An analysis of risk management tools utilized by Illinois farmers

Purpose – The purpose of this paper is to investigate the relationships among choice of risk management tools, perceived effectiveness of risk management tools, self-reported risk attitude, and farm and farmer characteristics. Design/methodology/approach – A mail survey was used to collect information about utilization of risk management tools, perceived effectiveness of risk management tools, and factors that could influence choice of risk management tools by Illinois farmers. Cluster analysis, one-way ANOVA, χ 2 tests of independence, and multinomial logistic regression were utilized to detect possible relationships among choice of risk management tools, perceived effectiveness of risk management tools, self-reported risk attitude, and farm and farmer characteristics. Findings – Multinomial logistic regression analysis revealed that age and gross farm income (GFI) were the strongest predictors of the risk management tool utilization group to which an individual would be assigned. The number of risk management tools utilized decreased with age but increased with GFI. Neither self-reported risk attitude nor education was a significant independent variable in the multinomial logistic regression model, but both were strongly impacted by age. Younger farmers with higher GFI were the most likely users of hedging. Research limitations/implications – The results of this study provide support for the idea that farmers who are better able to generate revenue are better able to manage risk, but the direction of causality was not investigated. Practical implications – Risk management service providers could benefit from this study as a benchmark for understanding their current and potential farmer clients’ risk management strategies. Originality/value – This study used cluster analysis and multinomial logistic regression to address the complexity of decisions regarding multiple risk management tools. The number of tools utilized by individuals was investigated.