Aiken, Emily
[Verfasser:in];
Bellue, Suzanne
[Verfasser:in];
Blumenstock, Joshua
[Verfasser:in];
Karlan, Dean
[Verfasser:in];
Udry, Christopher
[Verfasser:in]
;
National Bureau of Economic Research
Estimating Impact with Surveys versus Digital Traces
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Do non-traditional digital trace data and traditional survey data yield similar estimates of the impact of a cash transfer program? In a randomized controlled trial of Togo's COVID-19 Novissi program, endline survey data indicate positive treatment effects on beneficiary food security, mental health, and self-perceived economic status. However, impact estimates based on mobile phone data - processed with machine learning to predict beneficiary welfare - do not yield similar results, even though related data and methods do accurately predict wealth and consumption in prior cross-sectional analysis in Togo. This limitation likely arises from the underlying difficulty of using mobile phone data to predict short-term changes in wellbeing within a rural population with fairly homogeneous baseline levels of poverty. We discuss the implications of these results for using new digital data sources in impact evaluation