<![CDATA[Supply and demand response model of agricultural products to the lagged variables as explanatory variables often cause serious multi-colinearity among those variables. This condition could reduce the efficiency of parameter estimates and then affected the effectiveness of the whole model. Own and cross price elasticity of each parameter estimate computed from this response model will be definitely bias, so that any projection made from a bias model will not accurate. If policy implication is drowns from this response model then one will find this may not be useful. Therefore, any researcher that interested in this subject should find other technique in order to find better parameter estimates and more accurate projections. One of the most suitable techniques is the application of partial adjustment Nerlove model. This adjustment model is very popular in the study of supply response. Nevertheless, this approach could reduce any bias in the computation of elasticity of parameter estimate of each explanatory variable that will be used in projection. In respect to this approach, adjustment model also exercised in the estimation of parameter of demand response model]]>
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