Doctoral Dissertations

Date of Award

8-2012

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Natural Resources

Major Professor

Donald G. Hodges

Committee Members

Jason Henning, Dayton Lambert, Christian Vossler

Abstract

It is a common belief that the presence of forest industry and associated wood demand will result in forest management of procurement areas. The following essays examined the relationship between mill demand and procurement areas by assessing the likelihood of forest management and the ability to predict future wood output. The first study investigates the likelihood of forest management given proximity to mills using a multivariate probit model, incorporating forest characteristics and primary wood-using mill information collected by the USDA Forest Service Forest Inventory and Analysis and the Timber Products Output (TPO) survey. The second essay explores the use of vector autoregressive methods to forecast county pulpwood output using pulpwood production data collected by TPO. We evaluated a group of forecasting methods in the vector autoregressive family and compared the models forecast accuracy to that of the commonly used step-forward methodology. Results from the first study indicate that mill proximity has a low impact on private forest landowner management decisions. This information may prove useful to industry and state foresters when dealing with increases in demand arising from new markets, such as bioenergy. Forecasts from the second essay highlight the cross-county differences in terms of pulpwood output in response to national demand. While the macroeconomic series helped predict output activity in some counties, a group of counties displayed no correlation between product output and demand measured by the national variables. The results emphasize the need for disaggregated analysis to capture the dynamics of the procurement areas and primary mills.

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