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Abstract
The state-contingent approach to production uncertainty presents a more general
model than the conventional stochastic production approach. Here we investigate
whether the state-contingent approach offers a tractable framework for representing
climatic uncertainty at a farm level. We developed a discrete stochastic programming
(DSP) model of a representative wheat–sheep (mixed) farm in the Central West of
NSW. More explicit recognition of climatic states, and associated state-contingent
responses, led to optimal farm plans that were more profitable on average and less
prone to the effects of variations in climate than comparable farm plans based on the
expected value framework. The solutions from the DSP model also appeared to more
closely resemble farm land use than the equivalent expected value model using the
same data. We conclude that there are benefits of adopting a state-contingent view of
uncertainty, giving support to its more widespread application to other problems.