Yield and Price Forecasting for Stochastic Crop Decision Planning

Crop decision planning is an important part of effective farm management. Because of the many uncertain factors such as weather variations, technology advances, and crop yields and prices, all of which prove to change considerably, decision planning can be very complex. The focus of this paper is to develop accurate yield and price forecasting models to aid in decision planning. For yield forecasting, we establish a crop-weather model using regression methods. We propose a semiparametric regression model, which accounts for both withinand between-year relationships in the data. For price forecasting, we develop a futures-based model, which predicts the cash price from futures price and basis. We estimate the yearly basis pattern using a functional model-based approach and adjust the basis estimates with the futures prices to forecast the crop cash price. In both forecasting models, we estimate confidence bands for the predictions that can be further integrated in the decision planning model.