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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Prediction markets have been successfully used in several other fields such as sports, entertainment, and politics.
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Part of this paper’s reference list could not be split into single entries.
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779 · see citing works
Shleifer, A., & Vishny, R. W. (1997) · The Journal of Finance · doi:10.1111/j.1540-6261.1997.tb03807.x · Cited by 5,291 · see citing works
RUBINSTEIN, M. (1994) · The Journal of Finance · doi:10.1111/j.1540-6261.1994.tb00079.x · Cited by 1,752 · see citing works
Forecasting: theory and practice
Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babai, M. Z., Barrow, D. K., Taieb, S. B., Bergmeir, C., Bessa, R., Bijak, J., Boylan, J., et al. (2020) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2021.11.001 · Cited by 630 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
Plott, C. R., & Sunder, S. (1982) · Journal of Political Economy · doi:10.1086/261084 · Cited by 565 · see citing works
Combinatorial Information Market Design
Hanson, R. D. (2003) · Inf. Syst. Frontiers · doi:10.1023/a:1022058209073 · Cited by 554 · see citing works
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 · see citing works
Internet-Based Virtual Stock Markets for Business Forecasting
Spann, M., & Skiera, B. (2003) · Management Science · doi:10.1287/mnsc.49.10.1310.17314 · Cited by 282 · see citing works
Feedback Effects, Asymmetric Trading, and the Limits to Arbitrage
Edmans, A., Itay Goldstein, B., & Jiang, W. (2015) · American Economic Review · doi:10.1257/aer.20141271 · Cited by 240 · see citing works
Information in Financial Markets and Its Real Effects
Itay Goldstein, B. (2022) · European Finance Review · doi:10.1093/rof/rfac052 · Cited by 223 · see citing works
Do option markets correctly price the probabilities of movement of the underlying asset?
Aı̈t-Sahalia, Y., Wang, Y., & Yared, F. B. (2001) · Journal of Econometrics · doi:10.1016/s0304-4076(00)00091-9 · Cited by 217 · see citing works
The Crash of '87: Was It Expected? The Evidence from Options Markets
Bates, D. S. (1991) · The Journal of Finance · doi:10.2307/2328552 · Cited by 215 · see citing works
Blockchain‐Enabled Data Sharing in Supply Chains: Model, Operationalization, and Tutorial
Wang, Z., Zheng, Z., Jiang, W., & Tang, S. (2021) · Production and Operations Management · doi:10.1111/poms.13356 · Cited by 215 · see citing works
Prediction Markets as Decision Support Systems
Berg, J. E., & Rietz, T. A. (2003) · Information Systems Frontiers · doi:10.1023/a:1022002107255 · Cited by 212 · see citing works
What Do Employees Know? Evidence from a Social Media Platform
Huang, K., Li, M., & Markov, S. (2018) · The Accounting Review · doi:10.2139/ssrn.3225957 · Cited by 206 · see citing works
The Real Power of Artificial Markets
Pennock, D. M., Lawrence, S., Giles, C. L., & Nielsen, F. Å. (2001) · Science · doi:10.1126/science.291.5506.987 · Cited by 185 · see citing works
FinTechs and the Market for Financial Analysis
Grennan, J., & Michaely, R. (2020) · Journal of Financial and Quantitative Analysis · doi:10.1017/s0022109020000721 · Cited by 184 · see citing works
Point Shaving: Corruption in NCAA Basketball
Wolfers, J. J. (2006) · American Economic Review · doi:10.1257/000282806777211757 · Cited by 170 · see citing works
Self-citationWisdom or Madness? Comparing Crowds with Expert Evaluation in Funding the ArtsPreprint
Mollick, E., & Nanda, R. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2443114 · Cited by 145 · see citing works
Has Economic Analysis Improved Regulatory Decisions?
Hahn, R. W., & Tetlock, P. C. (2008) · The Journal of Economic Perspectives · doi:10.1257/jep.22.1.67 · Cited by 145 · see citing works
Can Asset Markets Be Manipulated? A Field Experiment With Racetrack Betting
Camerer, C. F. (1998) · Journal of Political Economy · doi:10.1086/250018 · Cited by 141 · see citing works
Information aggregation and collective intelligence beyond the wisdom of crowds
Kameda, T., Toyokawa, W., & Tindale, R. S. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-022-00054-y · Cited by 139 · see citing works
Qiu, L., & Kumar, S. (2017) · Information Systems Research · doi:10.1287/isre.2016.0679 · Cited by 135 · see citing works
Crowds, Lending, Machine, and Bias
Fu, R., Huang, Y. H., & Singh, P. V. (2021) · Information Systems Research · doi:10.1287/isre.2020.0990 · Cited by 126 · see citing works
Quid Pro Quo? Corporate Returns to Campaign Contributions
Fowler, A., Garro, H., & Spenkuch, J. L. (2019) · The Journal of Politics · doi:10.1086/707307 · Cited by 104 · see citing works
Brexit Uncertainty and Trade Disintegration
Graziano, A., Handley, K., & Limão, N. (2020) · The Economic Journal · doi:10.1093/ej/ueaa113 · Cited by 101 · see citing works
Ottaviani, M., & Sørensen, P. N. (2015) · American Economic Review · doi:10.1257/aer.20120881 · Cited by 95 · see citing works
Blockchain-Based Decentralized Application: A Survey
Zheng, P., Jiang, Z., Wu, J., & Zheng, Z. (2023) · IEEE Open Journal of the Computer Society · doi:10.1109/ojcs.2023.3251854 · Cited by 90 · see citing works
How psychological framing affects economic market prices in the lab and field
Sonnemann, U., Camerer, C. F., Fox, C. R., & Langer, T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1206326110 · Cited by 86 · see citing works
Three Tools for Forecasting Federal Elections: Lessons from 2001
Wolfers, J. J., & Leigh, A. (2002) · Australian Journal of Political Science · doi:10.1080/10361140220148115 · Cited by 79 · see citing works
Self-citationThe network science of collective intelligence
Centola, D. M. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.08.009 · Cited by 78 · see citing works
Economic cognitive institutions
Petracca, E., & Gallagher, S. (2020) · Journal of Institutional Economics · doi:10.1017/s1744137420000144 · Cited by 78 · see citing works
The Macro Effects of Climate Policy Uncertainty
Fried, S., Novan, K., & Peterman, W. B. (2021) · Finance and Economics Discussion Series · doi:10.17016/feds.2021.018 · Cited by 76 · see citing works
Effect of Crowd Voting on Participation in Crowdsourcing Contests
Chen, L., Xu, P., & De, L. (2020) · Journal of Management Information Systems · doi:10.1080/07421222.2020.1759342 · Cited by 70 · see citing works
Building intelligent systems one e-citizen at a time
Hearst, M. A., Hunson, R. D., & Stork, D. G. (1999) · IEEE Intelligent Systems and their Applications · doi:10.1109/5254.769877 · Cited by 69 · see citing works
Forecasting AI progress: A research agenda
Gruetzemacher, R., Dorner, F. E., Bernaola, N., Giattino, C., & Manheim, D. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120909 · Cited by 66 · see citing works
Did Steve Forbes scare the US municipal bond market?
