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Prediction Markets
Open accessAbstract
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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“Prediction markets have also been successfully used in several other fields such as sports, entertainment, and politics ( 25 , 59-62 ).”
From Evaluating replicability of laboratory experiments in economics (2016) · cites this paper as [59]
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Cites
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779
Shleifer, A., & Vishny, R. W. (1997) · The Journal of Finance · doi:10.1111/j.1540-6261.1997.tb03807.x · Cited by 5,291
RUBINSTEIN, M. (1994) · The Journal of Finance · doi:10.1111/j.1540-6261.1994.tb00079.x · Cited by 1,752
Forecasting: theory and practice
Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babaï, M. Z., Barrow, D. K., Taieb, S. B., Bergmeir, C., Bessa, R. J., Bijak, J., Boylan, J. E., et al. (2022) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2021.11.001 · Cited by 1,187
Anomalies: Parimutuel Betting Markets: Racetracks and Lotteries
Thaler, R. H., & Ziemba, W. T. (1988) · Journal of Economic Perspectives · doi:10.1257/jep.2.2.161 · Cited by 621
Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets
Plott, C. R., & Sunder, S. (1988) · Econometrica · doi:10.2307/1911360 · Cited by 608
Repugnance as a Constraint on Markets
Roth, A. E. (2007) · The Journal of Economic Perspectives · doi:10.1257/jep.21.3.37 · Cited by 580
Plott, C. R., & Sunder, S. (1982) · Journal of Political Economy · doi:10.1086/261084 · Cited by 565
Combinatorial Information Market Design
Hanson, R. D. (2003) · Inf. Syst. Frontiers · doi:10.1023/a:1022058209073 · Cited by 554
Wishes, expectations and actions: a survey on price formation in election stock markets
Forsythe, R. S., Rietz, T. A., & Ross, T. W. (1999) · Journal of Economic Behavior & Organization · doi:10.1016/s0167-2681(99)00027-x · Cited by 283
Research works printed but not linked: 1
- Athanasoulis Stefano, 1999, Economic Policy Review., 5, 21
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Metadata
- Authors
- Wolfers, J., & Zitzewitz, E.
- Affiliations
- National Bureau of Economic Research (US)
- Stanford University (US)
- ORCID
- Wolfers, Justin
- Venue
- Journal of Economic Perspectives
- Publisher
- American Economic Association
- Published
- 2004-05-01
- Volume
- 18
- Issue
- 2
- Pages
- 107-126
- ISSN
- 0895-3309 (ISSN-L)
- OpenAlex
- W4256232447
- Cited by
- 889
- References
- 17
- Citations by year
- 2026: 85 · 2025: 36 · 2024: 33 · 2023: 31 · 2022: 44 · 2021: 31 · 2020: 28 · 2019: 33 · 2018: 42 · 2017: 39 · 2016: 25 · 2015: 44 · 2014: 42 · 2013: 56 · 2012: 67
- FWCI
- 43.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journal of Economic Perspectives (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Sports Analytics and Performance
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- prediction markets, information aggregation, forecast accuracy, market design, regression coefficients, correlation versus causation, probability elicitation
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