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Abstract

Managers of businesses that involve agricultural commodities need price forecasts in order to manage the risk in either the sale or purchase of agricultural commodities. This paper examines whether commodity price forecasting model performance can be improved by the inclusion of price forecasts for other commodities within the model specification. We estimate 760 dfferent models to forecast the prices of hog, cattle, corn, and soybean and find strong support for the inclusion of other commodity price forecasts in the best forecasting models. Unfortunately, the out-of-sample performance of these models is mixed at best. Still, the results suggest more work is called for to determine how best to use other commodity price forecasts to improve forecasting performance.

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