Slemrod, J., & Greimel, T. (1999) · Journal of Public Economics · doi:10.1016/s0047-2727(99)00019-5 · Cited by 56 · see citing works
Bias, Information, Noise: The BIN Model of Forecasting
Satopää, V., Salikhov, M., Tetlock, P. E., & Mellers, B. A. (2020) · Management Science · doi:10.1287/mnsc.2020.3882 · Cited by 54 · see citing works
Amano, T., Bako, L. A., Best, M., Boenisch, N., Boersch‐Supan, P. H., Browne, D., Buckley, Y. M., Burgman, M., Cadotte, M. W., Canessa, S., et al. (2022) · Open Book Publishers · doi:10.11647/obp.0321 · Cited by 53 · see citing works
Belief Movement, Uncertainty Reduction, and Rational Updating
Augenblick, N., & Rabin, M. (2021) · The Quarterly Journal of Economics · doi:10.1093/qje/qjaa043 · Cited by 50 · see citing works
Bias, Information, Noise: The BIN Model of ForecastingPreprint
Satopää, V. A., Salikhov, M., Tetlock, P., & Mellers, B. (2020) · Management Sciences · doi:10.2139/ssrn.3540864 · Cited by 48 · see citing works
High-Speed Idea Filtering with the Bag of LemonsPreprint
Klein, M. H., & García, A. C. B. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2501787 · Cited by 48 · see citing works
How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence
Page, L., & Siemroth, C. (2018) · Review of Financial Studies · doi:10.1093/rfs/hhaa143 · Cited by 46 · see citing works
Small steps to accuracy: Incremental belief updaters are better forecasters
Atanasov, P. D., Witkowski, J., Ungar, L., Mellers, B. A., & Tetlock, P. E. (2020) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2020.02.001 · Cited by 45 · see citing works
The wisdom of the crowd in dynamic economies
Pietro Dindo, B., & Massari, F. (2020) · Theoretical Economics · doi:10.3982/te3924 · Cited by 24 · see citing works
Prediction Markets for Probabilistic Forecasting of Renewable Energy Sources
Shamsi, M., & Cuffe, P. (2021) · IEEE Transactions on Sustainable Energy · doi:10.1109/tste.2021.3112916 · Cited by 20 · see citing works
Feedback Effects, Asymmetric Trading, and the Limits to ArbitragePreprint
Edmans, A., Itay Goldstein, B., & Jiang, W. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1787732 · Cited by 19 · see citing works
How Prediction Markets Can Save Event StudiesPreprint
Snowberg, E., Wolfers, J. J., & Zitzewitz, E. W. (2008) · SSRN Electronic Journal · doi:10.2139/ssrn.1329017 · Cited by 19 · see citing works
Self-citationForecasting and Criminal Justice Policy and Practice
Sabol, W. J., & Baumann, M. L. (2022) · American Journal of Criminal Justice · doi:10.1007/s12103-022-09715-3 · Cited by 16 · see citing works
The wisdom of the crowd and prediction markets
Dai, M., Jia, Y., & Kou, S. G. (2020) · Journal of Econometrics · doi:10.1016/j.jeconom.2020.07.016 · Cited by 16 · see citing works
Accurately predicting hit songs using neurophysiology and machine learning
Merritt, S. H., Gaffuri, K., & Zak, P. J. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1154663 · Cited by 14 · see citing works
How Effective Altruism Can Help Psychologists Maximize Their Impact
Gainsburg, I., Pauer, S., Abboub, N., Aloyo, E., Mourrat, J.-C., & Cristià, A. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916221079596 · Cited by 12 · see citing works
DECISION‐MAKING MODELS, DECISION SUPPORT, AND PROBLEM SOLVING
Lehto, M. R., Nanda, G., & Nanda, G. (2021) · Wiley eBooks · doi:10.1002/9781119636113.ch6 · Cited by 12 · see citing works
Information markets and nonmarkets
Bergemann, D., & Ottaviani, M. (2021) · Handbook of Industrial Organization · doi:10.1016/bs.hesind.2021.11.008 · Cited by 12 · see citing works
Too Much Trust in Group Decisions: Uncovering Hidden Profiles by Groups and Markets
Maciejovsky, B., & Budescu, D. V. (2020) · Organization Science · doi:10.1287/orsc.2020.1363 · Cited by 11 · see citing works
Preference Markets: Organizing Securities Markets for Opinion Surveys with Infinite ScalabilityPreprint
Dahan, E., Soukhoroukova, A., & Spann, M. (2007) · SSRN Electronic Journal · doi:10.2139/ssrn.1031754 · Cited by 11 · see citing works
Almaatouq, A., Rahimian, M. A., Burton, J. W., & Alhajri, A. (2022) · Scientific Reports · doi:10.1038/s41598-022-20551-7 · Cited by 10 · see citing works
Wu, K., & Wheatley, S. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2940173 · Cited by 10 · see citing works
Towards the Use of Blockchain Prediction Markets for Forecasting Wind Power
Shamsi, M., & Cuffe, P. (2020) · IEEE International Energy Conference (ENERGYCON) · doi:10.1109/energycon48941.2020.9236467 · Cited by 9 · see citing works
Herding or wisdom of the crowd? Controlling efficiency in a partially rational financial market
Rossa, F. D., Giannini, L., & Lellis, P. D. (2020) · PLoS ONE · doi:10.1371/journal.pone.0239132 · Cited by 9 · see citing works
How Can Human-Computer “Superminds” Develop Business Strategies?
Malone, T. W. (2019) · Springer eBooks · doi:10.1007/978-3-030-20680-2_9 · Cited by 9 · see citing works
McAndrew, T., Codi, A., Cambeiro, J., Besiroglu, T., Braun, D., Chen, E., Césaris, L. E. U. D., & Luk, D. (2022) · BMC Infectious Diseases · doi:10.1186/s12879-022-07794-5 · Cited by 7 · see citing works
U.S. Politics from a multifractal perspective
Schadner, W. (2021) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2021.111677 · Cited by 7 · see citing works
Samotin, L. R., Friedman, J. A., & Horowitz, M. C. (2022) · Intelligence & National Security · doi:10.1080/02684527.2022.2142352 · Cited by 6 · see citing works
Social Networks as Platforms for Enhancing Collective Intelligence
Nguyen, V. D., Tran, C., Truong, H. B., & Nguyên, N. T. (2021) · Cybernetics & Systems · doi:10.1080/01969722.2021.2018544 · Cited by 6 · see citing works
Teschner, F., & Gimpel, H. (2018) · Group Decision and Negotiation · doi:10.1007/s10726-018-9565-y · Cited by 6 · see citing works
Virtuous opinion change in structured groups
Bolger, F., Rowe, G., Hamlin, I., Belton, I., Crawford, M. M., Sissons, A., Lūka, C. T. B., Vasilichi, A., & Wright, G. (2023) · Judgment and Decision Making · doi:10.1017/jdm.2023.22 · Cited by 5 · see citing works
Sperb, L. F. C., Sung, M., Ma, T., & JOHNSON, J. E. V. (2021) · European Journal of Operational Research · doi:10.1016/j.ejor.2021.09.048 · Cited by 5 · see citing works
Human Forest vs. Random Forest in Time-Sensitive COVID-19 Clinical Trial PredictionPreprint
Atanasov, P. D., Joseph, R., Feijoo, F., Marshall, M., Conway, A., & Siddiqui, S. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3981732 · Cited by 5 · see citing works
A logarithmic market scoring rule agent-based model to evaluate prediction markets
Carvalho, A. V. C., Silveira, D., Ely, R. A., & Cajueiro, D. O. (2023) · Journal of Evolutionary Economics · doi:10.1007/s00191-023-00822-w · Cited by 4 · see citing works
Inefficiency and predictability in the Brexit Pound market: a natural experiment
Wu, K., Wheatley, S., & Sornette, D. (2020) · European Journal of Finance · doi:10.1080/1351847x.2020.1805781 · Cited by 4 · see citing works
Overpricing persistence in experimental asset markets with intrinsic uncertainty
Sornette, D., Andraszewicz, S., Wu, K., Murphy, R. O., Rindler, P. B., & Sanadgol, D. (2020) · Economics · doi:10.5018/economics-ejournal.ja.2020-20 · Cited by 4 · see citing works
The Wisdom of the Crowd in Dynamic EconomiesPreprint
Pietro Dindo, B., & Massari, F. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3038309 · Cited by 4 · see citing works
Merz, O., Flepp, R., & Franck, E. P. (2019) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2021.101724 · Cited by 3 · see citing works
How Prediction Markets Can Save Event StudiesPreprint
Snowberg, E., Wolfers, J. J., & Zitzewitz, E. W. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1805406 · Cited by 3 · see citing works
Self-citationThe Mythology of Game TheoryPreprint
McCubbins, M. D., Turner, M. B., & Weller, N. (2012) · SSRN Electronic Journal · doi:10.2139/ssrn.1980848 · Cited by 2 · see citing works
Using Social Network Analysis to Support Collective Decision-Making Process
Shum, S. B., Cannavacciuolo, L., Liddo, A. D., Iandoli, L., & Quinto, I. (2013) · IGI Global eBooks · doi:10.4018/978-1-4666-4002-3.ch005 · Cited by 2 · see citing works
Intelligent Collectives: Impact of Independence on Collective Performance
Nguyen, V. D., & Truong, H. B. (2023) · Cybernetics & Systems · doi:10.1080/01969722.2022.2162735 · Cited by 1 · see citing works
Teall, J. L. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90955-6.00012-4 · Cited by 1 · see citing works
Schuh, G., Patzwald, M., & Studerus, B. (2022) · Portland International Conference on Management of Engineering and Technology (PICMET) · doi:10.23919/picmet53225.2022.9882878 · Cited by 1 · see citing works
An Analysis of Tradesports' 2005-06 National Football League Prediction MarketPreprint
Zhou, F. (2007) · SSRN Electronic Journal · doi:10.2139/ssrn.963532 · Cited by 1 · see citing works
Kübler, R. V., & Manke, K. (2023) · Springer eBooks · doi:10.1007/978-3-658-39008-2_8
Retrodiction MarketsPreprint
Guerra-Pujol, F. E. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4323607
A new randomized response technique with application to election polling
Singh, G. N., Bhattacharyya, D., & Bandyopadhyay, A. (2021) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2021.2008438
Underestimating randomness: Outcome bias in betting exchange marketsPreprint
Merz, O., Flepp, R., & Franck, E. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3905961
Leininger, A. (2020) · Springer eBooks · doi:10.1007/978-3-658-16936-7_36
Flagged first, then by citations
Research works printed but not linked: 61
- Athanasoulis, Stefano, Robert Shiller and Eric van Wincoop. 1999. "Macro Markets and Finan- cial Security." Economic Policy Review. 5:1, pp. 21- 39.
