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

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

Christina,

FWIW, I'd be reluctant to follow Sami's advice, for the same reasons I gave earlier, and in spite of my soft spot for recommendations involving -ivreg2-.  Two-way clustering requires asymptotics where both T->infinity and N->infinity.  11 is not very far on the way to infinity no matter how you slice it.

What about a simple 2-way fixed effects model with both group fixed effects and time dummies?  You have 121 observations, and you're losing 22 dofs to the FEs, so it's not tooooo bad....

--Mark 

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> Sami Alameen
> Sent: 19 September 2011 19:46
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: xtscc and small samples (equal size T and N)
> 
> It's up to you but I would use -ivreg2- with two-way 
> clustering as follow:
> 
> ssc install ivreg2, replace
> 
> use grunfeld
> 
> xi, noomit: ivreg2 invest kstock mvalue i.company, noconst 
> cluster(company year)
> 
> And igore the irrelevant segments of the output!
> 
> Sami
> 
> On Mon, Sep 19, 2011 at 8:24 PM, christina sakali 
> <christina.sakali@googlemail.com> wrote:
> > 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.
> >>> *
> >>> *   For searches and help try:
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> >>> *   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.
> >>
> >>
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