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
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/26748 |
| Date | 10 June 1985 |
| Creators | Wiese, Arthur Michael |
| Contributors | Cornelius, James |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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