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Published on: September 19, 2012
A discrete choice experiment exploring farmer preferences for insurance against extreme weather events
Edel Doherty1, Sinead Mellett2, Daniel Norton3
1National University of Ireland, Galway, J.E. Cairnes School of Business and Economics, Ireland.
Abstract:
Agriculture represents one of the most vulnerable sectors to extreme weather events that are projected to increase with climate change. Insurance has been advocated as a more efficient means to ensure financial security to farmers, than post-disaster aid for damages. A potential drawback of insurance however, is that unless carefully designed it could dis-incentivise farmers to engage in wider farm adaptation measures or lead to more risk-taking behaviour. This paper analyses the attractiveness of publicly-backed climate risk insurance offerings to farmers and explores their preferences for elements of insurance schemes that do not negatively affect incentives for wider farm adaptation. Specifically, a discrete choice experiment is used to reveal Irish farmers' preferences for multi-annual insurance contracts and weather-indexed versus traditional indemnity insurance and cost. Results indicate that a majority of farmers are willing to buy publicly-backed insurance for protection from extreme weather events. Younger farmers, farmers who currently have farm insurance, farmers from certain geographical locations and farmers who have been previously affected by extreme weather events are more likely to buy insurance. With respect to the design of insurance schemes, farmers prefer multi-annual coverage versus annual renewal. They also prefer indexed-insurance and have a strong preference for cheaper coverage. Despite the important role that insurance could play in protecting farms financially from damage caused by extreme weather events, few studies have examined preference for weather-indexed insurance within a European context. New evidence on farmer preferences and intended behaviours is therefore critical to inform policy in this area.
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