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When do the USDA forecasters make mistakes?

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  • Olga Isengildina-Massa
  • Berna Karali
  • Scott H. Irwin

Abstract

This study analysed forecasts for all US corn, soya bean and wheat categories published within the World Agricultural Supply and Demand Estimates (WASDE ) reports over the 1987/88 through 2009/10 marketing years in an attempt to identify patterns and better understand when the USDA forecasters make mistakes. Two general sources of errors were investigated: behavioural and macroeconomic factors. The first objective was to examine how these factors affect the size of the forecast error and the second concentrated on the direction of the error due to these effects. Our findings suggest that the largest increase in the size of USDA forecast errors was associated with structural changes in commodity markets that took place in the mid-2000s. Corn, soya bean and wheat forecast errors also grew during the periods of economic growth and with changes in exchange rates, while inflation and changes in oil price had a much smaller impact. With respect to behavioural sources, we identified patterns consistent with leniency and pessimism across different categories. Predictability of forecast errors based on the information available at the time the forecasts are made provides evidence of inefficiency and suggests that these forecasts may be improved using the findings of this study.

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  • Olga Isengildina-Massa & Berna Karali & Scott H. Irwin, 2013. "When do the USDA forecasters make mistakes?," Applied Economics, Taylor & Francis Journals, vol. 45(36), pages 5086-5103, December.
    • Handle: RePEc:taf:applec:v:45:y:2013:i:36:p:5086-5103
    DOI: 10.1080/00036846.2013.818213
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    Cited by:

    1. 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.
    2. Zhang, Tianyang & Li, Ziran, 2018. "How Well Do Rational Expectations Storage Model Forecast Crop Ending Stocks?," 2018 Annual Meeting, August 5-7, Washington, D.C. 273803, Agricultural and Applied Economics Association.
    3. Li, Ziran & Li, Ding & Zhang, Tengfei & Zhang, Tianyang, 2022. "Climate impact on the USDA ending stocks forecast errors," Finance Research Letters, Elsevier, vol. 48(C).
    4. Bahram Sanginabadi, 2018. "USDA Forecasts: A meta-analysis study," Papers 1801.06575, arXiv.org.
    5. 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.

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