Seb,
you can always create an r^2 measure from the squared correlation of
actual and predicted observations used in the estimation. So something
like
reg y...
heckman y...
predict double heckp if e(sample), xb
corr heckp y
di r(rho)^2
which should be comparable to the r^2 displayed from the regress.
Kit Baum | Boston College Economics and DIW Berlin | http://ideas.repec.org/e/pba1.html
An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html
An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html
On Sep 24, 2009, at 12:50 PM, seb nieto wrote:
Dear Kit,
I am running a regression in which one of the explanatory variables
could have a "selection bias".
The basic equation is
reg y x1 x2 x3 x4 (equation 1)
However x2 has a selection bias problem that can affect the result
of equation 1
I then run the following regression:
heckman y x1 x3 x4, select(x2 = Z1) twostep mills(lambda)
(equation 2)
in which Z1 are a set of explanatory variables (some of them
different than x1, x3 and x4).
I would like however compare the R2 of the equation (1) with respect
to equation (2). Can I then run the following regression and report
the results of equation (3) instead of those of equation (2)?:
reg y x1 x3 x4 lambda (equation 3)
Of course, lambda variable of eqaution 3 is estimated from equation 2.
Thank you very much for your help.
*
* 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/
