Modelling farm production risk with copulae instead of correlations
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The optimisation of production plans is an important topic in agriculture, often related to diversification
and specialisation as the classical instruments of coping with production risk. Although
the measurement of embedded risk is often inaccurate, it is nevertheless necessary for decision
making to describe the common behaviour of different variables in a model. Imprecisely
defined relationships influence the “right” choice, why it is important to find a good approximation
of the real circumstances. In financial science, copula functions are frequently used instead
of correlation coefficients to model joint price behaviour, because of the possibility to link the
marginal distributions on multifarious ways. By now, agricultural science makes less use of this
method. This research uses the concept of “partly nested Archimedean copula” to model the
relationship between different crop yields and compares it with a correlation based approach.
The analysis focuses the differences of the approaches in the context of production planning
and the use of weather derivatives.