[R] Random effects model with PLM: "System is computationally singular"-Error?

[tahaus]

Dear readers,

I am currently trying to estimate some panel data models in R using PLM
package. This includes the estimation of basic pooled, fixed effects and
random effects models. Therefore I make use of this code:
Now here's the problem:



Now here's the problem: I can without any problem estimate all models except
for the random effects model. After entering the "random"-formula, R
produces the following error:



First guesses:
- linear combinations in x? 
A first guess would be that there are exact linear dependencies of the
exogenous variables in x. The data is balance sheet data and I would like to
explain the standard deviation (y) of a specific balance sheet position  by
other balance sheet positions (or the ratio of the position and the balance
sheet sum). Of course, the variables in x are related to each other. For
example some of the ratios are calculated by dividing by the mean which is
also a separate independant variable. And the dependant variable, which is
the standard deviation, is also calculated by using this mean. But again:
There should be no EXACT correlation. But: If I exclude some of my exogenous
variables, the problem disappears, but I have to include them actually.
- problems with unbalanced panel data or NAs?
The data is unbalanced and there are NAs. Fixed effects output says: n=16,
T=18-40, N=455. Probably the unbalanced data or the NAs are the reason for
the error?

Traceback-Code:



Is there anybody who can give me a hint what this error does actually mean
and especially: how to solve the problem? How do I have to correct the code
in order to get results?

Thanks a lot!
Thomas



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