A Monte Carlo Methodology for Solving the Optimal Timber Harvest Problem with Stochastic Timber and Carbon Prices

Autor/innen

  • Stanislav Petrasek The University of Washington, USA
  • John Perez-Garcia The University of Washington, USA

Schlagwörter:

Optimal Harvest, Carbon Sequestration, American Option, Monte Carlo

Abstract

This article presents a Monte Carlo methodology for solving the
  stochastic optimal timber harvest problem modeled as a recurrent
  American call option. A detailed description of the proposed method-
  ology is given, and the Monte Carlo technique is contrasted with finite
  difference methods typically used to find solutions of the optimal har-
  vest problem with stochastic prices. The use of the methodology is
  then demonstrated via an example. In the example, expected bare
  land values and optimal harvest policies are calculated for a Douglas-
  fir stand in western Washington State. It is assumed that the forest
  owner derives revenue from traditional timber sales and carbon seques-
  tration, and that prices of timber and carbon follow a known stochastic
  process. Results of the calculations are discussed.  MCFNS 2(2):67-77.

Autor/innen-Biografien

  • Stanislav Petrasek, The University of Washington, USA
    graduate student, School of Forest Resources
  • John Perez-Garcia, The University of Washington, USA
    School of Forest Resources
    Professor/Vice Faculty Chair
    Trade analysis and modeling of forest sector

Veröffentlicht

2010-08-28

Ausgabe

Rubrik

Operations Research and Decision Support Systems

Zitationsvorschlag

A Monte Carlo Methodology for Solving the Optimal Timber Harvest Problem with Stochastic Timber and Carbon Prices. (2010). Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 2(2), Pages: 67-77 (11). https://mcfns.com/index.php/Journal/article/view/2.13

Ähnliche Artikel

1-10 von 38

Sie können auch eine erweiterte Ähnlichkeitssuche starten für diesen Artikel nutzen.