| Traditionally, agricultural forecasts, whether for the coming year or several years into the future, have been based on assumptions of normal weather and trend crop yields. That weather is seldom normal and that yields seldom fit trends are well recognized. However, relatively little attention has been given to projecting crop yields stochastically even though computer capacity and software programs are available to do so. One reason is that the task is more challenging than to assign standard deviations to various crop yields and simulate normal distributions using random number generators. For one, deviations of crop yields from trends may be correlated especially if the locations of the crops overlap such as is the case with US corn and soybeans. To... |
