Aggregation Mechanisms for Crowd Predictions
Palan, S., Huber, J., Senninger, L., 2019. “Aggregation mechanisms for crowd predictions”, University of Graz, School of Business, Economics and Social Sciences Working Paper 2019-01.
35 Pages Posted: 6 Jun 2019
Date Written: May 15, 2019
When the information of many individuals is pooled, the resulting aggregate often is a good predictor of unknown quantities or facts (“wisdom of crowds”). This aggregate predictor frequently outperforms the forecasts of experts or even the best individual forecast included in the aggregation process. However, an appropriate aggregation mechanism is considered crucial to reaping the benefits of a “wise crowd”. Of the many possible ways to aggregate individual forecasts, we compare (uncensored and censored) mean and median, continuous double auction market prices and sealed bid-offer call market prices in a controlled experiment. We use an asymmetric information structure where subjects know different subsets of the total information needed to exactly calculate the asset value to be estimated. We find that prices from continuous double auction markets clearly outperform all alternative approaches for aggregating dispersed information and that information is only useful to the best-informed subjects.
Keywords: information aggregation, asymmetric information, wisdom of crowds
JEL Classification: C53, C83, G14
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