Insurance and forest rotation decisions under storm risk

Patrice Loisel, Marielle Brunette () and Stéphane Couture

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Abstract: Forests are often threatened by storms; and such a threat is likely to increase due to climate change. Indeed, climate change is expected to increase the frequency and intensity of extreme events such as intensive storms. For forest owners, adaptation to climate change will require major adjustments in forest management practices. Then, forest owners will have to take these increasing risks into account through risk-sharing (insurance) and risk-reducing strategies (reduction of rotation length). In this paper, we propose to jointly analyze the forest owner's insurance decision and the rotation age under storm risk. We extend the Faustmann optimal rotation model under risk, first, considering the forest owner's preferences towards risk, and second, integrating the decision of insurance. With this analytical model, we show that unless the forest owner's discount rate and the insurer's discount rate are sufficiently unequal, it is not optimal for the forest owner to adopt insurance. We prove that the rotation length increases as the insurance premium increases, i.e. substitution between the two coverage mechanisms. Finally, we discuss the potential implications of government policy on the insurance scheme.

Keywords: Insurance; Risk-sharing; Storm risk; Rotation length; Subsidy; Faustmann Value; Assurance; Partage des risques; Risque d'orage (search for similar items in EconPapers)
Date: 2018-06-20
Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-02785389v1
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Published in Journées Internationales du Risque, Jun 2018, Niort, France. pp.20

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Related works:
Journal Article: Insurance and Forest Rotation Decisions Under Storm Risk (2020)
Working Paper: Insurance and Forest Rotation Decisions Under Storm Risk (2020)
Working Paper: Insurance and forest rotation decisions under storm risk (2019)
Working Paper: Insurance and forest rotation decisions under storm risk (2019)
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