  I should have not send the post to the list, and I apologize. The problem was on my part, and easily solvable. Thanks for your concern, I really appreciate it, and thanks to the list for patience. This is really a great resource and should not be abused :-)
  mihai

Spencer Graves <spencer.graves@pdf.com> wrote:    I can't say without more information.  If the system were saturated 
(i.e., has as many equations as unknowns), you should get the same 
answer from all the different methods.  However, I just tried a 
saturated model in 'systemfit', with the following results:

 > DF2 <- data.frame(y=1:2, x=3:4)
 > lm(y~x, DF2)
Call:
lm(formula = y ~ x, data = DF2)

Coefficients:
(Intercept)            x
          -2            1
 > library(systemfit)
 > systemfit("OLS", list(eqn=y~x), data=DF2)
Error in solve.default(sigma, tol = solvetol) :
 system is computationally singular: reciprocal condition number = 0
 >
   If you'd like more help from this listserve, please supply a simple, 
self-contained example to illustrate your question (as suggested in the 
posting guide! "www.R-project.org/posting-guide.html").

   Hope this helps.
   Spencer Graves

Mihai Nica wrote:
>    I might be sorry for asking this question :-)
> 
>     I have two equations and I tried to estimate 
them individually with "lm" and "gls", and then in a
system (using systemfit)  with "OLS", "WLS" and "SUR".
Quite surprisingly (for myself at least) the results
are identical to the last digit.
> 
>     Could someone (please!) give a hint as to what 
am I doing wrong?
> 
> Thanks,
> 
> mihai
>    
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