Program Targeting with Machine Learning and Mobile Phone Data: Evidence from an Anti-Poverty Intervention in Afghanistan

@article{Aiken2022ProgramTW,
  title={Program Targeting with Machine Learning and Mobile Phone Data: Evidence from an Anti-Poverty Intervention in Afghanistan},
  author={Emily L. Aiken and Guadalupe Bedoya and Joshua Evan Blumenstock and Aidan Coville},
  journal={ArXiv},
  year={2022},
  volume={abs/2206.11400}
}
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… 

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