Classifying Agricultural Risk Management Strategies: A Cluster Analysis Approach

This study develops a comprehensive typology of farmers' risk management strategies, simultaneously considering both market-based (e.g. insurance) and on-farm instruments (e.g. high equity ratios). Using Partitioning Around Medoids (PAM) clustering on data collected from 228 German farmers in Saxony during 2022, we identify two distinct farmer types with different approaches to risk management. Our analysis reveals that risk predictability is associated with instrument choice, while resource availability moderates management responses. This relationship manifests in distinct patterns: Large-scale professional farmers develop compre-hensive systems combining formal risk management instruments with infrastructural solutions, particularly for highly predictable risks, reflecting their market exposure and resource capacity. In contrast, small-scale diversified farmers opt for more flexible approaches that allow for adaptation to both predictable and less predictable risks while aligning with their resource constraints. The results have implications for agricultural policy, insurance companies, farmers and advisory services, indicating that effective risk management support should acknowledge the rationality of different approaches and focus on reducing implementation barriers specific to different farm types rather than promoting standardized solutions.