- Forsythe, Robert, Thomas Rietz and Thomas Ross. 1999. "Wishes, Expectations and Actions: Price Formation in Election Stock Markets." Jour- nal of Economic Behavior and Organization. 39:1, pp. 83-110.
- Hanson, Robin. 1999. "Decision Markets." IEEE Intelligent Systems. 14:3, pp. 16 -19.
- Plott, Charles and Shyam Sunder. 1988. "Ra- tional Expectations and The Aggregation of Di- verse information in Laboratory Security Mar- kets." Econometrica. 56:5, pp. 1085-118.
- Shiller, Robert. 2003. The New Financial Order: Risk in the Twenty-First Century. Princeton, N.J.: Princeton University Press.
- Nicola Dimitri. 2023. VOTING IN DAOs. Distributed Ledger Technologies: Research and Practice 2. . [Crossref] · DOI
- Yuanyuan Lei, Chen Wang. 2023. Extracting the wisdom of a smaller crowd from dependent quantile judgments. IISE Transactions 55:6, 574-587. [Crossref] · DOI
- Kensuke Ito. 2023. Be More Conceptual Regarding Non-Fungible Tokens (NFTs) as Art. Leonardo 56:3, 290-291. [Crossref] · DOI
- Majid Karimi, Stanko Dimitrov. 2023. To Subsidize Or Not to Subsidize: A Comparison of Market Scoring Rules and Continuous Double Auctions for Price Discovery. Information Systems Frontiers 5. . [Crossref] · DOI
- Hannah Gampe, Christopher Griffin. 2023. Dynamics of a binary option market with exogenous information and price sensitivity. Communications in Nonlinear Science and Numerical Simulation 118, 106994. [Crossref] · DOI
- Richard P Mann. 2023. Optimising collective accuracy among rational individuals in sequential decision-making with competition. Collective Intelligence 2:2, 263391372311764. [Crossref] · DOI
- Bo Wang, Zhen Zhou. 2023. Informational feedback between voting and speculative trading. Games and Economic Behavior 138, 387-406. [Crossref] · DOI
- Taylor Wiesen. 2023. Aggregate earnings and market expectations in United States presidential election prediction markets. Advances in Accounting 60, 100639. [Crossref] · DOI
- Ville A. Satopää, Marat Salikhov, Philip E. Tetlock, Barbara Mellers. 2023. Decomposing the effects of crowd-wisdom aggregators: The bias-information-noise (BIN) model. International Journal of Forecasting 39:1, 470-485. [Crossref] · DOI
- Antonio Filippin, Marco Mantovani. 2023. Risk aversion and information aggregation in binary-asset markets. Quantitative Economics 14:2, 753-798. [Crossref] · DOI
- Mahdieh Shamsi, Paul Cuffe. Towards Conditional Prediction Markets as Policy-Making Instruments for the Promotion of Renewable Energy 1-6. [Crossref] · DOI
- Lawrence Choo, Todd R. Kaplan, Ro'i Zultan. 2022. Manipulation and (Mis)trust in Prediction Markets. Management Science 68:9, 6716-6732. [Crossref] · DOI
- Ziemowit Bednarek, Jacqueline M. Doremus, Sarah S. Stith. 2022. U.S. cannabis laws projected to cost generic and brand pharmaceutical firms billions. PLOS ONE 17:8, e0272492. [Crossref] · DOI
- Majid Karimi, Nima Zaerpour. 2022. Put your money where your forecast is: Supply chain collaborative forecasting with cost-function-based prediction markets. European Journal of Operational Research 300:3, 1035-1049. [Crossref] · DOI
- Jonghwan (Simon) Kim, Heung-Jae Jeon, Grace Goun Kim. 2022. Overconfidence or competence? Your employees know. Economics Letters 216, 110580. [Crossref] · DOI
- Thomas Ferguson, Paul Jorgensen, Jie Chen. 2022. How money drives US congressional elections: Linear models of money and outcomes. Structural Change and Economic Dynamics 61, 527-545. [Crossref] · DOI
- Mahdieh Shamsi, Paul Cuffe. 2022. Using Binary Prediction Markets as Hedging Instruments: Strategies for Renewable Generators. IEEE Transactions on Sustainable Energy 13:2, 1160-1163. [Crossref] 40. 2022. Letters. Significance 19:2, 46-47. [Crossref] · DOI
- Stephen V. Marks, Seth C. Pope. 2022. Private prison stocks and the 2020 presidential election. Social Science Quarterly 31. . [Crossref] · DOI
- Hozan K. Hamarashid, Soran A. Saeed, Tarik A. Rashid. 2022. A comprehensive review and evaluation on text predictive and entertainment systems. Soft Computing 26:4, 1541-1562. [Crossref] · DOI
- Mohannad Jreissat, Charalampos Makatsoris. 2022. Towards consumer driven food new product development: a closed-loop platform. International Journal of Computer Integrated Manufacturing 35:2, 183-202. [Crossref] · DOI
- Michele Ciampi, Muhammad Ishaq, Malik Magdon-Ismail, Rafail Ostrovsky, Vassilis Zikas. FairMM: A Fast and Frontrunning-Resistant Crypto Market-Maker 428-446. [Crossref] · DOI
- Sirio Aramonte. 2022. Inflation Risk and the Labor Market. SSRN Electronic Journal 116. . [Crossref] · DOI
- Itay Goldstein. 2022. Information in Financial Markets and Its Real Effects. SSRN Electronic Journal 23. . [Crossref] · DOI
- Ruslan Momot, Marat Salikhov. 2022. Information Elicitation from Teams of Privacy-Conscious Experts. SSRN Electronic Journal . [Crossref] · DOI
- Nishanth Nakshatri, Arjun Menon, C. Lee Giles, Sarah Rajtmajer, Christopher Griffin. 2021. Design and analysis of a synthetic prediction market using dynamic convex sets. Results in Control and Optimization 5, 100052. [Crossref] · DOI
- John R. Birge, Yifan Feng, N. Bora Keskin, Adam Schultz. 2021. Dynamic Learning and Market Making in Spread Betting Markets with Informed Bettors. Operations Research 69:6, 1746-1766. [Crossref] · DOI
- Mahdieh Shamsi, Paul Cuffe. 2021. A Prediction Market Trading Strategy to Hedge Financial Risks of Wind Power Producers in Electricity Markets. IEEE Transactions on Power Systems 36:5, 4513-4523. [Crossref] · DOI
- CHRISTOPH SIEMROTH. 2021. When Can Decision Makers Learn from Financial Market Prices?. Journal of Money, Credit and Banking 53:6, 1523-1552. [Crossref] · DOI
- Leonid Komissarov, Robert Rüger, Matti Hellström, Toon Verstraelen. 2021. ParAMS: Parameter Optimization for Atomistic and Molecular Simulations. Journal of Chemical Information and Modeling 61:8, 3737-3743. [Crossref] · DOI
- Stephen L. France, Yuying Shi, Brett Kazandjian. 2021. Web Trends: A valuable tool for business research. Journal of Business Research 132, 666-679. [Crossref] · DOI
- Ahrash Dianat, Christoph Siemroth. 2021. Improving decisions with market information: an experiment on corporate prediction markets. Experimental Economics 24:1, 143-176. [Crossref] · DOI
- Mohammed Abdellaoui, Han Bleichrodt, Emmanuel Kemel, Olivier l'Haridon. 2021. Measuring Beliefs Under Ambiguity. Operations Research 69:2, 599-612. [Crossref] · DOI
- Andreas Kern, Puspa Amri. 2021. Political credit cycles. Economics & Politics 33:1, 76-108. [Crossref] · DOI
- William Halal. The Coming Space Age 270-280. [Crossref] · DOI
- Rajiv Sethi, Julie Seager, Emily Cai, Daniel Benjamin, Fred Morstatter. 2021. Models, Markets, and the Forecasting of Elections. SSRN Electronic Journal 10. . [Crossref] · DOI
