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RE: st: RE: xtscc and small samples (equal size T and N)


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: RE: xtscc and small samples (equal size T and N)
Date   Tue, 20 Sep 2011 15:55:27 +0100

Christina,

-xtivreg2- will do this.  Or, since you have a small number of T and N fixed effects, you could add the FEs by hand.

--Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> christina sakali
> Sent: 20 September 2011 15:48
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: xtscc and small samples (equal size T and N)
> 
> Mark,
> 
> thank you, this is clear now.
> 
> In the older versions of Stata,  het-robust SE were produced 
> with either - xtreg ..., fe robust- OR -xtreg ..., fe 
> vce(robust)- which both gived identical results.
> 
> However, as far as I know these commands have changed in the 
> newer versions. Is it possible to obtain the standard 
> het-robust SE in the newer versions and how?
> 
> 
> 
> On 20 September 2011 17:15, Schaffer, Mark E 
> <M.E.Schaffer@hw.ac.uk> wrote:
> > Christina,
> >
> > The factor in front of bias term in eqn 5 is 1/(T-1).  As T 
> gets bigger, this term gets smaller.  For T=11, the bias term 
> is being multiplied by 1/10, i.e., by 0.1.
> >
> > -xtivreg2-, like -ivreg2-, can estimate straight OLS as 
> well as IV.  The underlying logic is GMM.  OLS, IV, FE, RE, 
> etc., are all GMM estimators.
> >
> > --Mark
> >
> >> -----Original Message-----
> >> From: owner-statalist@hsphsun2.harvard.edu
> >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> christina 
> >> sakali
> >> Sent: 20 September 2011 15:03
> >> To: statalist@hsphsun2.harvard.edu
> >> Subject: Re: st: RE: xtscc and small samples (equal size T and N)
> >>
> >> Mark, this is very useful information.
> >>
> >> Can you please clarify what exactly you mean by "the bias is 
> >> decreasing in T". To me this sounds like the bias is 
> decreasing when 
> >> T is decreasing, but then you say that T=11 may be large enough to 
> >> justify using the standard het-robust VCV, so I am not sure I 
> >> completely get what you mean.
> >>
> >> Also, xtivreg works with instrumental variables, will I be able to 
> >> implement it with my data?
> >>
> >> On 20 September 2011 16:23, Schaffer, Mark E 
> <M.E.Schaffer@hw.ac.uk> 
> >> wrote:
> >> > Christina,
> >> >
> >> > With respect to your last point, you might actually be OK here.
> >> >
> >> > Stock & Watson show that the standard
> >> Eicker-Huber-White-robust VCV is biased with small-N 
> large-T panels.  
> >> But if you check the paper (eqn 5), you'll see that the 
> bias term has 
> >> a 1/(T-1) in front of it.  In other words, the bias is 
> decreasing in 
> >> T.  In your case, T=11 may be enough for you to justify using the 
> >> standard het-robust VCV.
> >> >
> >> > There is an as-yet undocumented option in -xtivreg2-, sw,
> >> that implements the Stock-Watson correction to the standard 
> >> het-robust VCV.  (It's still not documented because I haven't yet 
> >> verified it against a published output or another
> >> package.)  If the sw option gives you SEs that are similar to the 
> >> standard het-robust SEs, you've got grounds to believe that T is 
> >> indeed large enough to justify using the latter.
> >> >
> >> > HTH,
> >> > Mark
> >> >
> >> > NB: If anyone can point me to an example of Stock-Watson
> >> SEs that I can try to replicate, I'd be most grateful.
> >> >
> >> > References:
> >> >
> >> > Stock & Watson (2008),
> >> > http://www.princeton.edu/~mwatson/papers/ecta6489.pdf
> >> >
> >> >> -----Original Message-----
> >> >> From: owner-statalist@hsphsun2.harvard.edu
> >> >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
> >> christina
> >> >> sakali
> >> >> Sent: 20 September 2011 13:17
> >> >> To: statalist@hsphsun2.harvard.edu
> >> >> Subject: Re: st: RE: xtscc and small samples (equal 
> size T and N)
> >> >>
> >> >> Dear Gordon, thanks for the response.
> >> >>
> >> >> From your as well as Mark's suggestions, I get the idea
