Analysing Consequences of Increasing Acreage of Colza in Namdan Plain of Fars Province: An Application of Positive Mathematical Programming

Because of the fact that alternative agricultural policies cannot be examined in a laboratory, the potential effects of policies must be analyzed before policy setting, and during or after the policy implementation using mathematical programming (MP) models. In this context, the consequences of increasing the acreage of colza at representative farm (RF) level of Namdan plain were analyzed using positive mathematical programming (PMP), which were improved to overcome normative character of optimization models. The main aim of PMP is to give as true a picture as possible of the situation and then simulate the behavior of farmers as parameters in which the object of agricultural policy intervention is shifted. Based on the results of this study, reduction in the acreage of wheat and bean and increase in the expected profit of RFs are the consequences of increasing acreage of colza. But, as variance of profit increases, the net impact of policy on the expected utility of RFs is not perfectly known. The results also indicated that the use of pesticide increases through introducing colza into a cropping pattern. The effect of policy on water use is different among RFs and they can't take this policy as a water demand management policy.