Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay

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dc.creatorCeballos, Francisco
dc.date2016-12-29
dc.date2024-06-21T09:23:02Z
dc.date2024-06-21T09:23:02Z
dc.date.accessioned2026-06-27T15:06:15Z
dc.descriptionThis paper develops a novel methodology to estimate the degree of spatial basis risk for an arbitrary rainfall index insurance instrument. It relies on a widelyused stochastic rainfall generator, extendedto accommodate nontraditional dependence patterns—in particular spatial upper-tail dependence in rainfall—through a copula function. The methodology is applied to a recentlylaunched index product insuring against excess rainfall in Uruguay. The model is first calibrated using historical daily rainfall data from the national network of weather stations, complemented with a unique,high-resolution dataset from a dense network of 34 automatic weather stations around the study area. The degree of downside spatial basis risk is then estimated by Monte Carlo simulations and the results are linked to both a theoretical model of the demand for index insurance and to farmers’ perceptions about the product.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/147562
dc.identifier.urihttp://hdl.handle.net/123456789/94632
dc.languageen
dc.publisherInternational Food Policy Research Institute
dc.rightsOpen Access
dc.sourceCeballos, Francisco. 2016. Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay. IFPRI Discussion Paper 1595. Washington, DC: International Food Policy Research Institute (IFPRI). https://hdl.handle.net/10568/147562
dc.subjectinsurance
dc.subjectrain
dc.subjectrainfall
dc.subjectprecipitation
dc.subjectspatial analysis
dc.subjectrainfall patterns
dc.subjectweather
dc.subjectrisk
dc.titleEstimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay
dc.typeWorking Paper

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Instituto Internacional de Investigación sobre Políticas Alimentarias (IFPRI)