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Re: st: p-values seem too low after regress with cluster option


From   Erasmo Giambona <e.giambona@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: p-values seem too low after regress with cluster option
Date   Wed, 15 Apr 2009 12:00:35 +0200

Dear Eva and Garry,

Thanks very much for your help. Would that imply by any means that I
should avoid clustering in my case? Naively, it seems like I am
shrinking my sample from 304 to only 9 observations. Hope you can
comment on this.

Regards,

Erasmo


On Wed, Apr 15, 2009 at 11:34 AM, Eva Poen <eva.poen@gmail.com> wrote:
> 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 <e.giambona@gmail.com>:
>> 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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