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RE: st: fixed effect correcting auto correlation and heteroskedasticity
From
"Wooldridge, Jeffrey" <[email protected]>
To
<[email protected]>
Subject
RE: st: fixed effect correcting auto correlation and heteroskedasticity
Date
Tue, 1 Mar 2011 12:25:43 -0500
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: [email protected]
[mailto:[email protected]] On Behalf Of Jan Lid
Sent: Tuesday, March 01, 2011 12:20 PM
To: [email protected]
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: [email protected]
> Subject: Re: st: fixed effect correcting auto correlation and
heteroskedasticity
> To: [email protected]
>
> 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: [email protected]
> 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.
> *
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>
>
>
>
> *
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