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
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
