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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 21:38:36 -0000

John,

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> John Antonakis
> Sent: 12 February 2010 21:02
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: ivreg versus xtivreg
> 
> Interestingly, the Hansen J is non significant when I specify 
> the model with the "robust" vce option. However, I cannot 
> obtain the J test when clustering (as mention, I get the 
> "warming" message).

I have a hunch ... there's an undocumented ivreg2 option -spsd-.  For some special cases, it will take a non-pd VCV and make it pd using a spectral decomposition.  What happens if you reestimate using this option?

--Mark

> 
> Intuitively, would you think that the Hansen J would be close 
> to that obtained from the two-way clustered J?  I guess that 
> there is no "trick" 
> of sorts or something that could be done to get an idea if 
> the overidentifying restrictions are viable.
> 
> 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 17:53, Schaffer, Mark E wrote:
> > 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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> >>>>>>  >>>
> >>>>>>  >>> --
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