Search

PurposeThe article examines the impact of policy change on enterprise unit subsidies that took place in 2009 on the quantity demanded for crop insurance.Design/methodology/approachThe analysis covers corn, soybeans, and wheat that are grown in six economic regions and uses various measures of purchasing such as acres insured, unit structure, coverage levels, as well as crop hail use as proxies for the quantity demanded.The analysis first employs time series econometric tools to analyze whether the time path of the share of enterprise units within buyup acres is influenced by the policy change in enterprise unit subsidies. It then comparatively examines the insurance experience between 2008 (right before the change) and 2015 (well after the change).FindingsFor corn, soybean, and wheat, the analysis establishes that the time path of the share of enterprise units within buyup coverage acres is statistically and economically influenced by the intervention. The analysis further quantifies the intervention's immediate and long-term impacts and finds that farmers' unit choices are highly responsive (elastic) to subsidy rates in those units.Between 2008 and 2015, the insurance experience generally indicates that the share of enterprise units within buyup coverage surged, the share of acres under catastrophic coverage declined, and the share acres in high coverage levels increased. Meanwhile, growers have increasingly utilized crop-hail policies.Originality/valueThis appears to be the first study (1) quantifying the sensitivity of farmers' unit choices with respect to subsidy rates in those units and finding that such choices are actually highly responsive (elastic), and (2) pointing out the interaction between MPCI and crop-hail products and offering insights as to their combined use. The findings should be of considerable value to policymakers, academics, bankers, and producers in regards to the design and use of risk management tools.

Purpose Regional differences in crop insurance uptake have persisted over time. To partly explain this phenomenon, the purpose of this paper is to propose and evaluate a budget constraint (heuristic) effect within the standard expected utility theory (EUT) framework through simulation methods. Design/methodology/approach Within the EUT framework, a standard simulation model is used to gain insights into farm insurance decisions when a budget constraint is in effect. The budget constraint is modeled as it has been revealed through the data on farmers’ insurance expenditures. In the simulation analysis, certainty equivalent values are used to rank farm options subject to the revealed budget constraint. Findings A budget constraint effect within the EUT framework stands out in explaining the observed regional differences. The proposed explanation is consistent with the historical trends on the ratio of crop insurance expenditure to expected crop value, higher premium rates in regions with lower crop insurance uptake, and the limited turnout for the 2014 Farm Bill’s supplemental area-based crop insurance products. Farmers’ crop insurance choices are found to be mostly constrained-optimal. Originality/value This appears to be the first study taking the revealed preferences approach to farmers’ crop insurance choices in a simulation analysis. Some policy implications are drawn and future research avenues are suggested. The findings should be of considerable value to policymakers, academics, bankers, and producers in regard to the design and use of risk management tools.

Purpose – The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the Agricultural Act of 2014. Design/methodology/approach – The certainty equivalent of wealth is used to rank farm choices and assess the effects of supplemental revenue options on the crop insurance plan and coverage level chosen by the producer under a range of farm attributes. The risk-reducing effectiveness of the select programs is also examined through their impact on the farm revenue distribution. The dependence structure of yield and prices is modeled by applying copula techniques on historical data. Findings – Farm program supplemental revenue programs generally have no effect on crop insurance choices. Crop insurance supplemental revenue programs typically reduce crop insurance coverage at high coverage levels. An individual plan of crop insurance combined with a supplemental revenue insurance plan may substitute for incumbent area crop insurance plans. Originality/value – The analysis provides insights into farmers’ possible choices by focussing on alternative crops and farm attributes and extensive scenarios, using current data, crop insurance plans and programs contained in the 2014 Farm Bill and related bills. The results should be of value to policy officials and producers in regards to the design and use of risk management tools.