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From |
Sami Alameen <samialameen@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Mon, 19 Sep 2011 21:45:36 +0300 |

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: >>> * 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/ >> > > * > * 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/

**Follow-Ups**:**RE: st: RE: xtscc and small samples (equal size T and N)***From:*"Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>

**References**:**st: xtscc and small samples (equal size T and N)***From:*christina sakali <christina.sakali@googlemail.com>

**st: RE: xtscc and small samples (equal size T and N)***From:*"Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>

**Re: st: RE: xtscc and small samples (equal size T and N)***From:*christina sakali <christina.sakali@googlemail.com>

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