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st: RE: Two -way clustering (ivreg2/xtivreg2/cgmreg): warning messages, uncomprehensible behavior


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Two -way clustering (ivreg2/xtivreg2/cgmreg): warning messages, uncomprehensible behavior
Date   Mon, 21 Apr 2014 22:18:05 +0000

Kuba,

-ivreg2- and -cgmreg- are giving you basically the same message.  This problem can happen with 2-way clustering; I think if you follow up some of the literature on this, you'll find some discussion.

The only thing I can suggest is partialling-out all the regressors you aren't interested in, using the partial(.) option of ivreg2/xtivreg2.  Unless you are using the CUE estimator, this leaves the remaining coefficients unchanged, and often solves the problem.

HTH,
Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
> statalist@hsphsun2.harvard.edu] On Behalf Of Kuba Bembenek
> Sent: 21 April 2014 20:13
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Two -way clustering (ivreg2/xtivreg2/cgmreg): warning messages,
> uncomprehensible behavior
> 
> Dear Statalists,
> 
> what I am doing:
> 
> I am estimating a panel model via First Difference estimator. I either
> use ivreg2 and take the first differences myself, or xtivreg2, fd. The
> panal ist unbalanced and consists of seven sectors across 24 countries
> ( 168 panel units) observed over 33 years. In the model, I include
> seven industry specific trends (after FD: industry specific dummies)
> and year dummies.
> 
> The problem that occurs:
> 
> In this model I want to cluster across industries and countries. I
> almost always get the message "Warning: estimated covariance matrix of
> moment conditions not of full rank.model tests should be interpreted
> with caution." This even the case when the number of clusters exceeds
> the number of regressors to be estimated (in both cluster dimensions).
> Furthermore no singleton dummy variable is included
> 
> 
> Of course due to the number of time dummies etc., the number of
> clusters would not be sufficient in both dimensions if I just used the
> identification variables for countries and industries. To evade this
> problem,  I generate id variables for three year intervals,four year
> intervals, or each individual year to interact them (egen ..
> =group(threeyear country) etc.) with the country and industry
> indicator. The only combination where two-way custering works is the
> industry*year and country*year case. In all the other cases I get the
> error message above. However if I just cluster over one dimension,
> e.g.  fouryearid*industry or threeyear*country, it works. This
> confuses me as to my knowledge the numbers of coefficients that can be
> jointly tested is restrained by the "cluster dimension" with the
> fewest number of clusters.
> 
> Does anybody have an idea what could be happening here? I would be
> very thankful for some help!
> 
> Best Regards
> 
> Kuba Bembenek
> 
> 
> additional info:
> 
> I also tried the cgmreg command  (described here:
> https://www.econstor.eu/dspace/bitstream/10419/58397/1/609322079.pdf)
> and for every estimation, also for the year*country and
> industry*clusters, I get the following message:
> 
> " Raw estimated variance matrix was non-positive semi-definite.
> -cgmreg- is replacing any/all negative eigenvalues with 0"
> *
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