st: R squared of OLS with dummy variables

[Stefano Lugo <stefano.lugo@mail.polimi.it>]

I am estimating an OLS model which include dummy variables along with 
other regressors.
If - instead of dropping one dummy due to collinearity - I drop the 
constant, I get the same estimation for variables (including the 
dummy/constant) coefficients and standard errors as expected but a very 
different R squared of the model.

Computing the R squared myself with
reg y  x_a x_b d_1 d_2 d_3, nocons
predict fit if e(sample)
corr y x
di r(rho)^2

I get instead the same R squared showed by Stata when dropping the dummy 
instead of the constant.
To check whether the problem is somehow in my data, I've tried to repeat 
the same thing with simulated data and got the same problem. I have also 
tried using an other software and it reports instead the same R squared 
for both specifications.

Is that a Stata bug or am I missing some theoretical explanation for this?

Thank you for your help

--
Stefano Lugo, PhD
Politecnico di Milano
P.za Leonardo da Vinci 32
20133 Milan, Italy

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/