- Ville Satopää, Marat Salikhov, Philip Tetlock, Barb Mellers. 2021. Decomposing the Effects of Crowd-Wisdom Aggregators: The Bias-Information-Noise (BIN) Model. SSRN Electronic Journal 30. . [Crossref] · DOI
- Yang Zhao, Min-Teh Yu. 2020. Predicting catastrophe risk: Evidence from catastrophe bond markets. Journal of Banking & Finance 121, 105982. [Crossref] · DOI
- Jason M. Tangen, Kirsty M. Kent, Rachel A. Searston. 2020. Collective intelligence in fingerprint analysis. Cognitive Research: Principles and Implications 5:1. . [Crossref] · DOI
- Robert P Lieli, Augusto Nieto-Barthaburu. 2020. On the Possibility of Informative Equilibria in Futures Markets with Feedback. Journal of the European Economic Association 18:3, 1521-1552. [Crossref] · DOI
- George J. Mailath, Larry Samuelson. 2020. Learning under Diverse World Views: Model-Based Inference. American Economic Review 110:5, 1464-1501. [Abstract] [View PDF article] [PDF with links] · DOI
- George Christodoulakis. 2020. Estimating the term structure of commodity market preferences. European Journal of Operational Research 282:3, 1146-1163. [Crossref] · DOI
- Marcus Pivato, Arnold Soh. 2020. Weighted representative democracy. Journal of Mathematical Economics 88, 52-63. [Crossref] · DOI
- Kelly Huang, Meng Li, Stanimir Markov. 2020. What Do Employees Know? Evidence from a Social Media Platform. The Accounting Review 95:2, 199-226. [Crossref] · DOI
- Sabrina Armenio, Angela Stefania Bergantino, Andrea Morone. Can Laboratory Experiments Help in Evaluating Emission Trading Schemes? A Pilot Experiment on Aviation Allowances: Lessons to Be Learned 215-242. [Crossref] · DOI
- Anthony M. Diercks, Daniel Soques, William Waller. 2020. The 283 Days of Stock Returns after the 2016 Election. SSRN Electronic Journal 5. . [Crossref] · DOI
- Spyros Galanis. 2020. No Trade in a Blockchain. SSRN Electronic Journal 4. . [Crossref] 100. Henrich R. Greve, Nils Rudi, Anup Walvekar. 2019. Strategic rule breaking: Time wasting to win soccer games. PLOS ONE 14:12, e0224150. [Crossref] 101. Eskil Forsell, Domenico Viganola, Thomas Pfeiffer, Johan Almenberg, Brad Wilson, Yiling Chen, Brian A. Nosek, Magnus Johannesson, Anna Dreber. 2019. Predicting replication outcomes in the Many Labs 2 study. Journal of Economic Psychology 75, 102117. [Crossref] 102. Robert L. Winkler, Yael Grushka-Cockayne, Kenneth C. Lichtendahl, Victor Richmond R. Jose. 2019. Probability Forecasts and Their Combination: A Research Perspective. Decision Analysis 16:4, 239-260. [Crossref] 103. Sepideh Bazazi, Jorina von Zimmermann, Bahador Bahrami, Daniel Richardson. 2019. Self-serving incentives impair collective decisions by increasing conformity. PLOS ONE 14:11, e0224725. [Crossref] 104. Stefano DellaVigna, Devin Pope, Eva Vivalt. 2019. Predict science to improve science. Science 366:6464, 428-429. [Crossref] 105. Hajime Mizuyama, Seiyu Yamaguchi, Mizuho Sato. 2019. A Prediction Market-Based Gamified Approach to Enhance Knowledge Sharing in Organizations. Simulation & Gaming 50:5, 572-597. [Crossref] 106. G. Bottazzi, D. Giachini. 2019. Far from the madding crowd: collective wisdom in prediction markets. Quantitative Finance 19:9, 1461-1471. [Crossref] 107. Raymond Fisman, Eric Zitzewitz. 2019. An Event Long-Short Index: Theory and Applications. American Economic Review: Insights 1:3, 357-372. [Abstract] [View PDF article] [PDF with links] 108. · DOI
- Robert L. Winkler, Yael Grushka-Cockayne, Kenneth C. Lichtendahl, Victor Richmond Jose. 2018. Averaging Probability Forecasts: Back to the Future. SSRN Electronic Journal . [Crossref] 173. · DOI
- John R. Birge, Yifan Feng, N. Bora Keskin, Adam Schultz. 2018. Dynamic Learning and Market Making in Spread Betting Markets With Informed Bettors. SSRN Electronic Journal . [Crossref] 174. Alasdair Brown. 2018. Parimutuel Versus Fixed-Odds Betting: Evidence from a Hybrid Market. SSRN Electronic Journal . [Crossref] 175. · DOI
- Yuko Sakurai, Masato Shinoda, Satoshi Oyama, Makoto Yokoo. Flexible Reward Plans for Crowdsourced Tasks 400-415. [Crossref] 266. Stephen Coleman. 2015. Evolution of Russia's Political Party System Under the Influence of Social Conformity: 1993-2011. SSRN Electronic Journal . [Crossref] 267. · DOI
- Kyle J. Kain, Trevon D. Logan. 2014. Are Sports Betting Markets Prediction Markets?. Journal of Sports Economics 15:1, 45-63. [Crossref] 294. Andrew Gelman, Eric Loken. 2014. Ethics and Statistics: The AAA Tranche of Subprime Science. CHANCE 27:1, 51-56. [Crossref] 295. Hajime Mizuyama, Shuhei Torigai, Michiko Anse. A Prediction Market Game to Route Selection under Uncertainty 222-229. [Crossref] 296. Pankaj Pandey, Einar Arthur Snekkenes. Using Prediction Markets to Hedge Information Security Risks 129-145. [Crossref] 297. Jihui Chen, Xiaoyong Zheng. 2014. Price Volatility and Contract Maturity: Evidence from an Online Futures Market for Sports Tickets. Eastern Economic Journal 40:1, 56-70. [Crossref] 298. Mark Klein, Ana Cristina Bicharra Garcia. 2014. The Bag of Stars: High-Speed Idea Filtering for Open Innovation. SSRN Electronic Journal . [Crossref] 299. Karsten Eisenschmidt, Matthias Schmidt. 2014. Integrating Prediction Markets into the Due Process of International Accounting Standard Setting -A Possible Path to Achieve Legitimate Accounting Standards. SSRN Electronic Journal . [Crossref] 300. Bertrand Claude Lemennicier. 2014. What is Wrong with Moral Hazard and Adverse Selection Problems in the Conventional Economic Theory. SSRN Electronic Journal . [Crossref] 301. Christoph Siemroth. 2014. Why Prediction Markets Work: The Role of Information Acquisition and Endogenous Weighting. SSRN Electronic Journal . [Crossref] 302. · DOI
- Easwar A. Nyshadham, Janaki Krishnamurthy. 2012. Software Quality Market: Design and Field Study of a Prediction Market. SSRN Electronic Journal . [Crossref] 385. · DOI
