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Extracting the Wisdom of Crowds When Information is Shared

38 Pages Posted: 28 Jul 2015 Last revised: 15 Dec 2016

Asa B. Palley

Indiana University - Kelley School of Business

Jack B. Soll

Duke University - Management

Date Written: December 14, 2016

Abstract

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

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

Asa B. Palley (Contact Author)

Indiana University - Kelley School of Business ( email )

1309 East Tenth Street
Indianapolis, IN 47405-1701
United States

Jack B. Soll

Duke University - Management ( email )

Box 90120
Durham, NC 27708-0120
United States
(919) 660-7858 (Phone)

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