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From |
Kit Baum <baum@bc.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Re: xtreg fe cluster and Ftest |

Date |
Sat, 26 Apr 2008 06:35:54 -0400 |

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.

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.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

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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