Ambiguity, value of information and forest rotation decision under storm risk

Patrice Loisel, Marielle Brunette () and Stéphane Couture ()
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Marielle Brunette: BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - Université de Haute-Alsace (UHA) - Université de Haute-Alsace (UHA) Mulhouse - Colmar - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Stéphane Couture: MIAT INRAE - Unité de Mathématiques et Informatique Appliquées de Toulouse - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

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Abstract: Storm is a major risk in forestry. However, due to the more or less pessimistic scenarios of future climate change, storm frequency is now ambiguous and only partially known (i.e., scenario ambiguity). Furthermore, within each scenario, the quantification of storm frequency is also ambiguous due to the differences in risk quantification by experts, creating a second level of ambiguity (i.e., frequency ambiguity). In such an ambiguous context, knowledge of the future climate through accurate information about this risk is fundamental and can be of significant value. In this paper, we question how ambiguity and ambiguity aversion affect forest management, in particular, optimal cutting age. Using a classical Faustmann framework of forest rotation decisions, we compare three different situations: risk, scenario ambiguity and frequency ambiguity. We show that in a context of risk or scenario ambiguity, a forest owner characterized by risk aversion and ambiguity aversion reduces the optimal cutting age, whereas in a context of frequency ambiguity the owner does not change it. The optimal cutting age is always reduced when risk aversion increases, whereas an increase in ambiguity aversion never has an impact. The value of information that resolves scenario ambiguity is low and it is almost null for frequency ambiguity.

Keywords: Climate change; Faustmann criterion; Forest management; Natural hazard; Risk aversion; Value of information; Ambiguity aversion (search for similar items in EconPapers)
Date: 2025-12
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Published in Resource and Energy Economics, 2025, 84, pp.101536. ⟨10.1016/j.reseneeco.2025.101536⟩

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Related works:
Journal Article: Ambiguity, value of information and forest rotation decision under storm risk (2025)
Working Paper: Ambiguity, value of information and forest rotation decision under storm risk (2023)
Working Paper: Ambiguity, value of information and forest rotation decision under storm risk (2022)
Working Paper: Ambiguity, value of information and forest rotation decision under storm risk (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05313728

DOI: 10.1016/j.reseneeco.2025.101536

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