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Re: st: fixed effects with robust standard errors
If you want an estimate of the individual fixed effects use areg as
Mark rightly pointed out.
Otherwise if you're only interested in the effects of your independent
variables after controlling for individual FE then you don't need the
adjustment to the DOF if you run your regression on demeaned
In other words transforming the data to deviations from individual
means and then running the regress command doesn't "implicitly
estimates" the FEffects, it just differences them out... making your
estimator consistent. Hence no adjustment in the DOF needed.
Greetings to the AEM crowd,
On 10/25/05, Mark Schaffer <M.E.Schaffer@hw.ac.uk> wrote:
> > I am trying to do what Nick suggested in a posting a few years back (see
> > below), i.e. to estimate a fixed effects model with
> > heteroskedasticity-robust standard errors by transforming the data to
> > deviations from means and then running the regress command, with the
> > option robust specified.
> > However, I believe I need to correct the degrees of freedom for the number
> > of dummy variables this procedure implicitly estimates. Is it possible to
> > do this within the regress command;
> There is an undocumented -dof()- option for -regress- that sets the
> residual degrees of freedom to the number provided, but I don't see why
> you need to do this. Why not just use -areg-?
> > should I (not being an expert
> > programmer in the least) try to program it myself; or is there some other
> > way to change the degrees of freedom used?
> > Thanks very much,
> > Vivian
> >>From "Nick Cox" <email@example.com>
> > To <firstname.lastname@example.org>
> > Subject RE: st: robust st. errors and fixed effects
> > Date Mon, 21 Oct 2002 15:50:47 +0100
> >> > is there a possibility to estimate a fixed effect model,
> >> controlling for
> >> > heteroskedasticity.
> >> > the comad robust and xtreg don`t work togetehr.
> >> > Is there an other way to control for h.?
> >> > thanks for your help
> >> > peter
> >> >
> >> ...
> >> As was suggested in a posting to Statalist earlier today,
> >> you can get
> >> -regress- to estimate a fixed effects model for you, and -regress-
> >> will of course generate robust SEs.
> >> The posting suggested estimating a "least squares dummy variable"
> >> (LSDV) regression, with a dummy for each observational unit
> >> (individual, firm, whatever). This is OK unless you have a lot of
> >> different units, in which case you get more dummy variables
> >> than you
> >> can reasonable handle. A slightly more laborious but also
> >> equivalent
> >> method is to transform the data by putting it into mean-deviation
> >> form, and then estimating on the transformed data.
> > Mark mentioned -areg- in passing in his posting
> > (abbreviated here): this is just to flag its
> > availability given many dummy variables.
> > Nick
> > email@example.com
> > *
> > * For searches and help try:
> > * http://www.stata.com/support/faqs/res/findit.html
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> Prof. Mark Schaffer
> Director, CERT
> Department of Economics
> School of Management & Languages
> Heriot-Watt University, Edinburgh EH14 4AS
> tel +44-131-451-3494 / fax +44-131-451-3294
> email: firstname.lastname@example.org
> web: http://www.sml.hw.ac.uk/ecomes
> This e-mail message is subject to http://www.hw.ac.uk/disclaim.htm
> * For searches and help try:
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