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Thinning and harvesting in stochastic forest models

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  • Helmes, Kurt L.
  • Stockbridge, Richard H.

Abstract

This paper analyzes a stochastic forest growth model in which the manager is able to first thin the forest to promote better growth before harvesting. Both Wicksell single thinning and harvesting cycle and Faustmann on-going rotation problems are considered. The Wicksell problem is analyzed by first restricting the class of decision times to (thinning, harvesting) pairs that bound the growth away from infinity and imbedding the problem in an infinite-dimensional linear program on a space of triplets of measures. These measures capture the thinning and harvesting decisions along with the behavior of the growth process prior to harvest. An auxiliary linear program then leads to a nonlinear optimization problem for which an optimal value and solution are determined. The values of all the problems are be related through a set of inequalities. The solution of the nonlinear problem determines (random) thinning and harvesting times for the single thinning and harvesting cycle which demonstrate the equality of the values of these various problems. Finally for the Wicksell problem, the unrestricted class of thinning and harvest times is shown to give the same value as the restricted class. The Faustmann on-going thinning and harvesting rotation problem is reduced to a Wicksell problem which then allows for the characterization of the value as the solution to a different nonlinear optimization problem. The effects of the opportunity to thin the forest are illustrated on a mean-reverting stochastic model.

Suggested Citation

  • Helmes, Kurt L. & Stockbridge, Richard H., 2011. "Thinning and harvesting in stochastic forest models," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 25-39, January.
    • Handle: RePEc:eee:dyncon:v:35:y:2011:i:1:p:25-39
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    References listed on IDEAS

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    Cited by:

    1. Tahvonen, Olli & Suominen, Antti & Malo, Pekka & Viitasaari, Lauri & Parkatti, Vesa-Pekka, 2022. "Optimizing high-dimensional stochastic forestry via reinforcement learning," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
    2. Alvarez E., Luis H.R. & Hening, Alexandru, 2022. "Optimal sustainable harvesting of populations in random environments," Stochastic Processes and their Applications, Elsevier, vol. 150(C), pages 678-698.

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