An Alternative Method to Forecast Season-Average Price for U.S. Corn

Price forecasts are critical to market participants when making production and marketing decisions and to policymakers who administer commodity programs and assess the market impact of domestic or international events. With the exceptionally volatile conditions experienced in the corn market since 2006, the need for price forecasting has become even more critical. The purpose of this paper is to explore an alternative econometric procedure to forecast the season-average price of corn for U.S. producers, a relatively under-researched price forecast. The new method performs well against two widely-watched season-average price forecasts, i.e., the World Agricultural Supply and Demand Estimates and the futures-based forecasts, in particular at the beginning of the post-harvest season. Additionally, the proposed forecast performs no worse or better than the futures-based forecasts at the beginning of the forecast cycle, as well as from November to August during the marketing year. We attribute the satisfactory performance of the proposed forecast to the model's ability to assign heterogeneous weights to futures and cash prices depending on the underlying market conditions. Furthermore, the performance of the proposed forecast tends to improve when the market becomes more volatile