Models Based on Positive Mathematical Programming: State of the Art and Further Extensions
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Mathematical programming models have received renewed interest in the area of agricultural
and agri-environmental policy analysis. Their ability to explicitly represent physical constraints
makes them specifically suited for connecting economic and bio-physical aspects of agricultural
systems. Furthermore, they allow for a direct representation of many current agricultural policy
measures related to production activity levels. The introduction of Positive Mathematical Programming (PMP) addressed problems with plausibility of simulated behaviour and lack of
empirical validation of these models. This paper reviews the development of PMP in its various
forms and takes a look at approaches beyond PMP contributing to the quest for empirically
specified programming models.