Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/334688 
Year of Publication: 
2025
Series/Report no.: 
IZA Discussion Papers No. 18273
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
We provide a systematic framework to diagnose underlying problems and predict intervention effectiveness ex-ante. For this, we developed a parsimonious and generalizable survey tool (anamnesis). Our anamnesis classifies underlying problems along three fundamental diagnoses: awareness, intention, and implementation problems. We validate the framework in an online experiment with 7,500 subjects. We find that (i) intervention effectiveness is heterogeneous across different settings, and (ii) our diagnosis accurately predicts this heterogeneity. On average, predicting a 10%-effect corresponds to an actual effectiveness of 8.92%. We further demonstrate the applicability of our framework to predict heterogeneities in the setting of COVID booster take-up.
Subjects: 
intervention design
heterogeneous treatment effects
context dependency
experiment
JEL: 
C93
D01
D61
D90
Document Type: 
Working Paper

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