Participation patterns of the rainfall index insurance for pasture, rangeland and forage programme

Abstract

Using a novel policyholder-level data set, we analyse participants’ choices of 2-month index intervals in the Rainfall Index for Pasture, Rangeland and Forage (RI-PRF) insurance programme. We first provide a conceptual model that illustrates participation patterns of the rainfall index insurance. We then connect these predicted patterns to some empirical evidence from the policyholder-level data set, which is a subset of data provided by the USDA Risk Management Agency for all RI-PRF participants in Nebraska and Kansas during the years 2013–2017. Because the correlations between forage yield and precipitation and the expected premium subsidy vary by month, different degrees of risk aversion may predict distinctively different choices of the 2-month intervals. Using cluster analysis, we group the participants with similar allocation patterns across the 2-month intervals. We observe that the number of participants displaying relatively low levels of risk aversion increase over time. We connect this to the fact that premium subsidies and producer returns associated with non-growing season (risk-increasing) months are often greater than those for growing season (risk-reducing) months, and this has important implications for policy design. Our findings suggest that more research in this area could assist policymakers in keeping the RI-PRF programme in line with its objective of reducing risk for livestock producers.

Action needed for the EU Common Agricultural Policy to address sustainability challenges

“…Climate change also enhances sanitary hazards (through pests and pathogens) and phytosanitary hazards (through plant pathogens; Altizer, Ostfeld, Johnson, Kutz, & Harvell, 2013; Velásquez, Castroverde, & He, 2018). However, without requiring proper risk mitigation measures, insurance may promote risk‐prone behaviour, that is, disregarding avoidable risks (Goodrich, Yu, & Vandeveer, 2020; Müller, Johnson, & Kreuer, 2017). • Lack of consistency and transparency .…”

Nudge to insure: Can informational nudges change enrollment decisions in pasture, rangeland, and forage rainfall index insurance?

“…A recent review of PRF determined that the product is actuarially sound (Coble et al, 2020). However, among producers who do enroll in PRF insurance, there is a tendency to insure 2‐month intervals that do not have a significant impact on forage growth in addition to, or instead of, those 2‐month intervals that would impact forage growth (Goodrich et al, 2020). This strategy increases a participant's basis risk, that is, not receiving an indemnity when losses occur, in direct contrast with the program's goal of risk reduction.…”

An innovative tool for cost control under fragmented scenarios: The container freight index microinsurance

“…Such fragmented insurance scenarios emphasize affordable or inclusive insurance and the interests of insurance policyholders. In contrast, traditional index insurance is basically designed for risk management from the perspective of insurers ( Goodrich et al, 2020 , Assa and Wang, 2021 ), which may have adverse effects on potential policyholders, such as high premiums, low leverage and harsh underwriting conditions, and hence filter out the consumers who have actual needs.…”

“…If the index information is not transparent and publicly accessible, it can be easily manipulated. When index insurance is based on an opaque index, the moral hazard will be very large ( Goodrich et al, 2020 ). To ensure higher risk transfer efficiency and lower replication cost, the compilation of the index should aim at capturing the true trajectory of the target and reducing the underlying basis risk ( Li et al, 2021 ).…”