Optimizing forest management under storm risk with Markov decision process model

Marielle Brunette (), Stéphane Couture and Jacques-Alexandre Laye
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Jacques-Alexandre Laye: LEF - Laboratoire d'Economie Forestière - INRA - Institut National de la Recherche Agronomique - AgroParisTech

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Abstract: Windstorms generate windfalls that may lead to price decreases. Studies often focus on stochastic growth and price, but consider that there is no link between these two risks. In our model, we assume that storms generate windfalls and that these windfalls have an impact on timber price through volume and quality. The objective of this paper is to analyze the impact of these two effects on harvesting behavior. We consider that the dynamic of the timber stock follows a Markov Decision Process (MDP) and that the harvesting decision is a control variable. We solve the optimal harvesting problem under storm risk with a risk-averse forest owner and when the storm has an impact on production and price. We study the impact of a change in the storm risk distribution, the percentage of quality loss and risk aversion on the optimal harvesting decision. We show that the greater the storm risk is, the greater the harvesting will be. In addition, we observe no noticeable effect of an increase in the percentage of quality loss on harvesting. Moreover, when the forest owner's risk aversion increases, the harvesting is reduced. Finally, we discuss our results, in particular, in relation to climate change.

Keywords: markov decision process; storm risk (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

Published in Journal of Environmental Economics and Policy, 2014, à paraitre (2), ⟨10.1080/21606544.2014.982712⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01203830

DOI: 10.1080/21606544.2014.982712

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