We analyze the extent to which simple markets can be used to aggregate disperse information into efficient forecasts of uncertain future events. Drawing together data from a range of prediction contexts, we show that market-generated forecasts are typically fairly accurate, and that they outperform most moderately sophisticated benchmarks. Carefully designed contracts can yield insight into the market's expectations about probabilities, means and medians, and also uncertainty about these parameters. Moreover, conditional markets can effectively reveal the market's beliefs about regression coefficients, although we still have the usual problem of disentangling correlation from causation. We discuss a number of market design issues and highlight domains in which prediction markets are most likely to be useful.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number
10504.
Length: Date of creation: May 2004 Date of revision: Handle: RePEc:nbr:nberwo:10504
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Justin Wolfers & Eric Zitzewitz, 2004.
"Prediction Markets,"
NBER Working Papers
10504, National Bureau of Economic Research, Inc.
[Downloadable!] (restricted)
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Wolfers, Justin & Zitzewitz, Eric, 2004.
"Prediction Markets,"
Research Papers
1854, Stanford University, Graduate School of Business.
[Downloadable!]
Shleifer, Andrei & Vishny, Robert W, 1997.
" The Limits of Arbitrage,"
Journal of Finance,
American Finance Association, vol. 52(1), pages 35-55, March.
[Downloadable!] (restricted)
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