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

["Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>]

Kuba,

I can't help with -cgmreg-, I'm afraid; that's not something I've written or know much about.

--Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
> statalist@hsphsun2.harvard.edu] On Behalf Of Kuba Bembenek
> Sent: 22 April 2014 14:28
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: Two -way clustering (ivreg2/xtivreg2/cgmreg): warning
> messages, uncomprehensible behavior
> 
> Hi Mark,
> 
> thank you for your answer! I have to correct myself: cgmreg gives me
> this message for every regression, no matter if cluster by one or two
> dimensions. What is your opinion on this?
> 
> Best regards,
> 
> Kuba
> 
> 2014-04-22 0:18 GMT+02:00 Schaffer, Mark E <M.E.Schaffer@hw.ac.uk>:
> > 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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> >
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----- 
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We invite research leaders and ambitious early career researchers to 
join us in leading and driving research in key inter-disciplinary themes. 
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to apply.

Heriot-Watt University is a Scottish charity
registered under charity number SC000278.


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