Data and Code for: Forecasting the Results of Experiments: Piloting an Elicitation Strategy

Principal Investigator(s): View help for Principal Investigator(s) Stefano DellaVigna, UC Berkeley; Eva Vivalt, Australian National University; Nicholas Otis, UC Berkeley

Version: View help for Version V1

Name	File Type	Size	Last Modified
PP_DataAndCode			02/11/2020 06:17:PM
README.pdf	application/pdf	55.3 KB	04/10/2020 07:21:AM

Project Citation:

DellaVigna, Stefano, Vivalt, Eva, and Otis, Nicholas. Data and Code for: Forecasting the Results of Experiments: Piloting an Elicitation Strategy. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-05-18. https://doi.org/10.3886/E117601V1

Project Description

Summary: 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.

Funding Sources: Alfred P. Sloan Foundation (G-2019-12325)

Scope of Project

JEL Classification:
      C80 Data Collection and Data Estimation Methodology; Computer Programs: General
      C90 Design of Experiments: General
      C93 Field Experiments
      O10 Economic Development: General

Data Type(s): survey data

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Published Versions

V1 [2020-05-18]

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