiv.org arxiv.org

Can mobile phone data improve program targeting? By combining rich survey
data from a "big push" anti-poverty program in Afghanistan with detailed mobile
phone logs from program beneficiaries, we study the extent to which machine
learning methods can accurately differentiate ultra-poor households eligible
for program benefits from ineligible households. We show that machine learning
methods leveraging mobile phone data can identify ultra-poor households nearly
as accurately as survey-based measures of consumption and wealth; and that
combining survey-based measures with mobile …

afghanistan arxiv data evidence learning machine machine learning mobile phone

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