On the Systemic Natureof Weather Risk

Systemic weather risk is a major obstacle for the formation of private (non-subsidized) crop insurance. This paper explores the possibility of spatial diversication ofinsurance by estimating the joint occurrence of unfavorable weather conditions in dierentlocations. For that purpose copula methods are employed that allow an adequate descrip-tion of stochastic dependencies between multivariate random variables. The estimationprocedure is applied to weather data in Germany. Our results indicate that indemnitypayments based on temperature as well as on cumulative rainfall show strong stochasticdependence even at a national scale. Thus the possibility to reduce risk exposure byincreasing the trading area of the insurance is limited. Irrespective of their economicimplications our results pinpoint the necessity of a proper statistical modeling of the de-pendence structure of multivariate random variables. The usual approach of measuringstochastic dependence with linear correlation coefficients turned out to be questionable inthe context of weather insurance as it may overestimate diversication eects considerably.