Hello Everyone,
I have a panel of data and would like to estimate a Heckman sample
selection model. This can apparently be done with gllamm, though I'm
still struggling a bit with the code and interpretation (and may have
questions on that later).
My current question is whether the following simple alternative could be
availed: 1. estimate the random effects probit part of the model using
xtprobit 2. calculate the inverse Mills ratio from the results, which
equals normden(linear_pred)/norm(linear_pred) 3. Include the Mills as an
explanatory variable in the second stage regression to control for
selectivity bias. In the second stage regression, one would have to
decide between a fixed effects and random effects specification. And I
believe one would also want to use the robust option.
This approach seems simple enough, but I'm hesitant because I've never
seen it done in the literature. Instead, most articles on the panle
Heckman are fairly equation dense, and few of the findings have made
their way into statistical software (with a few exceptions like gllamm).
If anyone has any insights as to whether the suggested alternative is
defensible, please pass them along.
Many thanks,
Colin
Colin Vance, Ph.D.
German Aerospace Center
Institute of Transport Research
Rutherfordstrasse 2
12489 Berlin
Germany
tel: +49 30 67055147
fax: +49 30 67055202
email: [email protected]
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
