st: testing heteroksedasticity and autocorrelation fixed effect model

[Jan Lid <hhb010@hotmail.com>]

Hi everybody,

I was wondering if it is a necessary to test for heteroskedasticity and autocorrelation in either a fixed or random effect model? Or can i just ust he cluster (csid) option that will correct in case there is heteroskedasticity and autorcorrelation and won't correct for it in case there isn't. I can´t see to find a good way of testing for thm in a fixed effect model.  

Thx!



----------------------------------------
> From: hhb010@hotmail.com
> To: statalist@hsphsun2.harvard.edu
> Subject: RE: st: fixed effect correcting auto correlation and heteroskedasticity
> Date: Tue, 1 Mar 2011 18:59:35 +0100
>
>
> Total N is ci 1200. Divided in ci 150 groups So large N. T is ci 12 periods if T stands for time (not entirely sure...). My paneldata is unbalanced.
>
> Is the t and N-large enough to use stscc or better to use cluster option?
>
> Thx for the help!
>
> ----------------------------------------
> > Subject: RE: st: fixed effect correcting auto correlation and heteroskedasticity
> > Date: Tue, 1 Mar 2011 12:25:43 -0500
> > From: wooldri1@msu.edu
> > To: statalist@hsphsun2.harvard.edu
> >
> > What are the dimensions of your N and T (roughly?) Many of the routines
> > that claim to correct for serial correlation and/or heteroskedasticity
> > are only guaranteed to work (in the sense of eliminating the problems)
> > when T is fairly large.
> >
> > If N is large and T is not very large, the "cluster" option after FE --
> > or, for that matter, RE -- is attractive. So
> >
> > xtreg y x1 ... xk, fe cluster(csid)
> >
> > where csid is the cross section identifier. The resulting standard
> > errors are completely robust to any kind of serial correlation and/or
> > heteroskedasticity. The other approaches assume parametric forms and,
> > like I said, typically rely on large T approximations.
> >
> > Jeff
> >
> > Jeffrey M. Wooldridge
> > University Distinguished Professor
> > Department of Economics
> > Michigan State University
> > 110 Marshall-Adams Hall
> > East Lansing, MI 48824-1038
> > Phone: 517-353-5972
> > Fax: 517-432-1068
> > http://www.msu.edu/~ec/faculty/wooldridge/wooldridge.html
> >
> > -----Original Message-----
> > From: owner-statalist@hsphsun2.harvard.edu
> > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Jan Lid
> > Sent: Tuesday, March 01, 2011 12:20 PM
> > To: statalist@hsphsun2.harvard.edu
> > Subject: RE: st: fixed effect correcting auto correlation and
> > heteroskedasticity
> >
> > Thx for the reply. The xtscc command works fine! I also tried it with a
> > random effect model since I do have some regressions that prefer re. but
> > that doesn't worl.
> >
> > the command xtscc dependent independents, re however does not work.
> > Unfortunately i still have the same problem that i can correct for
> > heteroskedasticity or autocorrelation. Is there a command that corrects
> > for both in a random effect model?
> > or is xtregar enough? or xtreg, re robust?
> >
> > How does it work in this situation exactly.
> >
> > ----------------------------------------
> > > Date: Tue, 1 Mar 2011 08:52:31 -0800
> > > From: syed.basher@yahoo.com
> > > Subject: Re: st: fixed effect correcting auto correlation and
> > heteroskedasticity
> > > To: statalist@hsphsun2.harvard.edu
> > >
> > > Hi,
> > >
> > > You can consider the user written -xtscc- which corrects for both
> > > autocorrelation and heteroskedasticity. It also permits unbalanced
> > panel and
> > > allows for fixed effects. For further info, see:
> > > http://www.stata-journal.com/article.html?article=st0128
> > >
> > > ---------------------------
> > > Syed Abul Basher
> > > Qatar Central Bank
> > > P.O. Box 1234
> > > Doha, Qatar.
> > > ---------------------------
> > >
> > >
> > >
> > >
> > > ----- Original Message ----
> > > From: Jan Lid
> > > To: statalist@hsphsun2.harvard.edu
> > > Sent: Tue, March 1, 2011 7:44:44 PM
> > > Subject: st: fixed effect correcting auto correlation and
> > heteroskedasticity
> > >
> > >
> > > Dear statalisters,
> > >
> > > I have a question about correcting for autocorrelation and
> > heteroskedasticity in
> > > panel data. I have read many posts but are still very confused. First
> > of all my
> > > hausman test say i have to use fixed effect model so i will use that
> > one
> > >
> > > I can correct my paneldata for autocorrelation using xtregar in stead
> > of xtreg.
> > > This does not correct for heteroskedasticity however.
> > > i can use xtreg ,fe robust. This corrects for heteroskedasticity but
> > not for
> > > autocorrelation.
> > >
> > > Maybe the fixed effect model does already correct for either one or
> > both? Am I
> > > missing the obvious... i can't find a good explanation Is it possible
> > to use a
> > > newey west option somehow e.g?
> > >
> > > I also had a question about unbalanced data set. MY dataset is
> > unbalanced. Do i
> > > need to correct for this?
> > >
> > > Help is very much appreciated.
> > > *
> > > * For searches and help try:
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> > >
> > >
> > >
> > >
> > > *
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