Scalable Targeting of Social Protection: When Do Algorithms Out-Perform Surveys and Community Knowledge?

Emily Aiken, Anik Ashraf, Joshua E. Blumenstock, Raymond P. Guiteras and A. Mushfiq Mobarak

NBER Working Paper 33919, June 2025. Under review. 

Draft (PDF).

Abstract: Innovations in big data and algorithms are enabling new approaches to target interventions at scale. We compare the accuracy of three different systems for identifying the poor to receive benefit transfers --- proxy means-testing, nominations from community members, and an algorithmic approach using machine learning to predict poverty using mobile phone usage behavior --- and study how their cost-effectiveness varies with the scale and scope of the program. We collect mobile phone records from all major telecom operators in Bangladesh and conduct community-based wealth rankings and detailed consumption surveys of 5,000 households, to select the 22,000 poorest households for $300 transfers from 106,000 listed households. While proxy-means testing is most accurate, algorithmic targeting becomes more cost-effective for national-scale programs where large numbers of households have to be screened.  We explore the external validity of these insights using survey data and mobile phone records data from Togo, and cross-country information on benefit transfer programs from the World Bank.

Also available as:

Aiken, E., A. Ashraf, J. Blumenstock, R. Guiteras and A. Mobarak (2025), "Scalable Targeting of Social Protection: When Do Algorithms Out-Perform Surveys and Community Knowledge?", CEPR Discussion Paper No. 20332, https://cepr.org/publications/dp20332. (Gated.)

Emily Aiken, Anik Ashraf, Joshua E. Blumenstock, Raymond P. Guiteras, Ahmed Mushfiq Mobarak, "Scalable Targeting of Social Protection: When Do Algorithms Out-Perform Surveys and Community Knowledge?", CESifo Working Paper No. 11928, June 2025, https://www.ifo.de/en/publications/2025/working-paper/scalable-targeting-social-protection-when-do-algorithms-out-perform. PDF (open).

Media:

"Living in remote areas shouldn’t be a death sentence," Financial Times, 20 August 2025.