Because of the high volatility of prices of agricultural commodities over the past decade, the importance of accurate price forecasting for decision makers has become even more acute. This paper reviews literature on forecasting and evaluation. An application with forecasting U .S. hog prices is presented which includes both economic and statistical evaluation measures. Seven forecasting approaches are described and their performances are examined over 24 quarters from 1976 to 1981. These methods include exponential smoothing, an autoregressive integrated moving average process, an econometric model, expert judgement, and a composite forecasting approach. The application gives results which support previous findings in the forecasting literature and suggests that forecasting methods can provide valuable information to the decision maker.
KEY WORDS Forecasting Evaluation Hog prices Agricuitural application
The uncertainty of future price, production, and consumption levels makes agricultural market strategy and investment planning difficult. Low demand price elasticities for most agricultural products coupled with frequently large seasonal changes in production provide the setting for rather large price fluctuations (Tomek and Robinson, 1972, pp.196-197). In such an environment, a detailed listing of various courses of action, their consequences under alternative outcomes, and a statement of well-being under each is, of course, recommended. Forecasts of commodity price changes given specified market conditions provide information necessary to carry out the marketing or investment planning process. The intended use of the forecasts, in large degree, influences or dictates the type of model selected to generate the forecast and the criteria used to evaluate the forecasting technique. The objective of avoiding extremely large forecast errors might suggest a forecast approach different from that associated with the goal of predicting price turning points in the market. Similarly, short-run marketing strategies would require a different set of predictions than long-run investment planning.
This paper is organized to achieve three objectives. First, alternative methods of forecast generation are examined. Second, alternative evaluation procedures are explored. Within this list,