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RE: st: RE: ivreg versus xtivreg


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: RE: ivreg versus xtivreg
Date   Fri, 12 Feb 2010 16:53:56 -0000

Thanks, John.  2-way clustering is terra nova, and I am interested in general about how it works in practice.  It sounds like your application is very suitable.

Cheers,
Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> John Antonakis
> Sent: Friday, February 12, 2010 4:04 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: ivreg versus xtivreg
> 
> Hi Mark:
> 
> The SEs are quite similar (and still significant) using two-way 
> clustering as compared to the robust or clustering on one 
> dimension. The 
> first dimension has 192 clusters and the second dimension has 99 
> clusters (and observations are n =433).
> 
> Regards,
> John.
> 
> ____________________________________________________
> 
> Prof. John Antonakis, Associate Dean 
> Faculty of Business and Economics
> Department of Organizational Behavior
> University of Lausanne
> Internef #618
> CH-1015 Lausanne-Dorigny
> Switzerland
> 
> Tel ++41 (0)21 692-3438
> Fax ++41 (0)21 692-3305
> 
> Faculty page:
> http://www.hec.unil.ch/people/jantonakis
> 
> Personal page:
> http://www.hec.unil.ch/jantonakis
> ____________________________________________________
> 
> 
> 
> On 12.02.2010 14:26, Schaffer, Mark E wrote:
> > John,
> >
> >   
> >> -----Original Message-----
> >> From: owner-statalist@hsphsun2.harvard.edu 
> >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> >> John Antonakis
> >> Sent: Friday, February 12, 2010 12:03 PM
> >> To: statalist@hsphsun2.harvard.edu
> >> Subject: Re: st: RE: ivreg versus xtivreg
> >>
> >> Hi Mark:
> >>
> >> Yes; I am using the 2-way cluster option. Fyi, the highest 
> n-size for 
> >> the cluster is 192.
> >>     
> >
> > I take it that means you've got 192 clusters in one 
> dimension.  Do you have a similarly large number in the 
> second dimension?  In that case I agree, you're probably OK.
> >
> > I'm also curious about the results of using 2-way 
> clustering.  Does it make a big difference?
> >
> > --Mark
> >
> >   
> >> Glad to hear that the SEs are probably OK.
> >>
> >> Best regards,
> >> John.
> >>
> >> ____________________________________________________
> >>
> >> Prof. John Antonakis, Associate Dean 
> >> Faculty of Business and Economics
> >> Department of Organizational Behavior
> >> University of Lausanne
> >> Internef #618
> >> CH-1015 Lausanne-Dorigny
> >> Switzerland
> >>
> >> Tel ++41 (0)21 692-3438
> >> Fax ++41 (0)21 692-3305
> >>
> >> Faculty page:
> >> http://www.hec.unil.ch/people/jantonakis
> >>
> >> Personal page:
> >> http://www.hec.unil.ch/jantonakis
> >> ____________________________________________________
> >>
> >>
> >>
> >> On 12.02.2010 12:50, Schaffer, Mark E wrote:
> >>     
> >>> John,
> >>>
> >>>   
> >>>       
> >>>> -----Original Message-----
> >>>> From: owner-statalist@hsphsun2.harvard.edu 
> >>>> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> >>>> John Antonakis
> >>>> Sent: Friday, February 12, 2010 9:23 AM
> >>>> To: statalist@hsphsun2.harvard.edu
> >>>> Subject: Re: st: RE: ivreg versus xtivreg
> >>>>
> >>>> Hi Mark:
> >>>>
> >>>> I have a similar error; however, the message I get is:
> >>>>
> >>>> Warning: estimated covariance matrix of moment conditions not 
> >>>> of full rank.
> >>>>          overidentification statistic not reported, and
> >>>>          standard errors and model tests should be 
> >>>> interpreted with caution.
> >>>> Possible causes:
> >>>>          number of clusters insufficient to calculate robust 
> >>>> covariance 
> >>>> matrix
> >>>>          singleton dummy variable (dummy with one 1 and N-1 
> >>>> 0s or vice 
> >>>> versa)
> >>>> partial option may address problem.
> >>>>
> >>>> Note, I have modeled two dimensions of clustering
> >>>>     
> >>>>         
> >>> Do you mean you're using the new 2-way cluster option?
> >>>
> >>>   
> >>>       
> >>>> (and put all my 
> >>>> fixed-effects in the partial option).  Thus, I am correct in 
> >>>> saying that 
> >>>> the z test for a particular coefficient estimate is still 
> >>>> interpretable.
> >>>>     
> >>>>         
> >>> Probably.  I can think of some special cases where things 
> >>>       
> >> can go wrong (these are what motivated the writing of the 
> >> warning message).  You might have a small number of clusters 
> >> (so the asymptotics are dodgy) or a singleton dummy which 
> >> would mean you couldn't do a test on the significance of the 
> >> coefficient (of course, you couldn't do that anyway).  But 
> >> most likely the SEs are OK.