- Zhiling Guo, Fang Fang, Andrew B. Whinston. Managing Supply Uncertainty with an Information Market 80-95. [Crossref] 478. Xi Alice Gao, Yiling Chen. An Axiomatic Characterization of Continuous-Outcome Market Makers 505-514. [Crossref] 479. Sean Wise, Milan Miric, Dave Valliere. 2010. Testing the effectiveness of Semi -Predictive Markets: Are fight fans smarter than expert bookies?. Procedia -Social and Behavioral Sciences 2:4, 6497-6502. [Crossref] 480. Jens Krause, Graeme D. Ruxton, Stefan Krause. 2010. Swarm intelligence in animals and humans. Trends in Ecology & Evolution 25:1, 28-34. [Crossref] 481. Christian Wagner, Sesia Zhao, Christoph Schneider, Huaping Chen. The Wisdom of Reluctant Crowds 1-10. [Crossref] 482. Phattara Sripawatakul, Daricha Sutivong. Decision framework for constructing prediction markets 35-39. [Crossref] 483. Joyce E. Berg, John Geweke, Thomas A. Rietz. 2010. Memoirs of an Indifferent Trader: Estimating Forecast Distributions from Prediction Markets. SSRN Electronic Journal . [Crossref] 484. Ilona Babenko, Rik Sen. 2010. Do Non-Executive Employees Have Information? Evidence from Employee Stock Purchase Plans. SSRN Electronic Journal . [Crossref] 485. Marc Chesney, Mustafa Karaman, Ganna Reshetar. 2010. The Impact of Terrorism on Financial Markets: An Empirical Study. SSRN Electronic Journal . [Crossref] 486. Calvin Blackwell. 2010. Results from a Simple Prediction Contest. SSRN Electronic Journal . [Crossref] 487. Felipe A. Csaszar, J.P. Eggers. 2010. Organizing for Strategy Making: An Information Aggregation View. SSRN Electronic Journal . [Crossref] 488. Stefan Berthold, Rainer Böhme. Valuating Privacy with Option Pricing Theory 187-209. [Crossref] 489. Johan Almenberg, Ken Kittlitz, Thomas Pfeiffer. 2009. An Experiment on Prediction Markets in Science. PLoS ONE 4:12, e8500. [Crossref] 490. Li Chen, Paulo Goes, James R. Marsden, Zhongju Zhang. 2009. Design and Use of Preference Markets for Evaluation of Early Stage Technologies. Journal of Management Information Systems 26:3, 45-70. [Crossref] 491. THEO OFFERMAN, JOEP SONNEMANS, GIJS VAN DE KUILEN, PETER P. WAKKER. 2009. A Truth Serum for Non-Bayesians: Correcting Proper Scoring Rules for Risk Attitudes. Review of Economic Studies 76:4, 1461-1489. [Crossref] 492. Jennifer L. Castle, Nicholas W.P. Fawcett, David F. Hendry. 2009. Nowcasting is not Just Contemporaneous Forecasting. National Institute Economic Review 210, 71-89. [Crossref] 493. Jolyon J. Faria, Edward A. Codling, John R.G. Dyer, Fritz Trillmich, Jens Krause. 2009. Navigation in human crowds; testing the many-wrongs principle. Animal Behaviour 78:3, 587-591. [Crossref] 494. Nikolaos Vlastakis, George Dotsis, Raphael N. Markellos. 2009. How efficient is the European football betting market? Evidence from arbitrage and trading strategies. Journal of Forecasting 28:5, 426-444. [Crossref] 495. Michael A. Smith, David Paton, Leighton Vaughan Williams. 2009. Do bookmakers possess superior skills to bettors in predicting outcomes?. Journal of Economic Behavior & Organization 71:2, 539-549. [Crossref] 496. Martin Spann, Holger Ernst, Bernd Skiera, Jan Henrik Soll. 2009. Identification of Lead Users for Consumer Products via Virtual Stock Markets. Journal of Product Innovation Management 26:3, 322-335. [Crossref] 497. Nicholas Seybert, Robert Bloomfield. 2009. Contagion of Wishful Thinking in Markets. Management Science 55:5, 738-751. [Crossref] 498. David S. Lee,, Enrico Moretti. 2009. Bayesian Learning and the Pricing of New Information: Evidence from Prediction Markets. American Economic Review 99:2, 330-336. [Citation] [View PDF article] [PDF with links] 499. · DOI
- Helena Veiga, Marc Vorsatz. 2009. Price manipulation in an experimental asset market. European Economic Review 53:3, 327-342. [Crossref] 500. Ray C. Fair. 2009. Interpreting the Predictive Uncertainty of Elections. The Journal of Politics 71:2, 612-626. [Crossref] 501. ROBIN HANSON, RYAN OPREA. 2009. A Manipulator Can Aid Prediction Market Accuracy. Economica 76:302, 304-314. [Crossref] 502. ALBERT N. LINK, JOHN T. SCOTT. 2009. Private Investor Participation and Commercialization Rates for Government-sponsored Research and Development: Would a Prediction Market Improve the Performance of the SBIR Programme?. Economica 76:302, 264-281. [Crossref] 503. JUSTIN WOLFERS, ERIC ZITZEWITZ. 2009. Using Markets to Inform Policy: The Case of the Iraq War. Economica 76:302, 225-250. [Crossref] 504. DAVID PATON, DONALD S. SIEGEL, LEIGHTON VAUGHAN WILLIAMS. 2009. The Growth of Gambling and Prediction Markets: Economic and Financial Implications. Economica 76:302, 219-224. [Crossref] 505. Joyce E. Berg, George R. Neumann, Thomas A. Rietz. 2009. Searching for Google's Value: Using Prediction Markets to Forecast Market Capitalization Prior to an Initial Public Offering. Management Science 55:3, 348-361. [Crossref] 506. John Ledyard, Robin Hanson, Takashi Ishikida. 2009. An experimental test of combinatorial information markets. Journal of Economic Behavior & Organization 69:2, 182-189. [Crossref] 507. Stefan M. Herzog, Ralph Hertwig. 2009. The Wisdom of Many in One Mind. Psychological Science 20:2, 231-237. [Crossref] 508. Efthimios Bothos, Dimitris Apostolou, Gregoris Mentzas. 2009. Collective intelligence for idea management with Internet-based information aggregation markets. Internet Research 19:1, 26-41. [Crossref] 509. Saikat Ray Majumder, Daniel Diermeier, Thomas A. Rietz, Luís A. Nunes Amaral. 2009. Price dynamics in political prediction markets. Proceedings of the National Academy of Sciences 106:3, 679-684. [Crossref] 510. Daniel E. O'Leary. Forecasting using internal markets, Delphi, and other approaches: The knowledge distribution grid 157-172. [Crossref] 511. Lennart Sjöberg. 2009. Are all crowds equally wise? a comparison of political election forecasts by experts and the public. Journal of Forecasting 28:1, 1-18. [Crossref] 512. Stefan Palan. Literature Review 11-65. [Crossref] 513. Joseph Farfel, Vincent Conitzer. Turing Trade: A Hybrid of a Turing Test and a Prediction Market 61-73. [Crossref] 514. Agostino Capponi, Umberto Cherubini. A Copula Function Approach to Infer Correlation in Prediction Markets 4-12. [Crossref] 515. Peng Shi, Vincent Conitzer, Mingyu Guo. Prediction Mechanisms That Do Not Incentivize Undesirable Actions 89-100. [Crossref] 516. Xi Gao, Yiling Chen, David M. Pennock. Betting on the Real Line 553-560. [Crossref] 517. Nick Bostrom. The Future of Humanity 186-215. [Crossref] 518. David Rothschild. 2009. Forecasting Elections. Public Opinion Quarterly 73:5, 895-916. [Crossref] 519. Shu-Heng Chen, Wei-Shao Wu. Price errors from thin markets and their corrections: Studies based on Taiwan's political futures markets 1-25. [Crossref] 520. Pierre Brun, Hideki Kawai, Kazuo Kunieda, Keiji Yamada. ChronoSeeker: Future Opinion Extraction 568-571. [Crossref] 521. Christopher Avery, Judith A. Chevalier, Richard J. Zeckhauser. 2009. The 'CAPS' Prediction System and Stock Market Returns. SSRN Electronic Journal . [Crossref] 522. Christian Slamka, Wolfgang Jank, Bernd Skiera. 2009. Second-Generation Prediction Markets for Information Aggregation: A Comparison of Payoff Mechanisms. SSRN Electronic Journal . [Crossref] 523. Marco Ottaviani, Peter Norman Sorensen. 2009. Aggregation of Information and Beliefs: Asset Pricing Lessons from Prediction Markets. SSRN Electronic Journal 85. . [Crossref] 524. Egon P. Franck, Erwin Verbeek, Stephan Nüesch. 2009. Prediction Accuracy of Different Market Structures -Bookmakers Versus a Betting Exchange. SSRN Electronic Journal . [Crossref] 525. · DOI
