We compare three different elicitation methods for measuring risk attitudes of French farmers in a field experiment setting. We consider two experiments based on the lottery choices initially proposed by Holt and Laury (2002) and by Eckel and Grossman (2002,2008), a risk-taking psychological questionnaire and a self-reporting of perceived risk attitudes for different domains. The main empirical results from this within-subject study are the following. First, within the class of lottery choices, risk preference measures are affected by the type of mechanism used. In particular, farmers appear to be more risk averse using the Eckel and Grossman lottery than using the Holt and Laury one. However attitudes towards risk are significantly correlated across lotteries which means that the ranking of risk preferences seems to be preserved. Second, risk preferences appear to be context-dependent. French farmers are highly risk averse for decisions belonging to financial and ethical domains. They report a higher willingness to take risk for professional decisions. Lastly, using the psychological questionnaire, we find that the risk attitude elicited through lottery choices often correlates with risk attitude toward investments. These findings contribute to the literature which addresses the stability of risk preferences across elicitation methods.

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In this paper, we develop a multiple forest use model to determine the optimal harvest date for a forest stand producing both timber and carbon benefits under a risk of fire. The preferences of the representative non-industrial private forest (NIPF) owner are modeled though an expected utility specification. We introduce saving as a decision of the forest owner at any time. The problems of forest management and saving decisions are solved simultaneously using a stochastic dynamic programming method. A numerical programming method is used to characterize the optimal forest and saving policies. We apply this framework to model the behavior of a representative NIPF owner located in the Southwest of France. The empirical application indicates that a higher risk of fire will decrease the optimal rotation period, while higher carbon prices will increase the optimal harvesting age. We show that increasing the risk of fire leads to a reduction in rotation duration. On the contrary, a higher carbon price makes carbon sequestration more profitable, thereby leading to increasing the rotation duration. We then show how the carbon price/risk of fire frontier is affected by risk aversion.

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We propose a stochastic dynamic programming framework to model the management of a multi-stand forest under climate risk (strong wind occurrence). The preferences of the forest-owner are specified by a non-expected utility in order to separately analyze intertemporal substitution and risk aversion effects. A numerical method is developed to characterize the optimal forest management policies and the optimal consumption-saving strategy. The stochastic dynamic programming framework is applied to a non-industrial private forest-owner located in NorthEast of France. We show that the optimal decisions both depend upon risk and time preferences.