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Hi,

I'm doing LS regressions with fixed and random effects in EViews 7 and I would like to test my models for multicollinearity. I calculated variance inflation factors, but would also like to calculate the condition index/ condition number for my variables. Is there a way to 'automatically' calculate the condition number for all variables used in an equation? Can anybody help?

Thanks!

You can use the Coefficient Variance Decomposition diagnostic (which is beneath the VIFs).

Thanks for your quick reply Gareth! I have calculated the coefficient variance decomposition table as suggested. As I use much more independent variables in my regressions than in the example I found in the EViews User Guide II I am now not really sure how to interprete my results though.

Can anybody help me to interprete the results of the coefficient variance decomposition table? Maybe somebody can help with a detailed interpretation of the results in a published study (using eviews)?

The coefficient variance decomposition table looks like this:
* 16 out of 17 eigenvalues have condition numbers smaller than 0.001, the smallest condition number is 8.15E-7
* Decomposition proportions: The largest values in column one are 0.73, 0.16 and 0.10 (intercept c has a value of ~1.000- do I have to remove the intercept?)
* The largest values in the other columns reach ~0.9, but I do not observe any 'clusters' of large values (i.e., I do not find a column with more than one value >0.5)
* My panel has 1580 observations (~180 cross sections)
* I use an intercept (c) and a few dummy variables in my regression models

Thanks!

Ralf