TY  - RPRT
        AU  - Riedmiller, Sebastian
AU  - Sutter, Matthias
AU  - Tonke, Sebastian
        TI  - Designing Effective Interventions
        PY  - 2025/Nov/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 18273
        UR  - https://www.iza.org/publications/dp18273
        AB  - 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.
        KW  - context dependency
KW  - heterogeneous treatment effects
KW  - intervention design
KW  - experiment
        ER  -