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st: Re: Pls help me! question regarding panel fixed effect model
Although Clive's willingness to help early on a Sunday morning is
admirable, some of his advice is a bit off base.
(1) ivreg2 will NOT fit a fixed effect model. Mark Schaffer's
xtivreg2 will do so (and is in fact a 'wrapper' for ivreg2, so will
allow for all of the ivreg2 options).
(2) cluster-robust SEs allow errors to be heteroskedastic and
arbitrarily correlated with one another within clusters (but
independent of those in other clusters). A robust SE treatment allows
unspecified arbitrary heteroskedasticity. Cluster-robust SEs can
appear in a purely cross-sectional context. If you are in a panel
context, you may well want to treat the prospect of non-independently
distributed errors with something like the Newey-West estimator,
which as Clive says would be invoked with bw(2) [which allows for AR
(3) You cannot combine HAC estimation ("Newey-West") with cluster-
robust SEs. Use one or the other. You can combine robust and cluster
(varname) in any Stata command that allows cluster(), but 'robust' is
redundant, as cluster-robust SEs are always robust.
Kit Baum, Boston College Economics and DIW Berlin
An Introduction to Modern Econometrics Using Stata:
On May 20, 2007, at 2:33 AM, Clive wrote:
# If I use cluster option, does it correct for serial correlation and
heteroskedasticity? I need to correct both in my estimation. What does
group correlation mean?
Heteroskedasticity. As for the intra-group correlation, this link may
help to explain:
As for which model you should use, to achieve what you need, why not
use Baum, Schaffer and Stillman's -ivreg2-, downloadable from SSC?
Then you could do something like this:
. ivreg2 y x1 x2 d1 d2 d3, bw(2) robust cluster(group) small
where the d-variables are your time-dummies. This fits an OLS
fixe-effect model with Newey-West standard errors (although using both
the -robust- and -cluster()- options might be overdoing things). I'm
sure Kit, Mark and/or Steve will add further comments on this should
they feel the need.
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