Date of Award

5-2013

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Applied Economics

Committee Chair/Advisor

Templeton, Scott R

Committee Member

Cushing , Tamara

Committee Member

Brannan , James

Committee Member

Lamie , R D

Abstract

In the first essay, a critical examination of three commonly used stochastic price processes is presented. Each process is described and rejected as a possible model of lumber futures prices. A mean reverting generalized autoregressive conditional heteroskedasticity (GARCH) model, developed by Bollerslev (1986), is proposed as a stochastic process for lumber futures prices. The essay provides the steps that should be taken to ensure that a proper price process is used in each application.
In the second essay, a flexible harvesting strategy known as the reservation price strategy is presented. When the current price is below the reservation price, the forest owner delays the harvest. An optimal stopping model is used to derive an expression for the optimal sequence of reservation prices under price uncertainty. A solution method using a Monte Carlo backward recursion algorithm is presented. The Monte Carlo simulation procedure may be applied when analytical solutions are difficult or intractable.
In the third essay, a simulation model is used to estimate the per acre value of land devoted to timber production under different harvesting strategies, stumpage price processes, and site qualities. By following the reservation price strategy, forest owners can increase the expected prots from timber harvesting and reduce the variability in profits from timber harvesting relative to a fixed rotation strategy. For an estimated
mean reverting GARCH process, the reservation price strategy increases the value of timberland by 33.0 percent for a site index of 90 and by 22.1 percent for a site index of 60 relative to a fixed rotation strategy.

Included in

Economics Commons

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.