A large variance inflation factor (VIF) on an independent variable indicates a highly collinear relationship to the other variables that should be considered or adjusted for in the structure of the model and selection of independent variables.

What is considered a large VIF?

In general, a VIF above 10 indicates high correlation and is cause for concern. Some authors suggest a more conservative level of 2.5 or above. Sometimes a high VIF is no cause for concern at all. For example, you can get a high VIF by including products or powers from other variables in your regression, like x and x2.

What is a good VIF number?

There are some guidelines we can use to determine whether our VIFs are in an acceptable range. A rule of thumb commonly used in practice is if a VIF is > 10, you have high multicollinearity. In our case, with values around 1, we are in good shape, and can proceed with our regression.