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The predictive power of farmers’ risk attitude measures elicited by experimental methods

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Aim of study: Farmers’ behavior is shaped by their individual attitudes towards risk. Consequently, an understanding of the heterogeneous risk attitudes among farmers is key to predicting their decision-making. Therefore,… Click to show full abstract

Aim of study: Farmers’ behavior is shaped by their individual attitudes towards risk. Consequently, an understanding of the heterogeneous risk attitudes among farmers is key to predicting their decision-making. Therefore, there is a need for reliable methods to assess individuals’ risk attitudes. The main objective of this paper was to contribute to the existing literature about the external validity of risk attitude measures obtained with diverse experimental methods.Area of study: Irrigated agriculture in a Mediterranean climate region.Material and methods: Two different experimental methods widely applied in the agricultural sector were used to elicit farmers’ risk attitudes in a sample of irrigators in southern Spain: the Eckel and Grossman lottery-choice task and a self-assessment general risk question. We evaluated the explanatory power of both measures for the farming risk borne by farmers, using an approach based on dispersion measures of farming returns.Main results: Results revealed stability across these elicitation methods, but the study yielded no evidence of statistical correlation with the farming risk actually borne by farmers, suggesting that it may not be advisable to use these methods for directly predicting farmers’ decision-making in modeling exercises.Research highlights: The most relevant innovation of this paper was the validation approach followed, based on measures assessing the overall level of farming risk borne by individual producers, and the complementary analyses controlling for key variables that could affect farmer risk-taking.

Keywords: risk; experimental methods; attitude measures; risk attitude; farmers risk

Journal Title: Spanish Journal of Agricultural Research
Year Published: 2020

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