RE: st: RE: Hausman-Taylor and Autocorrelation

["Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>]

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: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> Wooldridge, Jeffrey
> Sent: 09 March 2011 18:39
> To: statalist@hsphsun2.harvard.edu
> 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: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of May Ster
> Sent: Tuesday, March 08, 2011 2:04 PM
> To: statalist@hsphsun2.harvard.edu
> 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 
> <wooldri1@msu.edu> 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: owner-statalist@hsphsun2.harvard.edu
> > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of May Ster
> > Sent: Sunday, March 06, 2011 8:13 PM
> > To: statalist@hsphsun2.harvard.edu
> > 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.
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