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Can a rational expectation storage model explain the USDA ending grain stocks forecast errors?

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  • Tianyang Zhang
  • Ziran Li

Abstract

We examine whether, and to what extent, a rational expectation storage model can be used to explain the US Department of Agriculture (USDA) ending stocks forecast errors for corn, soybean, and wheat. We show there is a predictable component of forecast errors from 1980/81 to 2018/19 that can partially be explained by the temporal basis and monthly stocks, two important factors from a rational expectation storage model that codetermines carry. The USDA ending stocks forecasts can be improved by 7.1%, 7.2%, and 4.5% for corn, soybean, and wheat, respectively. The improvement is most significant when the last year's carry is small.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:jfutmk:v:42:y:2022:i:3:p:313-337
    DOI: 10.1002/fut.22282
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    References listed on IDEAS

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    Cited by:

    1. 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).

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