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

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

Dear Mark, thanks for the response.

The first two specifications differ only in respect to one explanatory
variable, while the third specification includes both these two
variables from the previous two specifications.

After estimating them with xtreg ..., fe, I checked for serial and
cross-sectional correlation (using -xtregar, ... fe lbi- and xtcsd).
The results indicated NO serial correlation, but the presence of
cross-sectional dependence.

Moreover, I read in Hoechle (SJ, 2007, p.17) that the Driscoll-Kraay
SE have better small sample properties than other more commonly
employed estimators when cross-sectional dependence is present, that
is why I chose to estimate my model with xtscc.

If both xtscc and cluster are not appropriate for a small sample like
mine, then  what is the appropriate estimator, when one needs to
account for the presence of cross-sectional dependence? Or should I
just use -xtreg, ... fe robust-, which only accounts for
heteroscedasticity?

Any suggestions are greatly appreciated.

On 19 September 2011 19:38, Schaffer, Mark E <M.E.Schaffer@hw.ac.uk> wrote:
> Christina,
>
> You don't tell us how the 3 specifications differ.  It's hard to offer
> explanations for the differences in results without this information.
>
> That said, it looks like you have a basic problem here.
>
> The cluster-robust approach gives you SEs that are robust to arbitrary
> within-group autocorrelation.  It relies on asymptotics in which the
> number of clusters N goes off to infinity.  11 is not very far on the
> way to infinity.
>
> The Driscoll-Kraay SEs implemented by -xtscc- apply the kernel-robust
> approach (e.g., Newey-West) to panel data.  It gives you SEs that are
> robust to arbitrary common (across-groups) autocorrelated disturbances.
> This approach relies on asymptotics in which the number of observations
> in the T dimension goes off to infinity.  11 is not very far on the way
> to infinity.
>
> Personally, I'd be reluctant to use either of these approaches with an
> N=11/T=11 panel.  Maybe others on the list can offer some suggestions
> for alternatives.
>
> Sorry to sound so negative, but that's how it looks from here.
>
> --Mark
>
>> -----Original Message-----
>> From: owner-statalist@hsphsun2.harvard.edu
>> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
>> christina sakali
>> Sent: 19 September 2011 12:44
>> To: statalist
>> Subject: st: xtscc and small samples (equal size T and N)
>>
>> Hello all,
>>
>> I am estimating 3 different specifications of a panel fixed
>> effects model with T=N=11. According to Pesaran's test I have
>> found the presence of contemporaneous correlation in all 3
>> specifications.
>>
>> I then tried to estimate all 3 specs with both -xtscc ...,
>> fe- and -xtreg ..., fe cluster(panelvar) -
>>
>> When comparing the S.E. produced by the two estimators, I was
>> surprised to notice the following:
>>
>> Although in the first spec, xtscc S.E. were ALL larger than
>> cluster S.E., in the other two specs xtscc S.E. were either
>> larger or smaller than cluster S.E. However the difference
>> was rather small.
>>
>> What does this indicate for my data and model (when xtscc
>> produces both smaller and larger S.E. than cluster in the
>> same specification) and which of the two estimates (xtscc or
>> cluster) should I trust as more appropriate for my model?
>>
>> I am using Stata 9.2.
>>
>> Any help or suggestions are appreciated.
>> *
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>
>
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