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Re: st: RE: Hausman-Taylor and Autocorrelation
From
May Ster <[email protected]>
To
[email protected]
Subject
Re: st: RE: Hausman-Taylor and Autocorrelation
Date
Sat, 19 Mar 2011 19:53:48 +0000
Thank you Jeffrey and Mark so far,
I've followed your suggestion using -xthtaylor- with -xtoverid,
cluster(clustvar) noisily-
However, i have some doubts regarding the results.
I didn't change the sets of instruments from my previous tasks in
which the overidentification test suggests the validity of
instruments.
Nevertheless, after i use -xtoverid, cluster(clustvar) noisily- there
is the Hansen J statistic which giving the P value which is smaller
(Sargan-Hansen = 6.364 with the P value = 0.0415) than when i use
just -xtoverid- after -xthtaylor-.
So , does this imply that the overidentification test I've previously
done with -xtoverid- is no longer appropriate to identify that these
sets of instruments are valid?
Please assist,
May
On Wed, Mar 9, 2011 at 8:00 PM, Wooldridge, Jeffrey <[email protected]> wrote:
>
> Certainly seems easier to me!
>
> Even easier would be to get the Stata folks to allow "cluster" with xthtaylor in future versions.
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On Behalf Of Schaffer, Mark E
> Sent: Wednesday, March 09, 2011 2:27 PM
> To: [email protected]
> Subject: RE: st: RE: Hausman-Taylor and Autocorrelation
>
> Or, to avoid some of the tedium, after estimation by -xthtaylor-,
>
> xtoverid, cluster(clustvar) noisily
>
> will report the cluster-robust SEs for the HT estimation. (Replacing, of course, "clustvar" by the name of the variable on which you are clustering.)
>
> Not all the tedium is avoided, because the variable names reported by -xtoverid- are Stata temporary names, so you'd have to match them to the real names by comparing the output with that of -xthtaylor-, but it probably beats doing HT by hand.
>
> Cheers,
> Mark
>
> > -----Original Message-----
> > From: [email protected]
> > [mailto:[email protected]] On Behalf Of
> > Wooldridge, Jeffrey
> > Sent: 09 March 2011 18:39
> > To: [email protected]
> > Subject: RE: st: RE: Hausman-Taylor and Autocorrelation
> >
> > The transformation used by HT is the same as that used by RE,
> > it's just that the former uses IV. In Stata, RE has a "theta"
> > option so that you can see what fraction of the mean is
> > subtracted off (which is the same for all i with a balanced
> > panel). Unfortunately, it is not an option with HT.
> >
> > You can compute it from the HT output: it depends on
> > sigmasq(u), sigmasq(e), and T. I call it lambda
> > (unfortunately) in both editions of my book. Greene's book
> > and Baltagi's must have it, too. If you get this estimate,
> > you can compute the quasi-demeaned data by hand (tedious) and
> > then use pooled 2SLS. With a "cluster" option the standard
> > errors will be fully robust.
> >
> > Jeff
> >
> > -----Original Message-----
> > From: [email protected]
> > [mailto:[email protected]] On Behalf Of May Ster
> > Sent: Tuesday, March 08, 2011 2:04 PM
> > To: [email protected]
> > Subject: Re: st: RE: Hausman-Taylor and Autocorrelation
> >
> > Thank you JW,
> >
> > I so far haven't managed to get that version of your MIT
> > pressbook yet. I will try to get one asap.
> >
> > However, I am not quite sure what do you mean by firstly
> > "Obtain the quasi-demeaned data using theta (just as with
> > random effects)"
> > Does that mean i shall use ...
> >
> > xtreg y x1 x2 x3, re
> >
> > then what shall then be next steps?.
> >
> > I have to apologise if my question is somewhat not too
> > advanced as i'm very new to STATA.
> > Please help. Thanks.
> >
> >
> >
> >
> > On Mon, Mar 7, 2011 at 11:42 AM, Wooldridge, Jeffrey
> > <[email protected]> wrote:
> > >
> > > Actually, autocorrelation does not cause inconsistency in
> > the betahats.
> > > The Hausman-Taylor estimator is a generalized IV estimator
> > and, like
> > > GLS, it is consistent even if the second moments are
> > misspecified. Of
> > > course, the instruments need to be strictly exogenous.
> > >
> > > The main issue is how to obtain robust standard errors for the
> > > Hausman-Taylor approach. It can be programmed in Stata without too
> > > much trouble, but there is a way to use Stata commands, too. Obtain
> > > the quasi-demeaned data using theta (just as with random
> > effects) and
> > > then use ivreg on the pooled, quasi-demeaned data.
> > Clustering at the
> > > id level then produces valid standard errors.
> > >
> > > I discuss this in 2e of my MIT Press book.
> > >
> > > JW
> > >
> > > -----Original Message-----
> > > From: [email protected]
> > > [mailto:[email protected]] On Behalf Of May Ster
> > > Sent: Sunday, March 06, 2011 8:13 PM
> > > To: [email protected]
> > > Subject: st: Hausman-Taylor and Autocorrelation
> > >
> > > Dear all,
> > >
> > > Under the panel framework,I've used the Hausman-Taylor as an
> > > estimator. However, i can't find the way to check whether there's
> > > autocorrelation in residual after using -xthtaylor-.
> > >
> > >
> > > If i'm not wrong, if autocorrelation is the case here, the
> > estimates
> > > i've obtained so far are not consistent. And, i have to
> > find a way to
> > > tackle that later.
> > >
> > > Please help. Thanks.
> > > *
> > > * 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/
> > >
> > > *
> > > * 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/
> >
> > *
> > * 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/
> >
> > *
> > * 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/
> >
>
>
> --
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> registered under charity number SC000278.
>
>
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