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The impact of farm-level variables on federal crop insurance coverage selections

Author

Listed:
  • Mark Boyd
  • Eric Belasco

Abstract

Purpose - This paper examines the relationship between farm-level variables related to cash flow and premium rates on federal crop insurance coverage selection. Design/methodology/approach - Using farm-level data from the Agricultural Resource Management Survey (ARMS), the authors estimate a linear fixed effects model to evaluate the relationship between farm-level and regional variables and federal crop insurance coverage selections. Findings - The authors find evidence indicating that expected cash flow plays an important role in coverage level decisions. For example, variables directly related to cash flow, such as higher costs, are associated with significant differences in coverage level selection, though the direction of the association is dependent on the type of costs, whether fixed or variable, while higher revenue higher acreage farms insure at higher coverage levels. In addition, higher premium costs are associated with lower coverage level selections, despite subsidy incentives. Originality/value - This is the first paper that identifies a potential solution to the puzzling finding that farmers do not consistently maximize coverage level. This research points to the influence of credit constraints as playing a role in limiting coverage level selections.

Suggested Citation

  • Mark Boyd & Eric Belasco, 2022. "The impact of farm-level variables on federal crop insurance coverage selections," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 83(1), pages 21-42, March.
  • Handle: RePEc:eme:afrpps:afr-09-2021-0123
    DOI: 10.1108/AFR-09-2021-0123
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