Using PC regression for multicollinear model with lagged variable

This paper aims at identifying a most frequently multivariate technique,Principal Components Analysis (PCA), to solve a multicollinear single equation econometric model .results of the method used were compared to Ordinary Least Squares (OLS) and(Two Stages Least Squares (2SLS) to see if satisfactory results can be obtained. The proposed technique was applied to annual time series economic data, mainly total value added in agriculture. The method seemed to have little usefulness in the model; this might be referred to the nature and the number of the explanatory variables under concern. The method seemed to have few applications in economic fields and recommended when the number of explanatory variables included in the model is very large relative to sample size, or when multicollinearity exists.