Degree
Doctor of Philosophy (PhD)
Department
School of Renewable Natural Resources
Document Type
Dissertation
Abstract
While the forest grows, the price of timber fluctuates. Price uncertainty plays a key role in forestry due to the extended rotation length of growing trees. Like double sides of the same coin, risk preference and uncertainties should be considered together. This is because risk preference represents people’s attitude toward that uncertainty when making management decisions. Risk preference is especially an important issue for forest management because forests are exposed to substantial uncertainties during their long growing period. However, most existing relevant studies either simply overlook the risk preference issue or fail to consider it together with a practical forest management decision-making approach. In this dissertation study, a behavior-based forest management model was developed to measure forest managers’ risk preferences directly through their potential behaviors toward price changes. Besides, an adaptive harvest decision-making approach that incorporates varying levels of risk preference was established. Based on the models developed in this dissertation, numerical simulations were carried out to evaluate the impact of risk preferences in forest management outcomes. Results of simulations show that risk preference could indeed affect the performance of forest management. Besides, a properly selected risk preference level may bring extra risk premiums to forestry investment. In addition, sensitivity analyses found that there always exists a certain level of risk preference that will lead to the highest average return across different scenarios. Furthermore, a case study using the LSU Lee Memorial Forest as the sample site was carried out to demonstrate the adaptive harvest decision-making process using the method developed in prior chapters. The results of this case study not only confirmed the conclusions reached by numerical simulations, but also reiterated the importance of risk management strategy in forest management under uncertainties.
Date
11-5-2019
Recommended Citation
Zhang, Fan, "Making Decision Adaptive to Price Uncertainty and Risk Preference: A New Decision-Making Model for Forest Management" (2019). LSU Doctoral Dissertations. 5091.
https://repository.lsu.edu/gradschool_dissertations/5091
Committee Chair
Chang, Sun Joseph
DOI
10.31390/gradschool_dissertations.5091