Principal operators' farm risk attitudes in hot and cold climates

Purpose: The study investigates whether there is an association between climate types and farm risk attitudes of principal operators. Design/methodology/approach: 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). Findings: 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. Research limitations/implications: 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. Originality/value: 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.