Dealing with multicollinearity

The modeler still wasn't sure that the model was robust enough. He remembered that he hadn't tested the model for any effects of multicollinearity. We spoke briefly about this phenomenon when we studied the correlation of stock prices with each of the eight independent variables proposed for the regression model. The multicollinearity test was run using the tolerance and the variance inflation factor (VIF).

The PROC REG code for multicollinearity is as follows:

PROC REG DATA=build plots(only label)=(RStudentByLeverage CooksD); 
ID date; 
MODEL stock = basket_index -- m1_money_supply_index/tol vif; 
RUN;

Figure 2.18: Partial output for multicollinearity

The tolerance is computed as 1-R². When the R² is high, the tolerance value is very low. Such low values of tolerance are indicative of multicollinearity. The VIF is derived by taking the...