IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/9059.html
   My bibliography  Save this paper

Prediction Markets for Economic Forecasting

Author

Listed:
  • Snowberg, Erik
  • Wolfers, Justin
  • Zitzewitz, Eric

Abstract

Prediction markets--markets used to forecast future events--have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by economic forecasters. We show that prediction markets have a number of attractive features: they quickly incorporate new information, are largely efficient, and impervious to manipulation. Moreover, markets generally exhibit lower statistical errors than professional forecasters and polls. Finally, we show how markets can be used to both uncover the economic model behind forecasts, as well as test existing economic models.

Suggested Citation

  • Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2012. "Prediction Markets for Economic Forecasting," CEPR Discussion Papers 9059, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:9059
    as

    Download full text from publisher

    File URL: http://www.cepr.org/active/publications/discussion_papers/dp.php?dpno=9059
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    2. Colin F. Camerer, 1998. "Can Asset Markets Be Manipulated? A Field Experiment with Racetrack Betting," Journal of Political Economy, University of Chicago Press, vol. 106(3), pages 457-482, June.
    3. Koleman Strumpf, 2009. "Introduction to Special Issue on Corporate Applications of Prediction Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 3(1), pages 1, April.
    4. Göran Therborn & K.C. Ho, 2009. "Introduction," City, Taylor & Francis Journals, vol. 13(1), pages 53-62, March.
    5. Plott, Charles R & Sunder, Shyam, 1982. "Efficiency of Experimental Security Markets with Insider Information: An Application of Rational-Expectations Models," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 663-698, August.
    6. Berg, Joyce & Forsythe, Robert & Nelson, Forrest & Rietz, Thomas, 2008. "Results from a Dozen Years of Election Futures Markets Research," Handbook of Experimental Economics Results, Elsevier.
    7. Erik Snowberg & Justin Wolfers, 2010. "Explaining the Favorite-Long Shot Bias: Is it Risk-Love or Misperceptions?," Journal of Political Economy, University of Chicago Press, vol. 118(4), pages 723-746, August.
    8. Plott, Charles R & Sunder, Shyam, 1988. "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Econometrica, Econometric Society, vol. 56(5), pages 1085-1118, September.
    9. anonymous, 2000. "Directive of the Federal Open Market Committee," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Feb, pages 101-101.
    10. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    11. Erik Snowberg & Justin Wolfers & Eric Zitzewitz, 2007. "Partisan Impacts on the Economy: Evidence from Prediction Markets and Close Elections," The Quarterly Journal of Economics, Oxford University Press, vol. 122(2), pages 807-829.
    12. anonymous, 2000. "Federal Open Market Committee directive," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Aug, pages 582-582.
    13. Bruno Jullien & Bernard Salanie, 2000. "Estimating Preferences under Risk: The Case of Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 108(3), pages 503-530, June.
    14. Erik Snowberg & Justin Wolfers & Eric Zitzewitz, 2011. "How Prediction Markets can Save Event Studies," CAMA Working Papers 2011-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Refet Gürkaynak & Justin Wolfers, 2005. "Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty, and Risk," NBER Chapters,in: NBER International Seminar on Macroeconomics 2005, pages 11-50 National Bureau of Economic Research, Inc.
    16. Brian Spears & Christina LaComb & John Interrante & Janet Barnett & Deniz Senturk-Dogonaksoy, 2009. "Examining Trader Behavior in Idea Markets: An Implementation of GE's Imagination Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 3(1), pages 17-39, April.
    17. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, Elsevier.
    18. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    19. Tom W. Bell, 2009. "Private Prediction Markets and the Law," Journal of Prediction Markets, University of Buckingham Press, vol. 3(1), pages 89-110, April.
    20. Duffee, Gregory, 2013. "Forecasting Interest Rates," Handbook of Economic Forecasting, Elsevier.
    21. anonymous, 2000. "Federal Open Market Committee directive," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Nov, pages 740-740.
    22. Henry Berg & Todd A. Proebsting, 2009. "Hanson's Automated Market Maker," Journal of Prediction Markets, University of Buckingham Press, vol. 3(1), pages 45-59, April.
    23. Hanson, Robin & Oprea, Ryan & Porter, David, 2006. "Information aggregation and manipulation in an experimental market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(4), pages 449-459, August.
    24. repec:spr:infosf:v:5:y:2003:i:1:d:10.1023_a:1022058209073 is not listed on IDEAS
    25. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    26. repec:spr:infosf:v:5:y:2003:i:1:d:10.1023_a:1022002107255 is not listed on IDEAS
    27. 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, INFORMS, vol. 55(3), pages 348-361, March.
    28. David Laster & Paul Bennett & In Sun Geoum, 1999. "Rational Bias in Macroeconomic Forecasts," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 293-318.