- Katarina Kalovcova, Andreas Ortmann. 2008. Journal of Economic Psychology 29:1, 123-125. [Crossref] 541. K. Cuhls, R. Johnston. Corporate Foresight 103-114. [Crossref] 542. Tian-Ming Bu, Xiaotie Deng, Qianya Lin, Qi Qi. Strategies in Dynamic Pari-Mutual Markets 138-153. [Crossref] 543. Russell S. Sobel, Matt E. Ryan. Unifying the Favorite-Longshot Bias with Other Market Anomalies 137-160. [Crossref] 544. Erik Snowberg, Justin Wolfers, Eric Zitzewitz. Prediction Markets: From Politics to Business (and Back) 385-402. [Crossref] 545. David C. Croson. Prediction Market Design 1-4. [Crossref] 546. William E. Halal. Introduction: Guiding Technology's Promise 1-14. [Crossref] 547. Ulrich Sonnemann, Colin F. Camerer, Craig R. Fox, Thomas Langer. 2008. Partition-Dependent Framing Effects in Lab and Field Prediction Markets. SSRN Electronic Journal . [Crossref] 548. Shimon Kogan, Anthony M. Kwasnica, Roberto A. Weber. 2008. Coordination in the Presence of Asset Markets. SSRN Electronic Journal . [Crossref] 549. · DOI
- Robert W. Hahn, Paul C. Tetlock. 2007. Has Economic Analysis Improved Regulatory Decisions?. SSRN Electronic Journal . [Crossref] 571. · DOI
- Yiling Chen, Tracy Mullen, Chao-Hsien Chu. 2006. An in-depth analysis of information markets with aggregate uncertainty. Electronic Commerce Research 6:2, 201-221. [Crossref] 580. Steven Kelman. 2006. Book Review Essay: 9/11 and the Challenges of Public Management: The 9/11 Commission Report: Final Report of the National Commission on Terrorist Attacks upon the United States. Administrative Science Quarterly 51:1, 129-142. [Crossref] 581. Colin F. Camerer, Ernst Fehr. 2006. When Does "Economic Man" Dominate Social Behavior?. Science 311:5757, 47-52. [Crossref] 582. Arina Soukhoroukova, Martin Spann. 2006. Informationsmärkte. WIRTSCHAFTSINFORMATIK 48:1, 61-64. [Crossref] 583. J. Scott Armstrong. 2006. Findings from evidence-based forecasting: Methods for reducing forecast error. International Journal of Forecasting 22:3, 583-598. [Crossref] 584. Robert W. Hahn, Paul C. Tetlock. 2006. Information Markets: A New Way of Making Decisions. SSRN Electronic Journal . [Crossref] 585. James Dow, Itay Goldstein, Alexander Guembel. 2006. Commitment to Overinvest and Price Informativeness. SSRN Electronic Journal . [Crossref] 586. Justin Wolfers, Eric Zitzewitz. 2006. Prediction Markets in Theory and Practice. SSRN Electronic Journal . [Crossref] 587. Hans Gersbach, Markus Müller. 2006. Elections, Contracts and Markets. SSRN Electronic Journal 14. . [Crossref] 588. Steve Easton, Richard Gerlach. 2005. Interest rates and the 2004 Australian Election. Australian Journal of Political Science 40:4, 559-566. [Crossref] 589. Jonathan A. Morell. 2005. Why Are There Unintended Consequences of Program Action, and What Are the Implications for Doing Evaluation?. American Journal of Evaluation 26:4, 444-463. [Crossref] 590. Leighton Vaughan Williams. Models, markets, polls and pundits: a case study of information efficiency 193-214. [Crossref] 591. Erik Snowberg, Justin Wolfers, Eric Zitzewitz. Information (in)efficiency in prediction markets 366-386. [Crossref] 592. Raymond D. Sauer. 2005. The state of research on markets for sports betting and suggested future directions. Journal of Economics and Finance 29:3, 416-426. [Crossref] 593. Gerald F. Davis. 2005. New Directions in Corporate Governance. Annual Review of Sociology 31:1, 143-162. [Crossref] 594. Refet S. Gürkaynak, Justin Wolfers, Christopher D. Carroll, Adam Szeidl. 2005. Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty, and Risk [with Comments]. NBER International Seminar on Macroeconomics 2005:1, 11-64. [Crossref] 595. Paul C. Tetlock, Robert W. Hahn, Donald D. Lien. 2005. Designing Information Markets for Decision Making. SSRN Electronic Journal . [Crossref] 596. · DOI
Cited by
Sorted by citations
Price Informativeness and Investment Sensitivity to Stock Price
Chen, Q., Itay Goldstein, B., & Jiang, W. (2006) · Review of Financial Studies · doi:10.1093/rfs/hhl024 · Cited by 1,492 · see citing works
Evaluating replicability of laboratory experiments in economics
Camerer, C. F., Dreber, A., Forsell, E., Ho, T.-H., Huber, J., Johannesson, M., Kirchler, M., Almenberg, J., Altmejd, A., Chan, T., et al. (2016) · Science · doi:10.1126/science.aaf0918 · Cited by 1,314 · see citing works
Forecasting: theory and practice
Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babai, M. Z., Barrow, D. K., Taieb, S. B., Bergmeir, C., Bessa, R., Bijak, J., Boylan, J., et al. (2020) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2021.11.001 · Cited by 630 · see citing works
The Real Effects of Financial Markets
Bond, P., Edmans, A., & Itay Goldstein, B. (2012) · Annual Review of Financial Economics · doi:10.1146/annurev-financial-110311-101826 · Cited by 901 · see citing works
Quinn, A. J., & Bederson, B. B. (2011) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979148 · Cited by 801 · see citing works
Co-Creation: Toward a Taxonomy and an Integrated Research Perspective
Zwass, V. (2010) · International Journal of Electronic Commerce · doi:10.2753/jec1086-4415150101 · Cited by 778 · see citing works
When Does "Economic Man" Dominate Social Behavior?
Camerer, C. F., & Fehr, E. (2006) · Science · doi:10.1126/science.1110600 · Cited by 733 · see citing works
Predicting consumer behavior with web search
Goel, S., Hofman, J. M., Lahaie, S., Pennock, D. M., & Watts, D. J. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1005962107 · Cited by 636 · see citing works
Screening Peers Softly: Inferring the Quality of Small Borrowers
Iyer, R., Khwaja, A. I., Luttmer, E. F. P., & Shue, K. (2015) · Management Science · doi:10.1287/mnsc.2015.2181 · Cited by 595 · see citing works
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 · see citing works
Wisdom or Madness? Comparing Crowds with Expert Evaluation in Funding the Arts
Mollick, E., & Nanda, R. (2015) · Management Science · doi:10.1287/mnsc.2015.2207 · Cited by 517 · see citing works
Swarm intelligence in animals and humans
Krause, J., Ruxton, G. D., & Krause, S. (2009) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2009.06.016 · Cited by 400 · see citing works
Network dynamics of social influence in the wisdom of crowds
Becker, J., Brackbill, D., & Centola, D. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1615978114 · Cited by 397 · see citing works
(2008) · doi:10.1126/science.1157679 · Cited by 406 · see citing works
Self-citationThe Power of Stars: Do Star Actors Drive the Success of Movies?
