One option might to use -xtdata- to convert your panel data into a
form where you could use -heckman- directly. If you use the -fe-
option to obtain a fixed effects conversion you are essentially
getting a time demeaning of the data vis a vis the individuals. As the
manual points out, -xtdata- makes no adjustment for the appropriate
standard errors but if you're mainly interested in specification
searchers at the outset, this might be a way to get started.
--
Kind regards,
Ian
-------------------------------
Ian Watson
Senior Researcher
acirrt, University of Sydney
NSW, 2006, Australia
phone: 02 9351 5622
email:[email protected]
www.acirrt.com
-------------------------------
You wrote:
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
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