    29. Pedro Santa-Clara & Rossen Valkanov, 2003. "The Presidential Puzzle: Political Cycles and the Stock Market," Journal of Finance, American Finance Association, vol. 58(5), pages 1841-1872, October.
    30. Wolfers, Justin & Zitzewitz, Eric, 2006. "Interpreting Prediction Market Prices as Probabilities," IZA Discussion Papers 2092, Institute for the Study of Labor (IZA).
    31. Leigh, Andrew & Wolfers, Justin & Zitzewitz, Eric, 2003. "What do Financial Markets Think of War in Iraq?," Research Papers 1785, Stanford University, Graduate School of Business.
    32. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    33. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    34. Robin Hanson, 2007. "Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 3-15, February.
    35. Robin Hanson & Ryan Oprea, 2009. "A Manipulator Can Aid Prediction Market Accuracy," Economica, London School of Economics and Political Science, vol. 76(302), pages 304-314, April.
    36. anonymous, 2000. "Tapping an untapped market," Banking and Community Perspectives, Federal Reserve Bank of Dallas, issue Q3, pages 1-2.
    37. repec:reg:rpubli:460 is not listed on IDEAS
    38. Bakshi, Gurdip & Madan, Dilip, 2000. "Spanning and derivative-security valuation," Journal of Financial Economics, Elsevier, vol. 55(2), pages 205-238, February.
    39. Steven Gjerstad, 2004. "Risk Aversion, Beliefs, and Prediction Market Equilibrium," Microeconomics 0411002, EconWPA.
    40. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, Elsevier.
    41. Rubinstein, Mark, 1994. " Implied Binomial Trees," Journal of Finance, American Finance Association, vol. 49(3), pages 771-818, July.
    42. anonymous, 2000. "Strengthening the emerging market economies," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 44(Jun), pages 228-231.
    43. ., 2000. "Notes on the theory of markets," Chapters,in: Macroeconomic Instability and Coordination, chapter 12 Edward Elgar Publishing.
    44. Jim Lavoie, 2009. "The Innovation Engine at Rite-Solutions: Lessons from the CEO," Journal of Prediction Markets, University of Buckingham Press, vol. 3(1), pages 1-11, April.
    45. Mark Rubinstein., 1994. "Implied Binomial Trees," Research Program in Finance Working Papers RPF-232, University of California at Berkeley.
    46. Georgios Tziralis & Ilias Tatsiopoulos, 2007. "Prediction Markets: An Extended Literature Review," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 75-91, February.
    47. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, Elsevier.
    48. Michael Abramowicz, 2007. "The Hidden Beauty of the Quadratic Market Scoring Rule: A Uniform Liquidity Market Maker, with Variations," Journal of Prediction Markets, University of Buckingham Press, vol. 1(2), pages 111-125, July.
    49. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-590, June.
    50. P. Carr & D. Madan, 2001. "Optimal positioning in derivative securities," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 19-37.
    51. Paul W. Rhode & Koleman S. Strumpf, 2004. "Historical Presidential Betting Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 127-141, Spring.
    52. Colin Camerer, 1998. "Can asset markets be manipulated? A field experiment with racetrack betting," Natural Field Experiments 00222, The Field Experiments Website.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    2. Refet S. Gürkaynak & Jonathan H. Wright, 2013. "Identification and Inference Using Event Studies," Manchester School, University of Manchester, vol. 81, pages 48-65, September.
    3. Constantin ANGHELACHE & Ioan Constantin DIMA & Mãdãlina-Gabriela ANGHEL, 2016. "Using the Autoregressive Model for the Economic Forecast during the Period 2014- 2018," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 21-31, January.
    4. Mueller-Frank, Manuel, 2014. "Does one Bayesian make a difference?," Journal of Economic Theory, Elsevier, vol. 154(C), pages 423-452.
    5. Boleslavsky, Raphael & Kelly, David L. & Taylor, Curtis R., 2017. "Selloffs, bailouts, and feedback: Can asset markets inform policy?," Journal of Economic Theory, Elsevier, vol. 169(C), pages 294-343.
    6. Polson Nicholas G. & Stern Hal S., 2015. "The implied volatility of a sports game," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(3), pages 145-153, September.
    7. Mikuláš Gangur & Miroslav Plevný, 2014. "Tools for Consumer Rights Protection in the Prediction of Electronic Virtual Market and Technological Changes," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(36), pages 578-578, May.
    8. Lionel Page & Christoph Siemroth, 2018. "How much information is incorporated in financial asset prices? Experimental Evidence," QuBE Working Papers 054, QUT Business School.
    9. repec:oup:restud:v:82:y:2015:i:4:p:1309-1341. is not listed on IDEAS
    10. Linardi, Sera, 2017. "Accounting for noise in the microfoundations of information aggregation," Games and Economic Behavior, Elsevier, vol. 101(C), pages 334-353.
    11. Gabriela Victoria ANGHELACHE & Prof. Vladimir MODRAK & Madalina Gabriela ANGHEL & Marius POPOVICI, 2016. "Portfolio Management and Predictability," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 59-63, January.

    More about this item

    Keywords

    forecasting; prediction markets;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cpr:ceprdp:9059. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.