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RE: st: RE: ivreg2 and xtoverid error


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: RE: ivreg2 and xtoverid error
Date   Sat, 3 Apr 2010 20:12:45 +0100

John,

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> John Antonakis
> Sent: 03 April 2010 17:45
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: ivreg2 and xtoverid error
> 
> Thanks Mark.
> 
> I realize that the test of endogeneity is not one of 
> instrument validity. My thinking was that if OLS seems like 
> it is not consistent then I am better off with IV, which is 
> less efficient and given what evidence I currently have, 
> probably consistent.

I understand now.  But Kit's caveats are worth bearing in mind, even if
there isn't much you can do about it. 

> The instruments are fixed-effects (of 
> leaders); thus, these individual differences due to leaders 
> (stemming from ability, personality, are constant and 
> theoretically exogenous as they are mostly genetically determined).

They could still be correlated with the disturbance term and hence
endogenous in an econometric sense, even if they are exogenous in a
model sense.  But that's getting away from the topic, namely why don't
-ivreg2- or -ivregress- give you first-stage a.k.a. under- or
weak-identification statistics when presented with an enormous reduced
form matrix.

> Unfortunately, -ivregress- does not give me the first-stage critical
> values: it says "(not available)".

Looks like it is running into the same problems as -ivreg2-.

If you want to pursue this further, feel free to contact me off-list.
I'd be interested in tracing the problem and seeing when the missing
values in the matrix calculations start showing up.

