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Empirical Confidence Intervals for WASDE Forecasts of Corn, Soybean and Wheat Prices

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  • Isengildina, Olga
  • Irwin, Scott H.
  • Good, Darrel L.

Abstract

This study suggests that confidence intervals for WASDE forecasts of corn, soybean, and wheat prices may be improved if they are estimated using an empirical approach. Empirical confidence intervals are calculated following Williams and Goodman's (1971) method and use historical forecast errors to estimate forecast error distributions which is then used to predict confidence limits for future forecast errors. Three procedures for empirical distribution estimation are compared: 1) histogram, 2) changing distribution, 3) fixed distribution. The results suggest that the fixed distribution approach using logistic distribution provided accurate confidence intervals for WASDE corn, soybean, and wheat price forecasts.

Suggested Citation

  • Isengildina, Olga & Irwin, Scott H. & Good, Darrel L., 2006. "Empirical Confidence Intervals for WASDE Forecasts of Corn, Soybean and Wheat Prices," 2006 Conference, April 17-18, 2006, St. Louis, Missouri 18995, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    • Handle: RePEc:ags:ncrsix:18995
    DOI: 10.22004/ag.econ.18995
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    References listed on IDEAS

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    1. David M. Prescott & Thanasis Stengos, 1987. "Bootstrapping Confidence Intervals: An Application to Forecasting the Supply of Pork," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(2), pages 266-273.
    2. Victor Zarnowitz, 1992. "Business Cycles: Theory, History, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number zarn92-1.
    3. Stanley Smith & Terry Sincich, 1988. "Stability over time in the distribution of population forecast errors," Demography, Springer;Population Association of America (PAA), vol. 25(3), pages 461-474, August.
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    1. Hedtrich, F. & Loy, J.-P. & Müller, R.A.E., 2010. "Prognosen auf Agrarmärkten: Prediction Markets – eine innovative Prognosemethode auch für die Landwirtschaft?," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 45, March.

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