Econometrics For Dummies

Chapter 10

Multicollinearity

In This Chapter

Defining multicollinearity and describing its consequences

Discovering multicollinearity issues in your regressions

Fixing multicollinearity problems

Multicollinearity arises when a linear relationship exists between two or more independent variables in a regression model. In practice, you rarely encounter perfect multicollinearity, but high multicollinearity is quite common and can cause substantial problems for your regression analysis. Never fear, though. In this chapter, I help you identify when multicollinearity becomes harmful and the options available to address the problem.

Distinguishing between the Types of Multicollinearity

Two types of multicollinearity exist:

Perfect multicollinearity occurs when two or more independent variables in a regression model exhibit a deterministic (perfectly predictable or containing no randomness) linear relationship. When perfectly collinear variables are included as independent variables, you can’t use the OLS technique to estimate the value of the parameters (βs). Perfect multicollinearity ...