Abstract:
Recent changes in public timber supplies in the Pacific Northwest have increased the
importance of the role private timber plays in the forest products industry and local
communities. Most economic models of timber supply, however, have emphasized
national or regional markets where data are adequate and statistical testing methodologies
relatively well documented. Little attention has been paid to modeling timber harvests at
the local market level. This study attempts to develop an economic model to explain
timber harvests at the county level where previous efforts, which have emphasized a
simultaneous equations approach, have met with poor results.
A set of economic timber harvest relations was tested for eight counties in Northwest
Oregon using the seemingly unrelated regressions (SUR) technique. For industrial
landowners, a present net worth maximization model was used where harvest is a function
of stumpage price, discount rate, and level of growing stock inventory. For non-industrial
private landowners a utility maximization model was used where harvest is a function of
stumpage price, personal income, and level of growing stock inventory. Parameter
coefficient estimates developed using SUR were compared with those developed using
ordinary least squares (OLS) to evaluate the adequacy of the error-related approach.
Results of the study showed significant contemporaneous correlation between harvests in
the counties of the study region for both industrial and non-industrial landowners.
Therefore parameter coefficient estimates obtained using SEJR are more efficient than
those obtained with OLS. The greatest improvements in modeling efficiency were
observed for non-industrial owners. Furthermore, the present net worth maximization
model used for industrial landowners appears to reasonably represent the harvest
motivations of those landowners. However, the high standard errors and poor
explanatory power observed in the non-industrial landowner estimations suggest that the
utility maximization model used for those landowners needs to be re-evaluated.
For both landowners, the level of growing stock inventory plays a large role in
determining timber harvests. Policy makers and analysts interested in predicting countylevel
timber harvests should advocate the collection of more extensive county-level
inventory information than is currently collected. The recording of county-specific price
information would also prove valuable for future analyses by eliminating the need for a
proxy variable.
