Unn'ersiw,-rf Bonn, Insnrute for Agicultural Policy,

Nlathematical prograrnming models have received renewed interest in the area of agricultural and asri-environmental polict ' an:rl)'sis. Theit abiliry to explicidv represent physical constraints mzrkes them specificaily suited for connecting economic and bio-physical aspects of agricultural systems. Furthermore, they allou'for a direct representation of manv current agricultural policv measures related to production activiw levels. The introduction oi Positive X{athematical Pro-eramming (PX'IP) addressed problems rvith plausibiLity of simulated behaviour and lack of enipirical validation of these models. This paper reviews the development of PMP in its vari-ous forms and takes a look at approaches beyond PN{P contributing to the quesr for empiri-calli ' specified programming models. 1. Inttoduction During the 1960's.lrd 70's, aggregate Linear programming models were en vogue in agriculturai economics. Large scale systems, dis-aggregated by region and farm ry'pes, covering regional ttansPort floivs or including recursive-dynamic fearures were der.eloped both in the US and Europe. However, iew of the svstems urre kept alive, and, gradually, nerv model wpes like multi-commodirv- models, computable general equilibrium models and dualiw base