Austin,
Thank you for your suggestions. A follow up question-are you aware of
the existence of Heckman style corrections in the context of duration
models?
Murali
> Murali Kuchibhotla <[email protected]>:
> A better question might be: Is there a way to correct for this in the
> real world? Probably not, in most senses. Think of it as a
> logit/probit regressing "survival" on the k variables in X and a
> training dummy T and the k interactions T*X, so you have at least k+1
> endogenous variables measuring the effects of training. You could
> switch to an -ivprobit- model if you had a large number of
> instruments, but that seems unlikely (plus, I think you would want an
> -ivcloglog- command which does not exist). One way forward is to
> reweight the samples so they look identical on observables, using
> propensity scores, as described in
> http://www.stata-journal.com/article.html?article=st0136 and elsewhere
> (the sample will look identical in the sense that a -hotelling- test
> would fail to reject the null that the mean of X is the same in the
> training group and the non-training group--the distributions may
> differ in other ways). But this corrects only for selection on
> observables, not unobservable differences--for the latter, you need
> training to be randomly assigned, for a start. Or you need a very
> convincing natural experiment.
>
> On Wed, Sep 10, 2008 at 11:22 PM, Murali Kuchibhotla
> <[email protected]> wrote:
> >
> > Hello,
> > I am interested in estimating separate Cox regression models for 2
> > groups of individuals- trainees and non-trainees. The problem is that the
> > training decision is endogenously determined, so that the differences
> > between the 2 sets of parameter estimates may well be driven by the
> > differences in the unobservable characteristics between the 2 groups of
> > respondents. Is there a way to correct for this in Stata?
> >
> > Murali Kuchibhotla
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>
Murali Kuchibhotla
Department of Economics
Iowa State University
Office:75,Heady
Phone:515-294-5452
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