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

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

Oops.  I meant

> Eicker-Huber-White-robust VCV is biased with small-T large-N

Sorry about that!

--Mark 

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> Schaffer, Mark E
> Sent: 20 September 2011 14:24
> To: statalist@hsphsun2.harvard.edu
> Subject: RE: st: RE: xtscc and small samples (equal size T and N)
> 
> 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
> > > *   http://www.stata.com/support/statalist/faq
> > > *   http://www.ats.ucla.edu/stat/stata/
> > >
> > 
> > *
> > *   For searches and help try:
> > *   http://www.stata.com/help.cgi?search
> > *   http://www.stata.com/support/statalist/faq
> > *   http://www.ats.ucla.edu/stat/stata/
> > 
> 
> 
> --
> Heriot-Watt University is a Scottish charity registered under 
> charity number SC000278.
> 
> 
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
> 


-- 
Heriot-Watt University is a Scottish charity
registered under charity number SC000278.


*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/