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Prediction markets: an experimental approach to forecasting cattle on feed

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Author Info

  • R. Karina Gallardo
  • B. Wade Brorsen
  • Jayson Lusk

Abstract

Purpose – The purpose of this paper is to use prediction markets to forecast an agricultural event: United States Department of Agriculture's number of cattle on feed (COF). Prediction markets are increasingly popular forecast tools due to their flexibility and proven accuracy to forecast a diverse array of events. Design/methodology/approach – During spring 2008, a market was constructed comprised of student traders in which they bought and sold contracts whose value was contingent on the number of COF to be reported on April 18, 2008. During a nine-week period, students were presented three types of contracts to forecast the number of COF. To estimate forecasts a uniform price sealed bid auction mechanism was used. Findings – The results showed that prediction markets forecasted 11.5 million head on feed, which was about 1.6 percent lower than the actual number of COF (11.684 million). The prediction market also fared slightly worse than analysts' predictions, which on average suggested there would be about 11.795 million head (an over-estimate of about 1 percent). Originality/value – The contribution of this study was not to provide conclusive evidence on the efficacy of using prediction markets to forecast COF, but rather to present an empirical example that will spark interest among agricultural economists on the promises and pitfalls of a research method that has been relatively underutilized in the agricultural economics literature.

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Bibliographic Info

Article provided by Emerald Group Publishing in its journal Agricultural Finance Review.

Volume (Year): 70 (2010)
Issue (Month): 3 (November)
Pages: 414-426

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Handle: RePEc:eme:afrpps:v:70:y:2010:i:3:p:414-426

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Web page: http://www.emeraldinsight.com

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Related research

Keywords: Animal feed; Experimental design; Forecasting; United States of America;

References

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  1. Good, Darrel L. & Irwin, Scott H. & Isengildina, Olga, 2006. "The Value of USDA Situation and Outlook Information in Hog and Cattle Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 31(02), August.
  2. repec:reg:rpubli:259 is not listed on IDEAS
  3. Dhuyvetter, Kevin C. & Schroeder, Ted C. & Parcell, Joseph L., 1997. "The Effect of USDA Cattle on Feed Reports on Feeder Cattle Futures Prices," 1997 Annual Meeting, July 13-16, 1997, Reno\Sparks, Nevada 35751, Western Agricultural Economics Association.
  4. 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.
  5. Frank, Julieta & Garcia, Philip & Irwin, Scott H., 2007. "To What Surprises Do Hog Futures Markets Respond?," 2007 Conference, April 16-17, 2007, Chicago, Illinois 37573, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  6. Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
  7. Robert J. Shiller, 1998. "Human Behavior and the Efficiency of the Financial System," Cowles Foundation Discussion Papers 1172, Cowles Foundation for Research in Economics, Yale University.
  8. Wolfers, Justin & Zitzewitz, Eric, 2006. "Five Open Questions About Prediction Markets," IZA Discussion Papers 1975, Institute for the Study of Labor (IZA).
  9. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, vol. 82(5), pages 1142-61, December.
  10. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
  11. John M. Marsh, 2003. "Impacts of Declining U.S. Retail Beef Demand on Farm-Level Beef Prices and Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 902-913.
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