RE: st: RE: Hausman-Taylor and Autocorrelation

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

May,

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of May Ster
> Sent: 19 March 2011 19:54
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: Hausman-Taylor and Autocorrelation
> 
> 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?

You need to tell us more about the equations you are estimating.  Are you saying that you estimated the *same* equation but now obtained a different overid statistic?  That shouldn't be possible.  If the equations weren't the same, how were they different?

--Mark

> Please assist,
> 
> May
> 
> 
> 
> On Wed, Mar 9, 2011 at 8:00 PM, Wooldridge, Jeffrey 
> <wooldri1@msu.edu> 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: owner-statalist@hsphsun2.harvard.edu 
> > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> Schaffer, 
> > Mark E
> > Sent: Wednesday, March 09, 2011 2:27 PM
> > To: statalist@hsphsun2.harvard.edu
> > 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: 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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