i'm a complete newbie when it comes to statistically evaluating data for my thesis and would therefore very much appreciate your help.

I have two questions:

1) My regression equation is including a vector of industrial dummy variables as independent variable (meaning three columns with A) SIC 20-39=1, else=0, B) SIC 50-59=1, else=0 and C) SIC 70-89=1, else=0). To avoid the dummy variable trap, I did not consider the dummy variable SIC 20-39 due to multicollinearity.

=> My question therefore is, how one can estimate the estimation coefficient and the t-statistics of the dummy variable SIC 20-39 if it is not included in the (OLS) regression?

2) When making the OLS regression (in SPSS) I also included some multicollinearity statistics, where I saw that two variables have a VIF of 45-50 which is very high and possibly led to the very low adjusted R-Square.

=> My question therefore is, what I can do to lower the VIF without taking out any variables? (I am exactly following the procedure of a well-known paper with my data where the VIFs were very low with the exact same variables).

I would be so grateful if you could help me with those two issues as my thesis deadline is approaching and google doesn't offer any good advice neither .

THANK YOU GUYS SO MUCH IN ADVANCE!

Diana