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USDA Livestock Price Forecasts: A Comprehensive Evaluation

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  • Sanders, Dwight R.
  • Manfredo, Mark R.

Abstract

One-step-ahead forecasts of quarterly live cattle, live hog, and broiler prices are evaluated under two general approaches: accuracy-based measures and classification based measures which test the ability to categorize price movements directionally or within a forecasted range. Results suggest U.S. Department of Agriculture (USDA) price forecasts are not optimal. Broiler price forecasts are biased, and all the forecast series tend to repeat errors. While the USDA forecasts are more accurate than those of a univariate AR(4) time-series model, evidence suggests the USDA live cattle forecasts could be improved with a composite forecast that includes a time-series alternative. Despite this, the USDA correctly identifies the direction of price change in at least 70% of its forecasts over the sample period. Furthermore, actual prices fall within the USDA's forecasted range 48% of the time for broilers, but only 35% for hogs. Finally, there is some evidence that the USDA's price forecasting accuracy has improved over time for broilers, but has gotten marginally worse for hogs.

Suggested Citation

  • Sanders, Dwight R. & Manfredo, Mark R., 2003. "USDA Livestock Price Forecasts: A Comprehensive Evaluation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(2), pages 1-19, August.
    • Handle: RePEc:ags:jlaare:31101
    DOI: 10.22004/ag.econ.31101
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    Cited by:

    1. Guney, Selin, 2015. "An evaluation of price forecasts of the cattle market under structural changes," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205109, Agricultural and Applied Economics Association.
    2. Chen, Wei & Kauffman, Dan & Taylor, Daniel B. & Peterson, Everett B., 2008. "Managing Flounder Openings for Maximum Revenue," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6193, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Sanders, Dwight R. & Manfredo, Mark R., 2005. "A Test of Forecast Consistency Using USDA Livestock Price Forecasts," 2005 Conference, April 18-19, 2005, St. Louis, Missouri 19042, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    4. Bahram Sanginabadi, 2018. "USDA Forecasts: A meta-analysis study," Papers 1801.06575, arXiv.org.
    5. No, Sung Chul & Salassi, Michael E., 2006. "Dynamic Analysis and Forecasts of Rough Rice Price under Government Price Support Program: An Application of Bayesian VAR," 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida 35279, Southern Agricultural Economics Association.
    6. Tianyang Zhang & Ziran Li, 2022. "Can a rational expectation storage model explain the USDA ending grain stocks forecast errors?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 313-337, March.
    7. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    8. Adjemian, Michael K. & Bruno, Valentina G. & Robe, Michel A., 2016. "Forward‐Looking USDA Price Forecasts," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235931, Agricultural and Applied Economics Association.
    9. MacDonald, Stephen & Ash, Mark & Cooke, Bryce, 2017. "The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets," MPRA Paper 87545, University Library of Munich, Germany.
    10. repec:ags:aaea22:335690 is not listed on IDEAS
    11. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    12. Evelyn V. Colino & Scott H. Irwin, 2010. "Outlook vs. Futures: Three Decades of Evidence in Hog and Cattle Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 1-15.
    13. Michael K. Adjemian & Valentina G. Bruno & Michel A. Robe, 2020. "Incorporating Uncertainty into USDA Commodity Price Forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 696-712, March.
    14. Isengildina-Massa, Olga & Irwin, Scott H. & Good, Darrel L., 2008. "Quantile Regression Methods of Estimating Confidence Intervals for WASDE Price Forecasts," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6409, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    15. Isengildina-Massa, Olga & Sharp, Julia L., 2013. "Interval Forecast Comparison," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150791, Agricultural and Applied Economics Association.
    16. Olga Isengildina‐Massa & Berna Karali & Todd H. Kuethe & Ani L. Katchova, 2021. "Joint Evaluation of the System of USDA's Farm Income Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(3), pages 1140-1160, September.
    17. Elham Rahmani & Mohammad Khatami & Emma Stephens, 2024. "Using Probabilistic Machine Learning Methods to Improve Beef Cattle Price Modeling and Promote Beef Production Efficiency and Sustainability in Canada," Sustainability, MDPI, vol. 16(5), pages 1-19, February.

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