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Raw product value of vegetables for processing in the Northwest used to be established by a competitive market involving proprietary processors and growers. Due to the relocation of proprietary processors to the Midwest, this competitive market has eroded forcing cooperative processors to seek other means to set raw product values. In the absence of a competitive market for raw product, cooperatives must rely on an average of last year's prices paid by processors in a given region to value raw product. This method of lagged averages may be resulting in misallocated contracted acreage to grower-members of cooperatives, and inappropriate production levels of the processed good given market conditions. Therefore, the principal objective of this research is to develop and evaluate alternative methods of forecasting raw product value. Since the market for processed vegetables at the retail level is competitive, one alternative method employed was to use a forecast of supply and determinants of demand affecting retail price to forecast raw product value. These explanatory variables were regressed against raw product values of various crops obtained from a northwest processing and marketing cooperative. The raw product values were expressed as net returns/acre to the crops under investigation. The estimated equations, which had adjusted R²'s ranging from .267 to .851, were used to forecast raw product value. A second forecasting method investigated in this study was an exponential smoothing model. Raw product value forecasts were generated over two different time horizons, identified by the cooperatives' accounting procedures. The two alternative forecasting methods were compared to each other, and to the method currently in use by the cooperative, with the aim of determining the most accurate forecasting technique. Results showed that both the econometric and smoothing approaches fit the data better over the estimation period than did a naive lagged price estimate resembling the present method in use by the cooperative. The econometric method also fit the data better than did the smoothing approach. The econometric model provided poor forecasts for the longer forecast horizon, but proved to be effective in the shorter. The smoothing technique forecasted more effectively in the longer forecast horizon as compared with the shorter. These results suggest the importance of the forecast horizon in determining the more appropriate forecasting technique. Both forecasting techniques proposed in this study produced forecasts which were more accurate than the cooperative's present method at least half of the time. This suggests that viable alternatives to the present method of establishing raw product value exist for agricultural cooperatives. / Graduation date: 1986