> >> that perhaps
> >> >> the simple two way fixed effects model is the most
> >> appropriate choice
> >> >> for my data, although I do understand than none of the 
> options is 
> >> >> ideal with such a small panel sample.
> >> >>
> >> >> In other, previous papers with similar sample sizes and
> >> topic, I have
> >> >> seen that they usually either go for a simple one or 
> two way fixed 
> >> >> effects model or rely on simple robust SE such as White
> >> SE. However I
> >> >> am aware that Stock and Watson
> >> >> (2008) showed that these are inconsistent, so this 
> option is also 
> >> >> ruled out for my data..
> >> >>
> >> >> On 20 September 2011 13:29, Gordon Hughes
> >> <G.A.Hughes@ed.ac.uk> wrote:
> >> >> > You will probably get almost as many views about what
> >> constitutes
> >> >> > large T and/or large N as the number of people you 
> consult.  The 
> >> >> > answer is very dependent upon the type of data which you are 
> >> >> > analysing, because panel data comes in many different
> >> >> forms.  However,
> >> >> > as Mark says, no one would believe that 11 gets close.
> >> >> >
> >> >> > For -xtscc- you are dealing with large T asymptotics, so
> >> >> the reference
> >> >> > point would be time series asymptotics.  If you have
> >> annual data I
> >> >> > doubt whether anyone would rely on large T results for T
> >> >> much below 30
> >> >> > and some might be much stricter.  The problem, of course,
> >> >> is that many
> >> >> > panel datasets don't meet that criterion, in which case
> >> you have to
> >> >> > start to think carefully about what you are trying to
> >> >> estimate.  That
> >> >> > is the point which underlies Mark's original 
> suggestion.  Your 
> >> >> > response indicates that you may be trying to get too much
> >> >> out of some rather noisy - or complex - data.
> >> >> >
> >> >> > Gordon Hughes
> >> >> > g.a.hughes@ed.ac.uk
> >> >> >
> >> >> > =====================================
> >> >> >
> >> >> > Date: Tue, 20 Sep 2011 02:12:43 +0300
> >> >> > From: christina sakali <christina.sakali@googlemail.com>
> >> >> > Subject: Re: st: RE: xtscc and small samples (equal 
> size T and 
> >> >> > N)
> >> >> >
> >> >> > Dear Mark, thanks a lot for the advice and recommendations.
> >> >> >
> >> >> > I am a bit reluctant to go for just the simple 2-way
> >> fixed effects
> >> >> > model, since after implementing the necessary tests, I have
> >> >> found that
> >> >> > my residuals suffer from both heteroscedasticity and
> >> >> cross-sectional
> >> >> > dependence, so I am looking for an estimator to account
> >> for both of
> >> >> > these problems.
> >> >> >
> >> >> > Does the inclusion of time fixed effects correct for 
> >> >> > heteroscedasticity and/or cross-sectional dependence and
> >> >> how exactly
> >> >> > is this achieved? (or can you suggest some reference where
> >> >> I can find
> >> >> > some more information on this issue).
> >> >> >
> >> >> > Can you also please clarify this for me: What is the
> >> >> minimum (more or
> >> >> > less) sample size required for the use of estimators
> >> that rely on
> >> >> > large T and N asymptotics?
> >> >> >
> >> >> > Thank you again.
> >> >> >
> >> >> > Christina
> >> >> >
> >> >> >
> >> >> > *
> >> >> > *   For searches and help try:
> >> >> > *   http://www.stata.com/help.cgi?search
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> >> >> >
> >> >>
> >> >> *
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> >> >>
> >> >
> >> >
> >> > --
> >> > Heriot-Watt University is a Scottish charity registered
> >> under charity
> >> > number SC000278.
> >> >
> >> >
> >> > *
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> >>
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> >
> >
> > --
> > Heriot-Watt University is a Scottish charity registered 
> under charity 
> > number SC000278.
> >
> >
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registered under charity number SC000278.


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