Cheers,
Mark

> Thanks for your help.
> 
> 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 03.04.2010 16:56, 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: 03 April 2010 14:47
> >> To: statalist@hsphsun2.harvard.edu
> >> Subject: Re: st: RE: ivreg2 and xtoverid error
> >>
> >> Hi Mark
> >>
> >> Thanks for the note.
> >>
> >> I get exactly the same estimates and standard errors with
> >> -ivreg- and -ivregress-, with the cluster robust variance 
> estimator.  
> >> When using
> >> -ivreg2- with the  -noid- option it works and I get the same 
> >> estimates; more importantly, I also get the Hansen J-test,
> >>     
> >
> > Looks like it was -ranktest- that was also causing invsym() 
> to choke, 
> > probably for the same reason - the reduced form first-stage 
> matrix is 
> > probably too big and badly behaved for it to cope.
> >
> >   
> >> which is what interests me most (the -ivregress- estimator 
> does not 
> >> report an overid for cluster-robust vce's):
> >>
> >> Hansen J statistic (overidentification test of all instruments): 
> >> 402.476, Chi-sq(404) P-val =  0.5121
> >>
> >> Note, my estimates make sense and the regressors I expected to be 
> >> significant are mostly significant. I guess I can assume that my 
> >> estimates are consistent--and this because the endogeneity test is 
> >> significant (from -ivregres-), right?
> >>     
> >
> > You can get -ivreg2- to give you an endogeneity test statistic with 
> > the
> > -endog- option.  I think it will agree with the -estat- test.
> >
> > But -estat endogenous- and -ivreg2,endog()- are testing whether you 
> > need to treat your endogenous regressors x1-x13 as 
> endogenous (and the 
> > answer seems to be yes, you do).  They aren't testing whether your 
> > equation is underidentified or weakly identified, which is 
> what you'd 
> > also like to know.  This is the test that -ranktest- and 
> -ivreg2- are 
> > choking on because the matrix is so big.
> >
> > I'd be curious to know if Stata's -estat firststage- is able to 
> > generate the Cragg-Donald ("minimum eigenvalue") 
> > under/weak-identification statistic in your case.  You'll 
> need to use 
> > the -forcenonrobust- option to get it if you're using 
> cluster-robust.
> >
> > Cheers,
> > Mark
> >
> >   
> >> . estat endogenous
> >>
> >>   Tests of endogeneity
> >>   Ho: variables are exogenous
> >>
> >>   Robust regression F(13,417)     =  119.753  (p = 0.0000)
> >>     (Adjusted for 418 clusters in lead_number)
> >>
> >> 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 03.04.2010 15:16, Schaffer, Mark E wrote:
> >>     
> >>> John,
> >>>
> >>> You've got a very large number of instruments (almost 500),
> >>>       
> >> but also
> >>     
> >>> 13 endogenous regressors.  The under- and weak-id statistics are 
> >>> calculated by -ranktest-, and it's running of memory
> >>>       
> >> because it works
> >>     
> >>> with the reduced form in matrix form (13 first-stage
> >>>       
> >> regressions, each
> >>     
> >>> with almost 500 regressors).
> >>>
> >>> If you use the -noid- option, it might address that 
> problem problem 
> >>> (but you won't get the weak id stats).
> >>>
> >>> The
> >>>
> >>> invsym(): matrix has missing values
> >>>
> >>> is different.  -ivreg2- is having problems inverting this 
> huge Z'Z 
> >>> matrix  and -ivregress- isn't (I think possibly because 
> the latter 
> >>> uses a different Mata matrix inversion function).  I do
> >>>       
> >> wonder whether
> >>     
> >>> the results you're getting actually make sense.
> >>>
> >>> Have you tried using the old -ivreg-, which uses 
> -regress-?  It is 
> >>> numerically very stable and accurate.  Does it give the
> >>>       
> >> same results
> >>     
> >>> as -ivregress-?
> >>>
> >>> Cheers,
> >>> Mark
> >>>
> >>>   
> >>>       
> >>>> -----Original Message-----
> >>>> From: owner-statalist@hsphsun2.harvard.edu
> >>>> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of John 
> >>>> Antonakis
> >>>> Sent: 03 April 2010 01:20
> >>>> To: statalist@hsphsun2.harvard.edu
> >>>> Subject: st: ivreg2 and xtoverid error
> >>>>
> >>>> Hi:
> >>>>
> >>>> I am running Stata version 11 and have everything up to date.
> >>>>
> >>>> When running a two-stage model with ivreg2, I get the
> >>>>         
> >> following error:
> >>     
> >>>> . xi: ivreg2 sat (x1-x13=i.lead_n) , cluster(lead_n)
> >>>> i.lead_number     _Ilead_numb_1-484   (naturally coded; 
> >>>>         
> >> _Ilead_numb_1
> >>     
> >>>> omitted)
> >>>>              quadcross():  3900  unable to allocate real 
> >>>> <tmp>[5421,5421]
> >>>>                 rkstat():     -  function returned error
> >>>>                  <istmt>:     -  function returned error
