Forecasting the Results of Experiments: Piloting an Elicitation Strategy

Stefano DellaVigna, Nicholas Otis and Eva Vivalt

AEA Papers and Proceedings, 2020, vol. 110, 75-79

Abstract: Forecasts of experimental results can clarify the interpretation of research results, mitigate publication bias, and improve experimental designs. We collect forecasts of the results of three Registered Reports preliminarily accepted to the Journal of Development Economics, randomly varying four features: (1) small versus large reference values, (2) whether predictions are in raw units or standard deviations, (3) text-entry versus slider responses, and (4) small versus large slider bounds. Forecasts are generally robust to elicitation features, though wider slider bounds are associated with higher forecasts throughout the forecast distribution. We make preliminary recommendations on how many forecasts should be gathered.

JEL-codes: A14 C53 C90 O10 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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DOI: 10.1257/pandp.20201080

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