Deriving Forecast Probability Distributions of Harvest‐Time Corn Futures Prices

Preharvest corn price forecasts are typically presented as price ranges or point estimates, while the probabilities associated with alternative grain price forecast scenarios are usually not identified. For example, United States Department of Agriculture (USDA) preharvest price forecasts are typically given as price ranges, while preharvest forecasts from university extension and other private sources are often given as point estimates. When alternative market scenario probabilities are provided, they are often based on rudimentary statistical analysis of historic weather conditions and/or the analyst's intuition rather than on accepted econometric methods. Preharvest grain price probability information would be useful to farmers, grain buyers, and processors in making price risk management decisions. Farmers implicitly make probability judgements regarding the likelihood of alternative supply, demand, and price scenarios as they carry out preharvest grain marketing strategies. All grain buyers and sellers could benefit by knowing the probability of financially-adverse price outcomes. With accurate price forecast probability information, probability-based price risk management strategies could be developed to limit the risk of financial loss to the farmer or the firm. A number of structural models of grain market supply and demand have been developed for forecasting and policy analysis purposes. Examples are found in Houck, Ryan, and Subotnik; Chen; Arzac and Wilkinson; and Westhoff et al. Reduced form equations from these multiple equation systems guide the