The Risk Reduction Potential of Weather Derivatives in Crop Production:
Simple Indices versus Mixed Indices

Niels Pelka, Oliver Mußhoff

Published: 01.12.2013  〉 Volume 62 (2013), Number 4, 231-243  〉 Resort: Articles 
Submitted: N. A.   〉 Feedback to authors after first review: N. A.   〉 Accepted: N. A.


Weather derivatives are impaired with a basis risk that reduces the risk reduction potential and possibly hinders the introduction of these risk management instruments in the agricultural sector. A frequently suggested approach to reduce the basis risk is the use of mixed indices composed of several weather variables. The present study compares the risk-reduction potential of a temperature index-based and a precipitation index-based weather derivative to a derivative based on a mixed index including the two weather variables temperature and precipitation. This comparison is based on empirical winter wheat yield data of arable farms in Central Germany as well as on daily weather data of individual weather stations over several years. The hedging effectiveness is maximized using the hedging model by Johnson (1960). The results empirically prove that the improvement of the risk reduction potential of weather derivatives based on a mixed index improves significantly in comparison to single-index derivatives. However, it is more advantageous to use several weather derivatives based on a simple index at the same time than using one derivative based on a mixed index if the weather variables of the mixed index were measured at just one weather station. Hence, providers of weather derivatives would do better by offering different weather derivatives based on a simple index than derivatives that are based on a mixed index. In particular this is worth considering with regard to the fact that weather derivatives based on simple indices will surely attract the interest of other sectors more easily. Furthermore, by showing that farm-individual optimally designed weather indices have a significantly higher risk reduction potential than standardized weather indices, this study provides an important progress for the question about the design of weather derivatives. Hence, providers of weather derivative should better offer different weather derivatives with single index-based, farm-individual, optimally designed indices than a derivative based on a mixed index. The focus of the present study may be relevant for farmers as well as for potential providers of weather derivatives.

Georg-August-Universität Göttingen
Fakultät für Agrarwissenschaften,
Department für Agrarökonomie und Rurale Entwicklung,
Arbeitsbereich Landwirtschaftliche Betriebslehre
Platz der Göttinger Sieben 5, 37073 Göttingen
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