st: Re: xtreg fe cluster and Ftest

[Kit Baum <baum@bc.edu>]

But as Jeff Wooldridge's undergraduate econometrics book  
"Introductory Econometrics" (now in 4th edition) points out, in many  
circumstances, F-tests can be 'robustified', or made robust to  
arbitrary heteroskedasticity. The one we're talking about here is  
just a test on an OLS model with a bunch of dummy variables. Although  
xtreg, fe will not give you an F-statistic for joint significance of  
those variables when robust (actually cluster()) is specified (and  
now will -areg- with robust), you can always compute it for a  
standard -robust- estimator if the number of dummies is not too large.


> webuse grunfeld, clear
> qui tab company, gen(C)
> qui reg invest mvalue kstock C1-C9, robust
> // this should be the 'robustified' F-test
> testparm C1-C9
> // for comparison: here is the non-robust F test
> xtreg invest mvalue kstock, fe
Note this will not work if you use cluster(company), which is  
actually the kind of VCE that xtreg, fe robust is employing. But the  
only difference between robust and cluster(company) is that the  
latter allows for arbitrary correlation between errors within each  
cluster.

Kit Baum, Boston College Economics and DIW Berlin
http://ideas.repec.org/e/pba1.html
An Introduction to Modern Econometrics Using Stata:
http://www.stata-press.com/books/imeus.html


On Apr 26, 2008, at 02:33 , Stas wrote:

> F-tests are ratios of variances. When you start talking about
> - -robust-, it means you do not think there is a common variance
> anymore, so Stata does not provide neither the variances themselves
> nor their ratios. A perfectly sensible answer.
>
> You can follow up through the mechanics of the F-test, but what you
> will get in the end is a random variable with unknown distribution...
> probably a ratio of two complicated quadratic forms in normal
> variables, neither of which has a chi-square distribution, to begin
> with.
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