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

[christina sakali <christina.sakali@googlemail.com>]

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
>> >
>> >
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