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Geographic microtargeting of social assistance with high-resolution poverty maps

Author

Listed:
  • Isabella S. Smythe

    (a School of International and Public Affairs, Columbia University, New York, NY 10027;)

  • Joshua E. Blumenstock

    (b School of Information, University of California, Berkeley, CA 94720)

Abstract

Many antipoverty programs use geographic targeting to prioritize benefits to people living in specific locations. This paper shows that high-resolution poverty maps, constructed with machine learning algorithms from satellite imagery, can improve the geographic targeting of benefits to the poorest members of society. This approach was used by the Nigerian government to distribute benefits to millions of the extreme poor. As high-resolution poverty maps become globally available, these results can inform the design and implementation of social assistance programs worldwide.

Suggested Citation

  • Isabella S. Smythe & Joshua E. Blumenstock, 2022. "Geographic microtargeting of social assistance with high-resolution poverty maps," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(32), pages 2120025119-, August.
    • Handle: RePEc:nas:journl:v:119:y:2022:p:e2120025119
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