The best exposition of this is in Arthur Goldberger's textbook of econometrics, where he devotes an entire chapter to this and points out that "multicollinearity" is really just a misnomer for small sample size (or "hyponumerosity," as he calls it.) If you can't get your hands on his text, or don't have time to read the chapter, you can see a much condensed version written by Bryan Caplan at. It is a bogus issue, a statistical zombie that refuses to die. You have already, in writing your post in #1, wasted more of your time worrying about "multicolinearity" than it is worth. More generally, there is no point using VIF at all. There is no point in putting such variables into VIF. That's to be expected, and it isn't a problem. Whenever you have a series of variables that are indicators ("dummies") for the levels of a categorical variable, the VIF is going to be high.
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