Program Targeting with Machine Learning and Mobile Phone Data

• Tác giả: Emily L Aiken
• Ngôn ngữ: eng
• Ký hiệu phân loại: 006.68 Programs
• Thông tin xuất bản: World Bank, Washington, DC, 2023
• Bộ sưu tập: Tài liệu truy cập mở
• ID: 322941
• Chủ đề: 1. CASH TRANSFERS; 2. MACHINE LEARNING; 3. RECIPIENTS; 4. TARGETING; 5. TARGETING ULTRA-POOR HOUSEHOLD DATA

Tóm tắt

 Can mobile phone data improve program targeting By combining rich survey data from the baseline of a "big push" anti-poverty program in Afghanistan implemented in 2016 with detailed mobile phone logs from program beneficiaries, this paper studies the extent to which machine learning methods can accurately differentiate ultra-poor households eligible for program benefits from ineligible households. The paper shows 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 phone data produces classifications more accurate than those based on a single data source.