Pari-mutuel Information Aggregation Mechanisms

Main Article Content

Jordi McKenzie
Jared Bullen

Abstract

A number of experimental studies have found that pari-mutuel markets possess the ability to aggregate information privately held by individuals and therefore act as prediction markets.  However, all previous studies have assumed that information is privately and independently distributed. In real world environments the distribution of information is unlikely to take this form. This paper investigates, experimentally, an information structure in which there is both private and public information. It is found that this structure induces a ‘public knowledge bias’ which limits the market’s ability to aggregate information to the extent that the public information reduces the market’s predictive performance.The authors wish to thank Murali Agastya, Andrew Coleman, Pablo Guillen, Stefan Palan, Charles Plott, Kunal Sengupta, and Robert Slonim for useful comments and technical assistance.  We are also extremely grateful to Katarina Kálovcová and Andreas Ortmann for supplying their Ztree program for use in developing our own.

Article Details

Section
Articles

References

Axelrod, Boris S., Ben J. Kulick, Charles R. Plott, and Kevin A. Roust. 2009. “The Design of Improved Pari-mutuel-Type Information Aggregation Mechanisms: Inaccuracies and the Long-Shot Bias as Disequilibrium Phenomena.” Journal of Economic Behaviour & Organization, 69: 170-181.

Bickhchandri, Sushil., David Hirshleifer, and Ivo Welch. 1992. “A Theory of Fads, Fashion, Custom and Cultural Change as Information Cascades.” Journal of Political Economy, 100: 992-1026.

Chen, Kay-Yut, and Charles R. Plott. 2002. “Information Aggregation Mechanisms: Concept, Design and Implementation for a Sales Forecasting Problem.” California Institute of Technology Social Science Working Paper 1131.

Kálovcová, Katarina, and Andreas Ortmann. 2009. “Understanding the Plott-Witt-Yang Paradox.” Journal of Prediction Markets. 3(3), 33-44.

Milgrom, Paul, and Nancy Stokey. 1982. “Information Trade and Common Knowledge.” Journal of Economic Theory, 26(1): 17-27.

Leigh, Andrew and Justin Wolfers. 2006. “Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets.” Economic Record, 82(258): 325-340.

Leigh, Andrew, Justin Wolfers, and Eric Zitzewitz. 2006. “What do Financial Markets Think of War in Ira?.” NBER Working Paper 9587.

Plott, Charles R., Jorgen Wit, and Winston C. Yang. 2003. “Pari-mutuel Betting Markets as Information Aggregation Devices: Experimental Results.” Economic Theory, 22(2): 311-351.

Ray, Russ. 2006. “Prediction Markets and the Financial ‘Wisdom of Crowds’”. Journal of Behavioural Finance, 7(1): 2-4.

Roust, Kevin A., and Charles R. Plott. 2005. “The Design and Testing of Information Aggregation Mechanisms: A Two-Stage Pari-mutuel IAM.” California Institute of Technology Social Science Working Paper 1245.

Snowberg, Erik, Justin Wolfers, J. and Eric Zitzewitz. 2007. “Partisan Markets on the Economy: Evidence from Prediction Markets and Close Elections.” Quarterly Journal of Economics, 122(2): 807-829.

Spann, Martin, and Bernd Skiera. 2003, “Internet-Based Virtual Stock Markets for Business Forecasting.” Management Science, 49(10): 1310-1326.

Würtz, A. 1997. “A Universal Upper Bound on Power Functions.” UNSW Discussion Paper 97/12, University of New South Wales.