Supply and demand response model of agricultural products to the lagged variablesas explanatory variables often cause serious multi-colinearity among those variables.This condition could reduce the efficiency of parameter estimates and then affectedthe effectiveness of the whole model. Own and cross price elasticity of eachparameter estimate computed from this response model will be definitely bias, so thatany projection made from a bias model will not accurate. If policy implication isdrowns 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 tofind better parameter estimates and more accurate projections. One of the mostsuitable techniques is the application of partial adjustment Nerlove model. Thisadjustment model is very popular in the study of supply response. Nevertheless, thisapproach could reduce any bias in the computation of elasticity of parameterestimate of each explanatory variable that will be used in projection. In respect to thisapproach, adjustment model also exercised in the estimation of parameter ofdemand response model.
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