Modeling local timber harvests using a set of error-related economic relations Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/nv9355645

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  • 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.
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