THE CHOICE OF EXOGENOUS FACTORS IN THE REGRESSION MODEL WITH MULTICOLLINEARITY IN THE DATA
The paper considers an approach to the construction of a multiple regression model in terms of multicollinearity data. The types of multicollinearity causes and methods to reduce or eliminate it. This article is devoted to consideration and combining different methods of selection of informative factors for regression analysis. The proposed approach is implemented on the basis of real data of financial reporting industry «Communication». Data source http://www.fira.ru/. In the course of solving this problem is shown in detail the use of test Gloubera Farrar, step by step procedure for the selection factors in the model, the use of the test of choice «short» or «long» regression. The resulting model was tested for multicollinearity using the method of additional regressions (VIF test method or inflation factors). Test results showed that the resulting model contains no collinear factors and can be used for analysis and forecasting.