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

[Kuba Bembenek <kuba.bembenek1@gmail.com>]

Mark,

just to be sure, you nevertheless expect the -ivreg2/xtivreg2- warning
to appear because of a non-positive semi-definite variance matrix?

2014-04-22 16:09 GMT+02:00 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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>
> -----
> Sunday Times Scottish University of the Year 2011-2013
> Top in the UK for student experience
> Fourth university in the UK and top in Scotland (National Student Survey 2012)
>
>
> We invite research leaders and ambitious early career researchers to
> join us in leading and driving research in key inter-disciplinary themes.
> Please see www.hw.ac.uk/researchleaders for further information and how
> to apply.
>
> Heriot-Watt University is a Scottish charity
> registered under charity number SC000278.
>
>
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