Forecasting the Results of Experiments: Piloting an Elicitation Strategy
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.
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Document Object Identifier (DOI): 10.3386/w26716
Published: Stefano DellaVigna & Nicholas Otis & Eva Vivalt, 2020. "Forecasting the Results of Experiments: Piloting an Elicitation Strategy," AEA Papers and Proceedings, vol 110, pages 75-79.