Elberse, A. (2007) · Journal of Marketing · doi:10.1509/jmkg.71.4.102 · Cited by 374 · see citing works
New Directions in Corporate Governance
Davis, G. F. (2005) · Annual Review of Sociology · doi:10.1146/annurev.soc.31.041304.122249 · Cited by 342 · see citing works
Using prediction markets to estimate the reproducibility of scientific research
Dreber, A., Pfeiffer, T., Almenberg, J., Isaksson, S., Wilson, B., Chen, Y., Nosek, B. A., & Johannesson, M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1516179112 · Cited by 331 · see citing works
Interpreting the predictions of prediction markets
Manski, C. F. (2006) · Economics Letters · doi:10.1016/j.econlet.2006.01.004 · Cited by 330 · see citing works
Prediction market accuracy in the long run
Berg, J. E., Nelson, F. D., & Rietz, T. A. (2008) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2008.03.007 · Cited by 316 · see citing works
Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI
Fügener, A., Grahl, J., Gupta, A., & Ketter, W. (2021) · MIS Quarterly · doi:10.25300/misq/2021/16553 · Cited by 322 · see citing works
The Wisdom of Many in One Mind
Herzog, S. M., & Hertwig, R. (2009) · Psychological Science · doi:10.1111/j.1467-9280.2009.02271.x · Cited by 304 · see citing works
Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task
Graefe, A., & Armstrong, J. S. (2010) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2010.05.004 · Cited by 240 · see citing works
Feedback Effects, Asymmetric Trading, and the Limits to Arbitrage
Edmans, A., Itay Goldstein, B., & Jiang, W. (2015) · American Economic Review · doi:10.1257/aer.20141271 · Cited by 240 · see citing works
The Real Effects of Financial Markets
Bond, P., Edmans, A., & Itay Goldstein, B. (2011) · National Bureau of Economic Research · doi:10.3386/w17719 · Cited by 233 · see citing works
Information in Financial Markets and Its Real Effects
Itay Goldstein, B. (2022) · European Finance Review · doi:10.1093/rof/rfac052 · Cited by 223 · see citing works
Informational Feedback, Adverse Selection, and Optimal Disclosure Policy
Gao, P., & Liang, P. J. (2013) · Journal of Accounting Research · doi:10.1111/1475-679x.12019 · Cited by 209 · see citing works
The power of prediction with social media
Schoen, H., Gayo-Avello, D., Metaxas, P., Mustafaraj, E., Strohmaier, M., & Gloor, P. A. (2013) · Internet Research · doi:10.1108/intr-06-2013-0115 · Cited by 217 · see citing works
A Truth Serum for Non-Bayesians: Correcting Proper Scoring Rules for Risk Attitudes
Offerman, T., Joep Sonnemans, A., van de Kuilen, G., & Wakker, P. P. (2009) · The Review of Economic Studies · doi:10.1111/j.1467-937x.2009.00557.x · Cited by 219 · see citing works
Survey Measurement of Probabilistic Macroeconomic Expectations: Progress and Promise
Manski, C. F. (2018) · NBER Macroeconomics Annual · doi:10.1086/696061 · Cited by 218 · see citing works
What Do Employees Know? Evidence from a Social Media Platform
Huang, K., Li, M., & Markov, S. (2018) · The Accounting Review · doi:10.2139/ssrn.3225957 · Cited by 206 · see citing works
Agarwal, A., Dahleh, M. A., & Sarkar, T. (2019) · ACM Conference on Economics and Computation (EC) · doi:10.1145/3328526.3329589 · Cited by 214 · see citing works
Blockchain‐Enabled Data Sharing in Supply Chains: Model, Operationalization, and Tutorial
Wang, Z., Zheng, Z., Jiang, W., & Tang, S. (2021) · Production and Operations Management · doi:10.1111/poms.13356 · Cited by 215 · see citing works
Deliberating Groups versus Prediction Markets (or Hayek's Challenge to Habermas)
Sunstein, C. R. (2006) · Episteme · doi:10.3366/epi.2006.3.3.192 · Cited by 200 · see citing works
Findings from evidence-based forecasting: Methods for reducing forecast error
Armstrong, J. S. (2006) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2006.04.006 · Cited by 199 · see citing works
Organizational Decision Making: An Information Aggregation View
Csaszar, F. A., & Eggers, J. P. (2013) · Management Sciences · doi:10.1287/mnsc.1120.1698 · Cited by 170 · see citing works
Information aggregation and manipulation in an experimental market
Hanson, R., Oprea, R. D., & Porter, D. (2006) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2004.09.011 · Cited by 186 · see citing works
Predicting Experimental Results: Who Knows What?
DellaVigna, S., & Pope, D. G. (2018) · Journal of Political Economy · doi:10.1086/699976 · Cited by 183 · see citing works
Shall We Vote on Values, But Bet on Beliefs?
Hanson, R. (2013) · Journal of Political Philosophy · doi:10.1111/jopp.12008 · Cited by 181 · see citing works
The informational feedback effect of stock prices on management forecasts
Zuo, L. (2016) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2016.03.001 · Cited by 180 · see citing works
Herm, S., Callsen-Bracker, H.-M., & Kreis, H. (2014) · Sport Management Review · doi:10.1016/j.smr.2013.12.006 · Cited by 179 · see citing works
Point Shaving: Corruption in NCAA Basketball
Wolfers, J. J. (2006) · American Economic Review · doi:10.1257/000282806777211757 · Cited by 170 · see citing works
Self-citationFinTechs and the Market for Financial Analysis
Grennan, J., & Michaely, R. (2020) · Journal of Financial and Quantitative Analysis · doi:10.1017/s0022109020000721 · Cited by 184 · see citing works
Real Time, Time Series Forecasting of Inter- and Intra-State Political Conflict
Brandt, P. T., Freeman, J. R., & Schrodt, P. A. (2011) · Conflict Management and Peace Science · doi:10.1177/0738894210388125 · Cited by 166 · see citing works
An overview of decentralized autonomous organizations on the blockchain
El Faqir, Y., Arroyo, J., & Hassan, S. (2020) · Proceedings of the 16th International Symposium on Open Collaboration · doi:10.1145/3412569.3412579 · Cited by 165 · see citing works
Soukhoroukova, A., Spann, M., & Skiera, B. (2011) · Journal of Product Innovation Management · doi:10.1111/j.1540-5885.2011.00881.x · Cited by 164 · see citing works
Using Markets to Inform Policy: The Case of the Iraq War
Wolfers, J. J., & Zitzewitz, E. W. (2009) · Economica · doi:10.1111/j.1468-0335.2008.00750.x · Cited by 160 · see citing works
Self-citationZhang, G., Ding, Y., & Milojević, S. (2013) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22850 · Cited by 169 · see citing works
Iyer, R., Khwaja, A. I., Luttmer, E. F. P., & Shue, K. (2010) · SSRN Electronic Journal · doi:10.2139/ssrn.1570115 · Cited by 150 · see citing works
Interpreting Prediction Market Prices as Probabilities
Wolfers, J. J., & Zitzewitz, E. W. (2006) · National Bureau of Economic Research · doi:10.3386/w12200 · Cited by 149 · see citing works
Self-citationEliciting properties of probability distributions
Lambert, N. S., Pennock, D. M., & Shoham, Y. (2008) · ACM Conference on Economics and Computation · doi:10.1145/1386790.1386813 · Cited by 207 · see citing works
Elberse, A., & Anand, B. N. (2007) · Information Economics and Policy · doi:10.1016/j.infoecopol.2007.06.003 · Cited by 146 · see citing works
Has Economic Analysis Improved Regulatory Decisions?
Hahn, R. W., & Tetlock, P. C. (2008) · The Journal of Economic Perspectives · doi:10.1257/jep.22.1.67 · Cited by 145 · see citing works
Wisdom or Madness? Comparing Crowds with Expert Evaluation in Funding the ArtsPreprint
Mollick, E., & Nanda, R. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2443114 · Cited by 145 · see citing works
Predict science to improve science
DellaVigna, S., Pope, D. G., & Vivalt, E. (2019) · Science · doi:10.1126/science.aaz1704 · Cited by 140 · see citing works
Information aggregation and collective intelligence beyond the wisdom of crowds
Kameda, T., Toyokawa, W., & Tindale, R. S. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-022-00054-y · Cited by 139 · see citing works
Keller, J., & von der Gracht, H. A. (2013) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2013.07.010 · Cited by 139 · see citing works
Testing the Wisdom of Crowds in the field: Transfermarkt valuations and international soccer results
Peeters, T. L. P. R. (2017) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2017.08.002 · Cited by 138 · see citing works
Qiu, L., & Kumar, S. (2017) · Information Systems Research · doi:10.1287/isre.2016.0679 · Cited by 135 · see citing works
Chen, S. (2011) · Journal of Economic Dynamics and Control · doi:10.1016/j.jedc.2011.09.003 · Cited by 134 · see citing works
I nvestigate D iscuss E stimate A ggregate for structured expert judgement
Hanea, A., McBride, M., Burgman, M., Wintle, B., Fidler, F., Flander, L., Twardy, C. R., Manning, B., & Mascaro, S. (2017) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2016.02.008 · Cited by 95 · see citing works
Prediction Markets in Theory and PracticePreprint
Wolfers, J. J., & Zitzewitz, E. W. (2006) · SSRN Electronic Journal · doi:10.3386/w12083 · Cited by 130 · see citing works
Self-citationSimple Heuristics in a Social World
Hertwig, R., Hoffrage, U., & the, A. R. G. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388435.001.0001 · Cited by 129 · see citing works
Group-based forecasting?: A social psychological analysis
Kerr, N. L., & Tindale, R. S. (2010) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2010.02.001 · Cited by 130 · see citing works
Crowds, Lending, Machine, and Bias
Fu, R., Huang, Y. H., & Singh, P. V. (2021) · Information Systems Research · doi:10.1287/isre.2020.0990 · Cited by 126 · see citing works
Operational Research: methods and applications
Petropoulos, F., Gilbert Laporte, A., Aktaş, E., Alumur, S. A., Archetti, C., Ayhan, H., Battarra, M., Bennell, J. A., Bourjolly, J.-M., Boylan, J. E., et al. (2023) · Journal of the Operational Research Society · doi:10.1080/01605682.2023.2253852 · Cited by 138 · see citing works
Predicting Experimental Results: Who Knows What?
