tarunajwani

Multicollinearity itself is not a problem in a model - in fact, there should be some - and it depends upon the degree of multicolliearity… Remember, the explanatory variables should have some correlation between each other or else it wouldn’t be very useful… But having TOO MUCH is the main problem.
Think about explaining changes in GDP… Of course many factors in the economy have linkage between them, so it’s only when there is a high degree of multicollnearity that there is a problem and should consider dropping variables… Surprisingly the curriculum doesn’t use VIF for this as this what I learned in econometrics and forecasting courses… But oh well .. Hope this helps