Aggregation mechanisms for crowd predictions

Stefan Palan (), Jürgen Huber and Larissa Senninger ()
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Jürgen Huber: University of Innsbruck
Larissa Senninger: University of Innsbruck

Experimental Economics, 2020, vol. 23, issue 3, No 8, 788-814

Abstract: Abstract When the information of many individuals is pooled, the resulting aggregate often is a good predictor of unknown quantities or facts. This aggregate predictor frequently outperforms the forecasts of experts or even the best individual forecast included in the aggregation process (“wisdom of crowds”). 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) arithmetic and geometric 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 participants know different sub-sets 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 lets only the best-informed participants generate excess returns.

Keywords: Information aggregation; Asymmetric information; Wisdom of crowds (search for similar items in EconPapers)
JEL-codes: C53 C83 G14 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10683-019-09631-0

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