> >>     
> >>> --Mark
> >>>
> >>>   
> >>>       
> >>>> Best,
> >>>> J.
> >>>>
> >>>> ____________________________________________________
> >>>>
> >>>> Prof. John Antonakis, Associate Dean
> >>>> Faculty of Business and Economics
> >>>> Department of Organizational Behavior
> >>>> University of Lausanne
> >>>> Internef #618
> >>>> CH-1015 Lausanne-Dorigny
> >>>> Switzerland
> >>>>
> >>>> Tel ++41 (0)21 692-3438
> >>>> Fax ++41 (0)21 692-3305
> >>>>
> >>>> Faculty page:
> >>>> http://www.hec.unil.ch/people/jantonakis
> >>>>
> >>>> Personal page:
> >>>> http://www.hec.unil.ch/jantonakis
> >>>> ____________________________________________________
> >>>>
> >>>>
> >>>>
> >>>> On 12.02.2010 09:55, Schaffer, Mark E wrote:
> >>>>  > Sara,
> >>>>  >
> >>>>  >> -----Original Message-----
> >>>>  >> From: owner-statalist@hsphsun2.harvard.edu
> >>>>  >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
> >>>>  >> sara borelli
> >>>>  >> Sent: 12 February 2010 07:58
> >>>>  >> To: statalist@hsphsun2.harvard.edu
> >>>>  >> Cc: Schaffer, Mark E
> >>>>  >> Subject: R: st: RE: ivreg versus xtivreg
> >>>>  >>
> >>>>  >> Hi Mark,
> >>>>  >> I am sorry I did not understand your answer...and I think it
> >>>>  >> is because I I made a typo in writing the command and I did
> >>>>  >> not explain myself clearly. I do NOT include  i.county  in
> >>>>  >> xtivreg2. So I reformulate my question:
> >>>>  >>
> >>>>  >> xtivreg2  CRit  (Xit=Wit)  Zit   (state by year 
> fixed effects),
> >>>>  >> fe i(county), cluster(county)
> >>>>  >>
> >>>>  >> gives the error message " estimated covariance matrix of
> >>>>  >> moment conditions not of full rank; overidentification
> >>>>  >> statistic not reported, and standard errors and  model tests
> >>>>  >> should be interpreted with caution. Possible causes: 
> >>>>  >> singleton dummy variable (dummy with one 1 and N-1 0s or vice
> >>>>  >> versa) fwl option may address problem"
> >>>>  >>
> >>>>  >> but the same command xtivreg2 without state by year effects:
> >>>>  >> xtivreg2  CRit  (Xit=Wit)  Zit, fe i(county), cluster(county)
> >>>>  >>  does NOT report the above error message
> >>>>  >>
> >>>>  >> I do not uderstand why the inclusion of state by year fe
> >>>>  >> caused that error message
> >>>>  >
> >>>>  > I think your explanation in your earlier email is 
> >>>>         
> >> probably right:
> >>     
> >>>>  >
> >>>>  >> I noticed that 2 states have a number of counties 
> >>>>         
> >> (clusters) lower
> >>     
> >>>>  >> than the number of years available. By dropping these two 
> >>>> states STATA
> >>>>  >> run the xtivreg2 without giving the error message.
> >>>>  >>
> >>>>  >> I have read the help file and FAQ and I think something 
> >>>> is going with
> >>>>  >> those state by year effects that creates a kind of 
> >>>>         
> >> singleton dummy
> >>     
> >>>>  >> problem, but I am not sure Any help would be appreciated
> >>>>  >
> >>>>  > And the question is, should you worry about it?  The VCV 
> >>>> should still 
> >>>> be OK for tests of, say, one parameter at a time.  So long 
> >>>>         
> >> as you are 
> >>     
> >>>> aren't trying to do something that requires a full-rank VCV 
> >>>> (like 2-step 
> >>>> GMM, or using an overid stat, or joint testing of all 
> the coeffs), 
> >>>> you're OK, I think.
> >>>>  >
> >>>>  > Memo to self: calling this an "error" in the output 
> is possibly 
> >>>> overstating the issue; maybe "warning" is better.
