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Optimizing forest management under dependent price and production risks: a Markov decision process approach

Author

Listed:
  • Marielle Brunette

    (LEF - Laboratoire d'Economie Forestière - INRA - Institut National de la Recherche Agronomique - AgroParisTech)

  • Stéphane Couture

    (UBIA - Unité de Biométrie et Intelligence Artificielle (ancêtre de MIAT) - INRA - Institut National de la Recherche Agronomique)

  • Jacques-Alexandre Laye

    (LEF - Laboratoire d'Economie Forestière - INRA - Institut National de la Recherche Agronomique - AgroParisTech)

Abstract

In the forest sector, natural disturbances have impact on production and prices. Traditionally, these risks have been analysed separately. In our model, the production risk translates into a price risk through a quality loss. We consider that the stock of timber follows a Markov Decision Process (MDP) with the harvesting decision as a control variable. We solve the optimal harvesting problem under storm risk with a risk-averse forest owner and when risk induces triple dependent consequences on production, price and timber quality. We study the impact of the risk distribution, the risk aversion level and the percentage of quality loss on the optimal harvesting decision.

Suggested Citation

  • Marielle Brunette & Stéphane Couture & Jacques-Alexandre Laye, 2012. "Optimizing forest management under dependent price and production risks: a Markov decision process approach," Post-Print hal-01072291, HAL.
    • Handle: RePEc:hal:journl:hal-01072291
    Note: View the original document on HAL open archive server: https://hal.science/hal-01072291
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    References listed on IDEAS

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    1. Peter Lohmander, 2000. "Optimal sequential forestry decisions under risk," Annals of Operations Research, Springer, vol. 95(1), pages 217-228, January.
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