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Re: R: st: intreg with control for sample selection and endogeneity bias
From
"Justina Fischer" <[email protected]>
To
[email protected]
Subject
Re: R: st: intreg with control for sample selection and endogeneity bias
Date
Tue, 30 Oct 2012 00:41:45 +0100
Hi Francesco
obtaining bootstrapped s.e. should be an option of -intreg-.
For the first stage: Practically a good model specification strategy (instrument, exclusion restriction!) with supportive statistical tests should do at least for the first stage.
For the second stage you need to consult an intreg-specialist which I am not....
E.g. I do not know whether the assummption of the joint normality of the error terms still prevails.
HTH
Justina
-------- Original-Nachricht --------
> Datum: Tue, 30 Oct 2012 00:14:08 +0100
> Von: "Francesco Pastore" <[email protected]>
> An: [email protected]
> Betreff: R: st: intreg with control for sample selection and endogeneity bias
> Hi, Justina,
> any more details about bootstrapping and the rest? How would you suggest
> doing it practically.
> Francesco
>
> -----Messaggio originale-----
> Da: [email protected]
> [mailto:[email protected]] Per conto di Justina Fischer
> Inviato: 30 October 2012 00:09
> A: [email protected]
> Oggetto: Re: st: intreg with control for sample selection and endogeneity
> bias
>
> Hi Francesco
>
>
> when pursuing Thierry's suggesion do not forget to get the standard errors
> of the intreg regression right; I think bootstrapping is the easiest.
>
> In general, make sure that the statistical assumptions of both stages are
> met since they are important for identification and consistency.
>
> Justina
>
> -------- Original-Nachricht --------
> > Datum: Mon, 29 Oct 2012 23:12:45 +0100
> > Von: urbain thierry YOGO <[email protected]>
> > An: [email protected]
> > Betreff: Re: st: intreg with control for sample selection and
> > endogeneity bias
>
> > hi
> > i think you can deal with the sample selection as usual : you estimate
> > an equation of labor market participation, you recover the predicted
> > value p and you compute the inverse Mills ratio as follow:
> > gen pdfp1=normalden(p1)
> > gen cdfp1=normprob(p1)
> > gen IMR=pdfp1/cdfp1
> > finally, you insert IMR in the wage equation.
> >
> > 2012/10/29, Francesco Pastore <[email protected]>:
> > > Hi, All,
> > > I would like to ask to the statalist the following question:
> > >
> > > I am estimating a wage equation to see the impact of overeducation
> > > on earnings of a sample of graduates observed 5 years after getting
> > > their degree. The dependent variable is defined as an interval data:
> > > people
> > are
> > > asked to say to which class of earnings does their income belong to,
> > rather
> > > than a precise value. In this case, I should use the intreg command.
> > > One problem is that these types of cross-section estimates are
> > > plagued by sample selection and endogeneity bias. Does anybody know
> > > how to deal with it in the contest of interval regressions? Is there
> > > any routine available in
> > Stata?
> > >
> > > Best regards
> > > Francesco
> > >
> > >
> > >
> > > *
> > > * For searches and help try:
> > > * http://www.stata.com/help.cgi?search
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> > > * http://www.ats.ucla.edu/stat/stata/
> > >
> >
> >
> > --
> > *Urbain Thierry YOGO
> > Ph.D candidate in Economics*
> > *
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>
>
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