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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 13:19:18 +0200

Thanks very much Eva.

Martin, Garry is a person who replied to my post. I think he just replied to me.

Erasmo

On Wed, Apr 15, 2009 at 12:10 PM, Eva Poen <eva.poen@gmail.com> wrote:
> Erasmo,
>
> in this STB article (
> http://www.stata.com/support/faqs/stat/stb13_rogers.pdf ) it says
> that, as long as the largest cluster size is no more than 5% of the
> observations, the variance estimator performs reasonably well (based
> on some experiments). So, one should roughly have at least 20 clusters
> or so. However, I am sure this doesn't hold in all generality.
>
> Maybe you can make a finer distinction of your industries? Like
> sub-industries or something? Also, it's worth looking at the
> literature in your field to see how other people handle this issue.
>
> Eva
>
>
>
>
> 2009/4/15 Erasmo Giambona <e.giambona@gmail.com>:
>> 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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