Eliminating Public Knowledge Biases in Information-Aggregation Mechanisms

We present a novel methodology for identifying public knowledge and eliminating the biases it creates when aggregating information in small group settings. A two-stage mechanism consisting of an information market and a coordination game is used to reveal and adjust for individuals' public info...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:Management Science. - Institute for Operations Research and the Management Sciences, 1954. - 50(2004), 7, Seite 983-994
1. Verfasser: Chen, Kay-Yut (VerfasserIn)
Weitere Verfasser: Fine, Leslie R., Huberman, Bernardo A.
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2004
Zugriff auf das übergeordnete Werk:Management Science
Schlagworte:Game theory Experimental economics Information aggregation Markets Scoring rules Forecasting Information science Philosophy Behavioral sciences Economics mehr... Mathematics Business
Beschreibung
Zusammenfassung:We present a novel methodology for identifying public knowledge and eliminating the biases it creates when aggregating information in small group settings. A two-stage mechanism consisting of an information market and a coordination game is used to reveal and adjust for individuals' public information. A nonlinear aggregation of their decisions then allows for the calculation of the probability of the future outcome of an uncertain event, which can then be compared to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism outperforms both the imperfect market and the best of the participants.
ISSN:15265501