Using everyday data to deliver aid more effectively
In Bangladesh, Yale’s Mushfiq Mobarak and his team used machine-learning models applied to mobile phone records to identify the poorest households — faster and at far lower cost than traditional surveys. As global support for large-scale data collection declines, the research highlights how innovative use of existing data can help close information gaps and better target assistance.
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