标题： 使用机器学习和手机数据的目标定位：阿富汗反贫困干预措施的证据 显示英文标题

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

摘要： 移动电话数据能否改善项目定位？ 通过将阿富汗一项“大规模推动”扶贫计划的丰富调查数据与项目受益人的详细移动电话记录相结合，我们研究了机器学习方法在多大程度上能够准确区分符合项目福利条件的极度贫困家庭和不符合条件的家庭。 我们表明，利用移动电话数据的机器学习方法可以几乎像基于调查的消费和财富衡量指标一样准确地识别极度贫困家庭；并且将基于调查的衡量指标与移动电话数据相结合，可以产生比单一数据源更准确的分类。 显示英文摘要

摘要： 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 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.