38 Pages Posted: 28 Jul 2015 Last revised: 15 Dec 2016
Date Written: December 14, 2016
Using the wisdom of crowds -- combining many individual forecasts to obtain an aggregate estimate -- can be an effective technique for improving forecast accuracy. In practice, however, accuracy is limited by the presence of correlated forecast errors, which often emerge because information is shared. To address this problem, we propose an elicitation procedure in which each respondent is asked to provide both their own best forecast and a guess of the average forecast that will be given by all other respondents. We develop an aggregation method, called pivoting, which separates individual forecasts into shared and private information and then recombines these results in the optimal manner. In several studies, we investigate the method and examine the accuracy of the aggregate forecasts. Overall, the empirical data suggest that the pivoting method provides an effective forecast aggregation procedure that can significantly outperform the simple crowd average.
Keywords: Forecasting, Judgment Aggregation, Wisdom of Crowds, Shared Information
JEL Classification: D83, C53, C91
Suggested Citation: Suggested Citation
Palley, Asa B. and Soll, Jack B., Extracting the Wisdom of Crowds When Information is Shared (December 14, 2016). Available at SSRN: https://ssrn.com/abstract=2636376 or http://dx.doi.org/10.2139/ssrn.2636376