> >>>>  >
> >>>>  > --Mark
> >>>>  >
> >>>>  >> thank you
> >>>>  >> sara
> >>>>  >>
> >>>>  >>
> >>>>  >>
> >>>>  >> --- Gio 11/2/10, Schaffer, Mark E <M.E.Schaffer@hw.ac.uk> 
> >>>> ha scritto:
> >>>>  >>
> >>>>  >>> Da: Schaffer, Mark E <M.E.Schaffer@hw.ac.uk>
> >>>>  >>> Oggetto: st: RE: ivreg versus xtivreg
> >>>>  >>> A: statalist@hsphsun2.harvard.edu
> >>>>  >>> Data: Giovedì 11 febbraio 2010, 19:43
> >>>>  >>> Sara,
> >>>>  >>>
> >>>>  >>>> -----Original Message-----
> >>>>  >>>> From: owner-statalist@hsphsun2.harvard.edu
> >>>>  >>>> [mailto:owner-statalist@hsphsun2.harvard.edu]
> >>>>  >>> On Behalf Of
> >>>>  >>>> sara borelli
> >>>>  >>>> Sent: Thursday, February 11, 2010 6:32 PM
> >>>>  >>>> To: statalist@hsphsun2.harvard.edu
> >>>>  >>>> Subject: st: ivreg versus xtivreg
> >>>>  >>>>
> >>>>  >>>> Dear members,
> >>>>  >>>> I am running the following regressions in STATA8.2:
> >>>>  >>>> CRit =  a*Xit +  b*Zit  + (state by
> >>>>  >>> year fixed effects)  +
> >>>>  >>>> (county fixed effects), cluster(county)
> >>>>  >>>>
> >>>>  >>>> CRit= crime rate in county i year t
> >>>>  >>>> Xit = endogenous regressor
> >>>>  >>>> Zit = set of 7 exogenous regressors
> >>>>  >>>> state by year fixed effects = interactions between
> >>>>  >>> indicators
> >>>>  >>>> for each state and year
> >>>>  >>>>
> >>>>  >>>> I instrument Xit using Wit
> >>>>  >>>> There are 246 counties, 10 states, 8 years I have been
> >>>>  >> running this
> >>>>  >>>> model with two commands
> >>>>  >>>>
> >>>>  >>>> xi:   ivreg  CRit
> >>>>  >>> (Xit=Wit)  Zit   (state by year fixed
> >>>>  >>>> effects)  i.county, cluster(county)
> >>>>  >>>> xtivreg2  CRit  (Xit=Wit)
> >>>>  >>> Zit   (state by year fixed
> >>>>  >>>> effects)  i.county, fe i.(county)
> >>>>  >>> cluster(county)
> >>>>  >>>> the two commands give exactly the same coefficient,
> >>>>  >>> and just
> >>>>  >>>> slightly different std errors, but after xtivreg2 I
> >>>>  >>> get the
> >>>>  >>>> following message:
> >>>>  >>>> Error: estimated covariance matrix of moment
> >>>>  >>> conditions not
> >>>>  >>>> of full rank;
> >>>>  >>>> overidentification statistic not reported, and
> >>>>  >>> standard
> >>>>  >>>> errors and       model tests
> >>>>  >>> should be interpreted with
> >>>>  >>>> caution. Possible causes:  singleton dummy
> >>>>  >>> variable (dummy
> >>>>  >>>> with one 1 and N-1 0s or vice versa) fwl option may
> >>>>  >>> address problem.
> >>>>  >>>> I noticed that 2 states have a number of counties
> >>>>  >>> (clusters)
> >>>>  >>>> lower than the number of years available. By dropping
> >>>>  >>> these
> >>>>  >>>> two states STATA run the xtivreg2 without giving the
> >>>>  >>> error message.
> >>>>  >>>> I have read the help file and FAQ and I think
> >>>>  >>> something is
> >>>>  >>>> going with those state by year effects that creates a
> >>>>  >>> kind of
> >>>>  >>>> singleton dummy problem, but I am not sure Any 
> help would be
> >>>>  >>>> appreciated
> >>>>  >>> It's not a problem.
> >>>>  >>>
> >>>>  >>> You will note that xtivreg2 does not report the fixed 
> >>>> effect dummy
> >>>>  >>> variables.
> >>>>  >>>
> >>>>  >>> xi: ivreg2 explicitly includes the dummies, and the
> >>>>  >> coefficients are
> >>>>  >>> reported.
> >>>>  >>>
> >>>>  >>> The warning message reported by ivreg2 is triggered by the
> >>>>  >> fact that
> >>>>  >>> there are now many more rows/columns in the VCV, the new,
> >>>>  >> extended VCV
> >>>>  >>> is no longer full rank.
> >>>>  >>>
> >>>>  >>> In fact, the coefficients and standard errors for the
> >>>>  >> dummies aren't
> >>>>  >>> consistent anyway (under the usual panel data 
> >>>> assumptions - this is
> >>>>  >>> the "incidental parameters problem").  So you really aren't
> >>>>  >> interested
> >>>>  >>> in the extended VCV anyway.
> >>>>  >>>
> >>>>  >>> HTH,
> >>>>  >>> Mark
> >>>>  >>> 
> >>>>  >>>> thank you
> >>>>  >>>> sara
> >>>>  >>>>
> >>>>  >>>>
> >>>>  >>>>
> >>>>  >>>>       
> >>>>  >>>>
> >>>>  >>>> *
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> >>>>  >>>>
> >>>>  >>>
> >>>>  >>> --
> >>>>  >>> Heriot-Watt University is a Scottish charity registered
> >>>>  >> under charity
> >>>>  >>> number SC000278.
> >>>>  >>>
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> >>>>  >>      
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> >>>       
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