Using Ridge Regression & Generalized Maximum Entropy for the Aanalysis of the Environmental Pollution of Kirkuk Cement Factory

This paper specifies econometric model for environmental pollution such as solid waste and gas emissions of Kirkuk cement factory for the period (1984-2006) the variables used in the production process, which is electric power, black oil, clay and limestone. We used ridge regression and Generalized Maximum Entropy(GME) to solve the multicollinearity problem,because this problem is appeared between the variables of the model. The multicollinearity diagnostic is done by variance inflation factor,condition index and variance proportions. From the analysis, we obtained the GME as the best estimation with respect to standard error of the parameters and logic. The limestone has the largest influence in solid pollution and the black oil and electric power are the variables which affects gas emissions. The (SAS.9) is used in the statistical analysis.