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RE: st: RE: Hausman-Taylor and Autocorrelation


From   "Schaffer, Mark E" <[email protected]>
To   <[email protected]>
Subject   RE: st: RE: Hausman-Taylor and Autocorrelation
Date   Sun, 20 Mar 2011 23:03:52 -0000

May,

90 isn't very small.  And taken at face value, the cluster-robust overid stat suggests that you have inconsistent estimates.

But the term you're using for your panel units, "tradepairs", suggests that the cluster-robust structure may not be appropriate.  Are these bilateral pairs of trading partners?  Say you have 3 trading partners, A, B and C.  Then you have 3 possible trading pairs, AB, AC and BC.  The cluster-robust structure implies that there is no correlation between, e.g., the errors for AB and AC.  Is that reasonable, given that partner A is trading in both?

Maybe some others on the list have suggestions about how to deal with data that take this structure.

--Mark

> -----Original Message-----
> From: [email protected] 
> [mailto:[email protected]] On Behalf Of May Ster
> Sent: 20 March 2011 21:44
> To: [email protected]
> Subject: Re: st: RE: Hausman-Taylor and Autocorrelation
> 
> Thank you.
> 
> I have additional informations. Hopefully, there are solutions.
> 
> I have 90 Tradepairs (Panel Variables) in this setting. So, 
> in this case, Can i plausibly use the non-robust overid 
> statistic to suggest the estimates are still consistent? yet 
> lack efficiency?.
> 
> Or, i can't conclude anything at this stage.
> 
> If 90 Tradepairs are small and you've suggested HT is unrealiable.
> Does this simply mean the model is misspecified?
> If possible could you privide other optional solutions?. I am 
> very new to econometrics and STATA.
> 
> Actually, my next plan is to estimate this same equation  
> however enlarging the Panel to be 380. Hopefully the 
> robust-overid statistic is reliable then.
> 
> Please assist.
> Thanks.
> 
> 
> On Sun, Mar 20, 2011 at 9:20 PM, Schaffer, Mark E 
> <[email protected]> wrote:
> > May,
> >
> > In other words, the standard non-robust overid statistic is 
> small, suggesting you shouldn't reject the null of valid 
> instruments, but the cluster-robust overid statistic is 
> large, suggesting you should reject the null.
> >
> > This is a little unusual but possible.  Usually it's the 
> other way around, i.e., we usually expect non-robust test 
> stats to be misleadingly small compared to the 
> heteroskedasticity or cluster-robust versions.
> >
> > One caveat - if you have only a small number of clusters, 
> the cluster-robust test stats can be unreliable.  For that 
> matter, if clusters are panel units, and you have only a 
> small number of panel units, HT will be unreliable as well.
> >
> > --Mark
> >
> >> -----Original Message-----
> >> From: [email protected]
> >> [mailto:[email protected]] On Behalf Of May Ster
> >> Sent: 20 March 2011 20:57
> >> To: [email protected]
> >> Subject: Re: st: RE: Hausman-Taylor and Autocorrelation
> >>
> >> 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 
> >> <[email protected]> wrote:
> >> > May,
> >> >
> >> >> -----Original Message-----
> >> >> From: [email protected]
> >> >> [mailto:[email protected]] On Behalf Of May 
> >> >> Ster
> >> >> Sent: 19 March 2011 19:54
> >> >> To: [email protected]
> >> >> 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 
> >> >> <[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
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> >> >> > > > *   http://www.ats.ucla.edu/stat/stata/
> >> >> > > >
> >> >> > > > *
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> >> >> > > *
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> >> >> > >
> >> >> >
> >> >> >
> >> >> > --
> >> >> > Heriot-Watt University is a Scottish charity registered
> >> >> under charity
> >> >> > number SC000278.
> >> >> >
> >> >> >
> >> >> > *
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> >> >
> >> >
> >> > --
> >> > Heriot-Watt University is a Scottish charity registered
> >> under charity
> >> > number SC000278.
> >> >
> >> >
> >> > *
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> >>
> >
> >
> > --
> > Heriot-Watt University is a Scottish charity registered 
> under charity 
> > number SC000278.
> >
> >
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> 


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