DellaVigna, S., & Pope, D. G. (2016) · National Bureau of Economic Research · doi:10.3386/w22566 · Cited by 117 · see citing works
Bostrom, N. (2009) · Palgrave Macmillan UK eBooks · doi:10.1057/9780230227279_10 · Cited by 114 · see citing works
High-speed idea filtering with the bag of lemons
Klein, M., & García, A. C. B. (2015) · Decision Support Systems · doi:10.1016/j.dss.2015.06.005 · Cited by 112 · see citing works
Information and Efficiency: Goal Arrival in Soccer Betting
Croxson, K., & Reade, J. J. (2013) · The Economic Journal · doi:10.1111/ecoj.12033 · Cited by 111 · see citing works
Evolutionary mechanism design: a review
Phelps, S., McBurney, P., & Parsons, S. (2009) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-009-9108-7 · Cited by 111 · see citing works
Privacy-aware mechanism design
Kobbi Nissim, B., Orlandi, C., & Rann Smorodinsky, B. (2012) · ACM Conference on Electronic Commerce (EC) · doi:10.1145/2229012.2229073 · Cited by 110 · see citing works
Rothschild, D. M. (2009) · Public Opinion Quarterly · doi:10.1093/poq/nfp082 · Cited by 106 · see citing works
Incentives for Information Production in Markets where Prices Affect Real Investment
Dow, J., Itay Goldstein, B., & Guembel, A. (2017) · Journal of the European Economic Association · doi:10.1093/jeea/jvw023 · Cited by 106 · see citing works
Leigh, A., & Wolfers, J. J. (2006) · Economic Record · doi:10.1111/j.1475-4932.2006.00343.x · Cited by 105 · see citing works
Self-citationOttaviani, M., & Sørensen, P. N. (2015) · American Economic Review · doi:10.1257/aer.20120881 · Cited by 95 · see citing works
Predicting replication outcomes in the Many Labs 2 study
Forsell, E., Viganola, D., Pfeiffer, T., Almenberg, J., Wilson, B., Chen, Y.-L., Nosek, B. A., Johannesson, M., & Dreber, A. (2018) · Journal of Economic Psychology · doi:10.1016/j.joep.2018.10.009 · Cited by 97 · see citing works
Quid Pro Quo? Corporate Returns to Campaign Contributions
Fowler, A., Garro, H., & Spenkuch, J. L. (2019) · The Journal of Politics · doi:10.1086/707307 · Cited by 104 · see citing works
Improving Out-of-Sample Predictions Using Response Times and a Model of the Decision ProcessPreprint
Clithero, J. A. (2016) · SSRN Electronic Journal · doi:10.1016/j.jebo.2018.02.007 · Cited by 99 · see citing works
Identification of Lead Users for Consumer Products via Virtual Stock Markets*
Spann, M., Ernst, H., Skiera, B., & Soll, J. H. (2009) · Journal of Product Innovation Management · doi:10.1111/j.1540-5885.2009.00661.x · Cited by 102 · see citing works
Brexit Uncertainty and Trade Disintegration
Graziano, A., Handley, K., & Limão, N. (2020) · The Economic Journal · doi:10.1093/ej/ueaa113 · Cited by 101 · see citing works
Stekler, H. O., Sendor, D., & Verlander, R. (2010) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2010.01.003 · Cited by 99 · see citing works
Swarm intelligence in humans: diversity can trump ability
Krause, S., James, R., Faria, J. J., Ruxton, G. D., & Krause, J. (2011) · Animal Behaviour · doi:10.1016/j.anbehav.2010.12.018 · Cited by 99 · see citing works
Supply chain information sharing in a macro prediction market
Guo, Z., Fang, F., & Whinston, A. B. (2006) · Decision Support Systems · doi:10.1016/j.dss.2006.05.003 · Cited by 99 · see citing works
Classification of intraday S&P500 returns with a Random Forest
Lohrmann, C., & Luukka, P. (2018) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2018.08.004 · Cited by 98 · see citing works
Vlastakis, N., Dotsis, G., & Markellos, R. N. (2007) · Journal of Forecasting · doi:10.1002/for.1085 · Cited by 97 · see citing works
Prediction accuracy of different market structures – bookmakers versus a betting exchange
Franck, E., Verbeek, E., & Nüesch, S. (2010) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2010.01.004 · Cited by 107 · see citing works
Making decisions based on the preferences of multiple agents
Conitzer, V. (2010) · Communications of the ACM · doi:10.1145/1666420.1666442 · Cited by 93 · see citing works
Rate or Trade? Identifying Winning Ideas in Open Idea Sourcing
Blohm, I., Riedl, C., Füller, J., & Leimeister, J. M. (2016) · Information Systems Research · doi:10.1287/isre.2015.0605 · Cited by 93 · see citing works
How psychological framing affects economic market prices in the lab and field
Sonnemann, U., Camerer, C. F., Fox, C. R., & Langer, T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1206326110 · Cited by 86 · see citing works
Blockchain-Based Decentralized Application: A Survey
Zheng, P., Jiang, Z., Wu, J., & Zheng, Z. (2023) · IEEE Open Journal of the Computer Society · doi:10.1109/ojcs.2023.3251854 · Cited by 90 · see citing works
Momentum and Social Learning in Presidential Primaries
Knight, B. G., & SCHIFF, N. M. (2010) · Journal of Political Economy · doi:10.1086/658372 · Cited by 90 · see citing works
Understanding Investor Sentiment: The Case of Soccer
Bernile, G., & Lyandres, E. (2011) · Financial Management · doi:10.1111/j.1755-053x.2011.01145.x · Cited by 88 · see citing works
The economics of options-implied inflation probability density functions
Kitsul, Y., & Wright, J. H. (2013) · Journal of Financial Economics · doi:10.1016/j.jfineco.2013.08.013 · Cited by 87 · see citing works
Incentives for Information Production in Markets Where Prices Affect Real InvestmentPreprint
Dow, J., Itay Goldstein, B., & Guembel, A. (2013) · SSRN Electronic Journal · doi:10.2139/ssrn.2356994 · Cited by 87 · see citing works
Law, E., & von Ahn, L. (2011) · Synthesis lectures on artificial intelligence and machine learning · doi:10.2200/s00371ed1v01y201107aim013 · Cited by 86 · see citing works
Online foresight platforms: Evidence for their impact on scenario planning & strategic foresight
Raford, N. (2014) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2014.03.008 · Cited by 85 · see citing works
The Impact of Terrorism on Financial Markets: An Empirical StudyPreprint
Chesney, M., Karaman, M., & Reshetar, G. (2010) · SSRN Electronic Journal · doi:10.2139/ssrn.1579674 · Cited by 84 · see citing works
A live experiment on approval voting
Laslier, J., & der Straeten, K. V. (2007) · Experimental Economics · doi:10.1007/s10683-006-9149-6 · Cited by 83 · see citing works
PROXYING FOR UNOBSERVABLE VARIABLES WITH INTERNET DOCUMENT-FREQUENCY
Sáiz, A., & Simonsohn, U. (2013) · Journal of the European Economic Association · doi:10.1111/j.1542-4774.2012.01110.x · Cited by 79 · see citing works
Cybersecurity Strategies: The QuERIES Methodology
Carin, L., Cybenko, G. V., & Hughes, J. A. (2008) · Computer · doi:10.1109/mc.2008.295 · Cited by 79 · see citing works
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
