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

Tianyang Zhang and Ziran Li

Journal of Futures Markets, 2022, vol. 42, issue 3, 313-337

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.

Date: 2022
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