st: RE: ivreg2 and xtoverid error

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

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:
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> 
> Personal page:
> http://www.hec.unil.ch/jantonakis
> ____________________________________________________
> 
> 
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