Re: st: RE: Hausman-Taylor and Autocorrelation

[May Ster <mayfrank@gmail.com>]

Apologize for not making my point clear earlier. However, what i meant
was that i have this panel data ;

Panel data set : Panel Variable : Tradepairs (Strongly Balanced)
                        Time Variable  : year, 1970 -2007
                          delta             : 1 year
Initially i did ;

xthtaylor Y X1 X2 X3,...,X9, endo(X3 X4 X7) varying(X1 X2 X3 X4 X5)

After that, i used -xtoverid- , as a result, i obtained Sargan-Hansen
Test = 2.520 with the P= 0.2837
so i considered this sets of instruments are valid.

However, since i suspected Autocorrelations. I then followed
suggestions as discussed by again after estimated ;

xthtaylor Y X1 X2 X3,...X9, endo(X3 X4 X7) varying(X1 X2 X3 X4 X5)

This time, i used -xtoverid, cluster(Tradepairs) noisily-

As a result, i obtained Sargan-Hansen Statistic = 9.898 with P =
0.0195. This is where i'm being confused by.
Since, as i understand, i didn't change the sets of instruments, but
now with cluster option, the P value is lowered ( < 0.05) which
signifies that this sets of instruments are now not valid?

I am not sure whether this could be because i used the command option
-cluster- wrongly.
Please assist.
Thank you very much in advance,

May

On Sun, Mar 20, 2011 at 1:02 AM, Schaffer, Mark E <M.E.Schaffer@hw.ac.uk> wrote:
> 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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