On the Systemic Nature of Weather Risk

Systemic weather risk is a major obstacle for the formation of private (nonsubsidized)crop insurance. This paper explores the possibility of spatial diversification of insurance by estimating the joint occurrence of unfavorable weather conditions in different locations.For that purpose copula methods are employed that allow an adequate descriptionof stochastic dependencies between multivariate random variables. The estimation procedureis applied to weather data in Germany. Our results indicate that indemnity paymentsbased on temperature as well as on cumulative rainfall show strong stochastic dependenceeven at a national scale. Thus the possibility to reduce risk exposure by increasing thetrading area of the insurance is limited. Irrespective of their economic implications ourresults pinpoint the necessity of a proper statistical modeling of the dependence structureof multivariate random variables. The usual approach of measuring stochastic dependencewith linear correlation coefficients turned out to be questionable in the context of weatherinsurance as it may overestimate diversification effects considerably.