Data limitations often limit the time framework in which agricultural commodities are modeled and prices forecasted. Our research provides a technique to alleviate this constraint. By combining an annual econometric model with a quarterly ARIMA model, quarterly forecasts can be made which utilize the theoretical and structural foundations in econometric modeling.