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RE: st: RE: using xtivreg2 for FE
From
DE SOUZA Eric <[email protected]>
To
"[email protected]" <[email protected]>
Subject
RE: st: RE: using xtivreg2 for FE
Date
Mon, 21 Feb 2011 13:37:24 +0100
Your sample is much too small to do anything sophisticated: even -fe robust-
With only seven firms I would introduce dummy variables for the firms and stick to OLS
Then check the residuals for mis-specification
Eric de Souza
College of Europe
Brugge (Bruges), Belgium
http://www.coleurope.eu
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Murod Aliyev
Sent: 21 February 2011 12:15
To: [email protected]
Subject: Re: st: RE: using xtivreg2 for FE
Dear Mark,
Thanks very much for your reply!
Time span is 9 years in average (8-11 years unbalances). Is it too bad? Number fo firms is only 7 (so total N of obs =70).
I tried bw(), bw(2), bw(auto). Results vary, but not to a large extent.
Thanks again!
Murod
----- Original Message ----
From: "Schaffer, Mark E" <[email protected]>
To: [email protected]
Sent: Sun, 20 February, 2011 19:20:54
Subject: st: RE: using xtivreg2 for FE
Murod,
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of
> Murod Aliyev
> Sent: 19 February 2011 14:04
> To: [email protected]
> Subject: st: using xtivreg2 for FE
>
> Dear all,
> I want to estimate a simple FE model, but there may be
> heteroskedasticity and autocorrelation. As far as I
> understand xtreg fe robust gives Huber-White sandwich
> estimator, which deals with heteroskedasticity only.
> Can I use xtivreg2 with fe robust bw() options to get HAC
> (Het. and autocorrelation consistent) standard errors. Of
> course, I will not specify any instruments, as I want only FE
> estimation.
Yes, you can.
Two points worth noting: (a) -xtreg, fe robust- reports cluster-robust
SEs, not heteroskedasticity-robust SEs as you suggest. (b) If you use
-xtivreg2- with the bw() option to get kernel-robust SEs, you are
relying on large-T asymptotics. If your dataset is not very long in the
time-series dimension, the kernel-robust approach will not work very
well.
HTH,
Mark
> Thanks in advance!
> Murod
>
>
>
>
>
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