Re: st: Testing joint significance of fixed effects in presence of heteroskedasticity and auto-correlation

[Christian Wagener <wagener.christian@googlemail.com>]

Thanks a lot for your reply, we really appreciate your help.

Just to be sure, we would be testing the joint significance of fixed
effects in the presence of heteroskedasticity and auto-correlation by
using the following code:

xtreg y x, fe vce(cluster cluster_id)
scalar rss1 = e(rss)
scalar dfr = e(df_r)
scalar dfa = e(df_a)
regress y x, vce(cluster cluster_id)
scalar rss2 = e(rss)
scalar fstat = ((rss2-rss1)/dfa)/(rss1/dfr)
di "Resid SS with dummies " rss1
di "Resid SS without dummies " rss2
di "F statistic with " dfa " and " dfr " d.f. = " fstat

This example is exactly the one from you we quoted in our initial
posting, we just replaced areg with xtreg and robust with vce(cluster
cluster_id) to account for auto-correlation. Would this be a viable
way or are we overlooking something important?

When using vce(cluster cluster_id), we noticed that the rss stay the
same as in the case without vce(cluster cluster_id). Only the df_r
drop down to the number of clusters - 1 and equals the df_a. The same
happens when using areg instead of the xtreg-command.

Is this drop of df_r a problem for the test of fixed-effect
significance we are looking for?

Sorry for our probably rudimentary question - we really appreciate your support!

Thomas and Christian


2010/6/9 Christopher Baum <kit.baum@bc.edu>:
> <>
> On Jun 9, 2010, at 2:33 AM, Christian wrote:
>
>> using  - xtreg y x, fe - we obtain the p-value of the joint
>> significance of firm-specific fixed effects from the common output (F
>> test that all u_i=0).
>>
>> In order to correct for heteroskedasticity and auto-correlation, we
>> would like to use -xtreg y x, fe vce(cluster clusterid) - to receive
>> robust standard errors. The F-test mentioned above is not calculated
>> anymore when this option is applied. Stata help files indicate that
>> "The F test of u_i = 0 is suppressed because it is too difficult to
>> compute the robust form of the statistic when there are more than a
>> few panels." (xt p. 452)
>>
>> Kit Baum proposed a test for the joint significance of fixed effects
>> based on estimates robust to heteroscedasticity, but not
>> autocorrelation (
>> http://www.stata.com/statalist/archive/2005-05/msg00373.html ).
>>
>> Is there any way to test the joint significance of fixed effects in
>> the presence of both heteroscedasticity AND autocorrelation?
>
> The inclusion of -robust- in the quoted example was a red herring. You will get the same results without
> -robust-, and you would get the same results with a HAC estimator in the first part (which you could compute
> with Mark Schaffer's -xtivreg2-). If only residuals are involved in the formula, consistency of the point estimates
> makes this computable without any reference to the VCE.
>
> Kit
>
>
>
> Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
>                              An Introduction to Stata Programming  |   http://www.stata-press.com/books/isp.html
>   An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html
>
>
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