The design of improved parimutuel-type information aggregation mechanisms: Inaccuracies and the long-shot bias as disequilibrium phenomena

Abstract

Information aggregation mechanisms (IAMs) based on parimutuel-type betting systems can aggregate information from complex environments. However, the performance of previously studied systems is imperfect due to possible bluffing, strategic timing of decisions, and "long-shot bias". This paper demonstrates two modifications of parimutuel systems that improve information aggregation performance by removing disinformation due to strategic behavior and by removing misleading disequilibrium behavior. These experiments also demonstrate that "long-shot bias" results from disequilibrium behavior as opposed to being inherent in the psychology of the individuals.

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