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

 From christina sakali <[email protected]> To [email protected] Subject Re: st: RE: xtscc and small samples (equal size T and N) Date Tue, 20 Sep 2011 17:47:54 +0300

```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

On 20 September 2011 17:15, Schaffer, Mark E <[email protected]> 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: [email protected]
>> [mailto:[email protected]] On Behalf Of
>> christina sakali
>> Sent: 20 September 2011 15:03
>> To: [email protected]
>> 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
>> <[email protected]> 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: [email protected]
>> >> [mailto:[email protected]] On Behalf Of
>> christina
>> >> sakali
>> >> Sent: 20 September 2011 13:17
>> >> To: [email protected]
>> >> 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
>> <[email protected]> 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
>> >> > [email protected]
>> >> >
>> >> > =====================================
>> >> >
>> >> > Date: Tue, 20 Sep 2011 02:12:43 +0300
>> >> > From: christina sakali <[email protected]>
>> >> > 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
>> >> >
>> >> > 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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>> >
>> > --
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>> under charity
>> > number SC000278.
>> >
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>
>
> --
> Heriot-Watt University is a Scottish charity
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>
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