Improving agricultural microinsurance by applying universal kriging and generalised additive models for interpolation of
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Improving agricultural microinsurance by applying universal kriging and generalised additive models for interpolation of mean daily temperature Mitchell Roznik1 · C. Brock Porth1 · Lysa Porth1 · Milton Boyd1 · Katerina Roznik1 Received: 16 June 2018 / Accepted: 4 February 2019 / Published online: 22 March 2019 © The Author(s) 2019
Abstract Agricultural microinsurance has the potential to protect farmers against crop loss caused by extreme adverse weather conditions. Microinsurance policies for smallholder farmers are often designed on the basis of weather indices, whereby weather insurance variables are measured at ground weather stations and then interpolated to the location of the farm. However, a low density of weather stations causes interpolation error, which contributes to basis risk. The objective of this paper is to investigate whether agricultural microinsurance can be improved by reducing interpolation error through advanced interpolation methods, including universal kriging (UK) and generalised additive models (GAM) used with land surface temperature, elevation, and other covariates. Results indicate that for areas with a lower density of weather stations, UK with elevation substantially improves air temperature interpolation accuracy. The approach developed in this paper may help to improve interpolation and could therefore reduce basis risk for agricultural microinsurance in regions with a low density of weather stations, such as in developing countries. Keywords Weather insurance · Microinsurance · Basis risk · Remote sensing · Universal kriging · Generalised additive models
Introduction Agricultural risk management and insurance are important to the growth of the agricultural sector worldwide because they help producers to stabilise their income and respond to large and unexpected weather risks. A strong agricultural risk management and insurance system in a global context is important for meeting food demand now and in the future and enhancing world food security (FAO 2009). In developing * Mitchell Roznik [email protected] 1
University of Manitoba, Winnipeg, Canada Vol:.(1234567890)
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countries farmers often face poverty and constraints such as a lack of understanding of insurance, unaffordable insurance premiums and inadequate access to credit. Agricultural microinsurance has the potential to reduce poverty and stabilise the income of smallholder farmers. Crop microinsurance tends to use an index-based approach, whereby payouts are based on an easily observable index that is correlated to crop yield outcome. Compared to traditional crop insurance, index-based weather insurance approaches have the potential to address some of the difficulties facing smallholder farmers. For example, index-based weather insurance involves relatively low administration costs, and savings on administration could be passed on to farmers through reduced premiums, resulting in more affordable insurance. However, the problem of basis risk, which refe
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