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Depends on the degrees of freedom... See
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help density_functions, mark(t)
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to find out...
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Eva Poen
Gesendet: Mittwoch, 15. April 2009 11:35
An: [email protected]
Betreff: Re: st: p-values seem too low after regress with cluster option
Erasmo,
this depends on the degrees of freedom. With clustering, your df can
be greatly reduced. If, for example, you have 7 degrees of freedom
(i.e. 8 industries), the p-value will be equal to 2*ttail(7,1.78)
which is around 0.118.
Hope this helps,
Eva
2009/4/15 Erasmo Giambona <[email protected]>:
> Dear Statlist,
>
> I am fitting a model to a cross-sectional data set of 304 firms across
> 9 industries. I fit the model using regress with the robust and
> cluster options (which I use to cluster standard errors at the
> industry level). One of the variables obtains a "t" of 1.78 but its
> p-value is "only" 0.114. Shouldn't the p-value be lower than 10% in
> this case?
>
> I really cannot explain this.
>
> I hope somebody could provide an explanation.
>
> Thanks,
>
> Erasmo
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