The study investigates whether there is an association between climate types and farm risk attitudes of principal operators.
The study exploits temperature variation in the diverse climate types across the US and defines hot- and cold-climate states. Ordered logit and generalized ordered logit models are used to model principal operators' farm risk attitudes, which are measured on a Likert scale. The study uses two datasets. The first dataset is a 2017 survey of US large commercial producers (LCPs). The second dataset provides a Köppen-Geiger climate classification of the US at a spatial resolution of 5 arcmin for a 25-year period (1986–2010).
The study finds that principal operators in hot-climate states are 4–5% more likely to have a higher willingness to take farm risk compared to principal operators in cold-climate states.
It is likely that farm risk mitigation decisions differ between hot- and cold-climate states. For instance, the authors show that corn acres' enrollment in federal crop insurance and computers' usage for farm business are pursued more intensely in cold-climate states than in hot-climate states. A differentiation of farm risk attitude by hot- and cold-climate states may help agribusiness, the government and economists in their farm product offerings, farm risk management programs and agricultural finance models, respectively.
Based on Köppen-Geiger climate classification, the study introduces hot- and cold-climate concepts to understand the relationship between climate types and principal operators' farm risk attitudes.
The authors would like to thank Jayson Lusk, Terrance Hurley, Todd Kuethe (AFR editor), anonymous reviewers, and participants in the Australian Agricultural and Resource Economics Society 2020 conference for their valuable feedback and comments.
Wahdat, A.Z. and Gunderson, M. (2022), "Principal operators' farm risk attitudes in hot and cold climates", Agricultural Finance Review, Vol. 82 No. 5, pp. 797-814. https://doi.org/10.1108/AFR-06-2021-0087
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