> >>>> r(3900);
> >>>>
> >>>> If I remove the vce cluster command I get another error:
> >>>>
> >>>> . xi: ivreg2 y (x1-x13=i.lead_n) ,
> >>>> i.lead_number     _Ilead_numb_1-484   (naturally coded; 
> >>>>         
> >> _Ilead_numb_1
> >>     
> >>>> omitted)
> >>>>
> >>>> invsym(): matrix has missing values
> >>>>
> >>>> This model is estimated fine with the official -ivregress-
> >>>>         
> >> command,
> >>     
> >>>> whether I use a cluster-robust or normal variance 
> estimator, e.g.,
> >>>>
> >>>> . xi: ivregress 2sls y (x1-x13=i.lead_n) ,cluster(lead_n)
> >>>> i.lead_number     _Ilead_numb_1-484   (naturally coded; 
> >>>>         
> >> _Ilead_numb_1
> >>     
> >>>> omitted)
> >>>>
> >>>> Instrumental variables (2SLS) regression               
> >>>>         
> >> Number of obs
> >>     
> >>>> =     832
> >>>>                                                        
> >>>>         
> >> Wald chi2(13)
> >>     
> >>>> =
> >>>> 1020.01
> >>>>                                                        Prob > 
> >>>> chi2   =  
> >>>> 0.0000
> >>>>                                                        
> >>>> R-squared     =  
> >>>> 0.7020
> >>>>                                                        Root 
> >>>> MSE      =   
> >>>> .2955
> >>>>
> >>>>                           (Std. Err. adjusted for 418 clusters in
> >>>> lead_number)
> >>>> --------------------------------------------------------------
> >>>> ----------------
> >>>>              |               Robust
> >>>>            y |      Coef.   Std. Err.      z    P>|z|     
> >>>>         
> >> [95% Conf. 
> >>     
> >>>> Interval]
> >>>> -------------+------------------------------------------------
> >>>> ----------
> >>>> -------------+------
> >>>>           x1 |   .3849406   .0509433     7.56   0.000     
> >>>>         
> >> .2850935    
> >>     
> >>>> .4847877
> >>>>           x2 |  -.0452167   .0541093    -0.84   0.403    
> >>>>         
> >> -.1512689    
> >>     
> >>>> .0608355
> >>>>           x3 |  -.0214062   .0392473    -0.55   0.585    
> >>>>         
> >> -.0983295    
> >>     
> >>>> .0555171
> >>>>           x4 |   .0743079   .0528296     1.41   0.160    
> >>>> -.0292363     
> >>>> .177852
> >>>>           x5 |   .1559398    .056997     2.74   0.006     
> >>>>         
> >> .0442276    
> >>     
> >>>> .2676519
> >>>>           x6 |    .168241   .0577832     2.91   0.004     
> >>>> .0549879     
> >>>> .281494
> >>>>           x7 |  -.1359489   .0290323    -4.68   0.000    
> >>>>         
> >> -.1928512   
> >>     
> >>>> -.0790465
> >>>>           x8 |   .0485811   .0358857     1.35   0.176    
> >>>>         
> >> -.0217535    
> >>     
> >>>> .1189157
> >>>>           x9 |  -.1772587   .0512706    -3.46   0.001    
> >>>>         
> >> -.2777472   
> >>     
> >>>> -.0767701
> >>>>          x10 |   .1785753   .0570718     3.13   0.002     
> >>>>         
> >> .0667166    
> >>     
> >>>> .2904339
> >>>>          x11 |   .0309138   .0533183     0.58   0.562    
> >>>>         
> >> -.0735883    
> >>     
> >>>> .1354158
> >>>>          x12 |   .2282491   .0554658     4.12   0.000     
> >>>> .1195381      
> >>>> .33696
> >>>>          x13 |  -.0723148   .0486346    -1.49   0.137    
> >>>>         
> >> -.1676369    
> >>     
> >>>> .0230072
> >>>>        _cons |   .4183937   .1616004     2.59   0.010     
> >>>>         
> >> .1016627    
> >>     
> >>>> .7351247
> >>>> --------------------------------------------------------------
> >>>> ----------------
> >>>> Instrumented:  x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13
> >>>> Instruments:   _Ilead_numb_2 _Ilead_numb_3 _Ilead_numb_4 
> >>>>         
> >> _Ilead_numb_5
> >>     
> >>>> [output snipped]
> >>>>
> >>>>
> >>>> Interestingly, when I run it with -xtivreg-, the model is
> >>>>         
> >> estimated
> >>     
> >>>> fine; however, -xtoverid- gives me the following error:
> >>>>
> >>>> . xtoverid
> >>>> invsym(): matrix has missing values r(504);
> >>>>
> >>>> This is the same error that follows ivreg2 estimation.
> >>>>
> >>>> I suspect it might have something to do with the fact that
> >>>>         
> >> I have a
> >>     
> >>>> large number of instruments (fixed-effects, with 483
> >>>> dummies) and clustering on those fixed-effects.
> >>>>
> >>>> Best,
> >>>> 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
> >>>> ____________________________________________________
> >>>>
> >>>>
> >>>> *
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> >>>>
> >>>>     
> >>>>         
> >>>   
> >>>       
> >> *
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> >>     
> >
> >
> >   
> *
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