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RE: st: GMM error (bug in Stata?)


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: GMM error (bug in Stata?)
Date   Sun, 30 Oct 2011 15:34:22 -0000

John,

When you don't stack, do you get nonzero values for the maximized GMM
objective functions?

--Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> John Antonakis
> Sent: 30 October 2011 15:01
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: GMM error (bug in Stata?)
> 
> Hi Mark:
> 
> I am unsure, particularly because gmm works when I don't 
> stack the models. I have send the dataset and code to the 
> Stata people to look at (also, forgot to mention, I am using 
> Stata 11).
> 
> Best,
> J.
> 
> __________________________________________
> 
> Prof. John Antonakis
> 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
> http://www.hec.unil.ch/people/jantonakis
> 
> Associate Editor
> The Leadership Quarterly
> __________________________________________
> 
> 
> On 30.10.2011 12:47, Schaffer, Mark E wrote:
>  > John,
>  >
>  > I see from the output that after an iteration, the value 
> of the GMM  > objective function becomes very small, e.g., 
> 1.656e-33 ... in other  > words, zero.
>  >
>  > This could happen if the model is exactly identified, or 
> (if I remember  > the discussion in Hall's GMM book 
> correctly) if the rank of the VCV of  > moment conditions is 
> PSD instead of PD.  Could either of these be the  > explanation?
>  >
>  > Cheers,
>  > Mark
>  >
>  >> -----Original Message-----
>  >> From: owner-statalist@hsphsun2.harvard.edu
>  >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf 
> Of  >> John Antonakis  >> Sent: 30 October 2011 05:54  >> To: 
> statalist@hsphsun2.harvard.edu  >> Subject: Re: st: GMM error 
> (bug in Stata?)  >>  >> Hi Stas (and Cam):
>  >>
>  >> Thanks for the follow-up but its not the number of 
> clusters  >> that is causing the problem; I have 418 of them 
> (refers to  >> the output of the first note:
>  >>
>  >> Here is the output from the first gmm estimation:
>  >> Step 1
>  >> Iteration 0:   GMM criterion Q(b) =  13.184222
>  >> Iteration 1:   GMM criterion Q(b) =  1.497e-26
>  >> Iteration 2:   GMM criterion Q(b) =  4.387e-32
>  >>
>  >> Step 2
>  >> Iteration 0:   GMM criterion Q(b) =  4.314e-33
>  >> Iteration 1:   GMM criterion Q(b) =  4.314e-33  (backed up)
>  >>
>  >> GMM estimation
>  >>
>  >> Number of parameters =  14
>  >> Number of moments    =  14
>  >> Initial weight matrix: Unadjusted                     
> Number of obs
>  >> =    3344
>  >> GMM weight matrix:     Cluster (lead_n)
>  >>
>  >>                                 (Std. Err. adjusted for 418
>  >> clusters in
>  >> lead_n)
>  >> --------------------------------------------------------------
>  >> ----------------
>  >>               |               Robust
>  >>               |      Coef.   Std. Err.      z    P>|z|    
>  [95% Conf.
>  >> Interval]
>  >> -------------+------------------------------------------------
>  >> ----------
>  >> -------------+------
>  >>           /b1 |   1.049204   .0549893    19.08   0.000
>  >> .9414266
>  >> 1.156981
>  >>           /b2 |   1.078344   .0586466    18.39   0.000
>  >> .9633983
>  >> 1.193289
>  >>           /b3 |   .9043237   .0616768    14.66   0.000
>  >> .7834394
>  >> 1.025208
>  >>           /b4 |    1.04687   .0528909    19.79   0.000
>  >> .9432057
>  >> 1.150534
>  >>           /b5 |   1.043876   .0569363    18.33   0.000
>  >> .9322833
>  >> 1.155469
>  >>           /b6 |    1.01851   .0592967    17.18   0.000
>  >> .9022906
>  >> 1.134729
>  >>           /b7 |   .9258437   .0602654    15.36   0.000
>  >> .8077256
>  >> 1.043962
>  >>           /b8 |   .9485584   .0553715    17.13   0.000
>  >> .8400322
>  >> 1.057085
>  >>           /b9 |   1.066044   .0601146    17.73   0.000
>  >> .9482216
>  >> 1.183867
>  >>          /b10 |   1.075929   .0577217    18.64   0.000
>  >> .9627967
>  >> 1.189062
>  >>          /b11 |   1.017601   .0614807    16.55   0.000
>  >> .8971007
>  >> 1.138101
>  >>          /b12 |  -.9610472   .0526738   -18.25   0.000    
> -1.064286
>  >> -.8578085
>  >>          /b13 |  -.9627249   .0589321   -16.34   0.000    
>  -1.07823
>  >> -.8472202
>  >>           /b0 |  -.1096011   .0587362    -1.87   0.062
>  >> -.2247219
>  >> .0055198
>  >> --------------------------------------------------------------
>  >> ----------------
>  >> Instruments for equation 1: x_fe1 x_fe2 x_fe3 x_fe4 x_fe5 
> x_fe6 x_fe7  >> x_fe8 x_fe9 x_fe10
>  >>      x_fe11 x_fe12 x_fe13 _cons
>  >>
>  >> Here's the output from the second gmm estimation:
>  >>
>  >> Step 1
>  >> Iteration 0:   GMM criterion Q(b) =  12.045213
>  >> Iteration 1:   GMM criterion Q(b) =  2.209e-26
>  >> Iteration 2:   GMM criterion Q(b) =  1.786e-32
>  >>
>  >> Step 2
>  >> Iteration 0:   GMM criterion Q(b) =  1.883e-33
>  >> Iteration 1:   GMM criterion Q(b) =  1.656e-33
>  >>
>  >> GMM estimation
>  >>
>  >> Number of parameters =  14
>  >> Number of moments    =  14
>  >> Initial weight matrix: Unadjusted                     
> Number of obs
>  >> =    3344
>  >> GMM weight matrix:     Cluster (lead_n)
>  >>
>  >>                                 (Std. Err. adjusted for 418
>  >> clusters in
>  >> lead_n)
>  >> --------------------------------------------------------------
>  >> ----------------
>  >>               |               Robust
>  >>               |      Coef.   Std. Err.      z    P>|z|    
>  [95% Conf.
>  >> Interval]
>  >> -------------+------------------------------------------------
>  >> ----------
>  >> -------------+------
>  >>           /c1 |   .9598146   .0517448    18.55   0.000
>  >> .8583967
>  >> 1.061232
>  >>           /c2 |   .9256337   .0535588    17.28   0.000
>  >> .8206605
>  >> 1.030607
>  >>           /c3 |   .8305105   .0582733    14.25   0.000
>  >> .7162969
>  >> .9447241
>  >>           /c4 |    .956631   .0482825    19.81   0.000
>  >> .8619991
>  >> 1.051263
>  >>           /c5 |   .9736638    .053159    18.32   0.000
>  >> .8694742
>  >> 1.077853
>  >>           /c6 |   .9493385   .0541098    17.54   0.000
>  >> .8432853
>  >> 1.055392
>  >>           /c7 |   .8518398   .0555893    15.32   0.000
>  >> .7428867
>  >> .9607929
>  >>           /c8 |   .8813955    .051279    17.19   0.000
>  >> .7808906
>  >> .9819004
>  >>           /c9 |   .9793823   .0518981    18.87   0.000
>  >> .877664
>  >> 1.081101
>  >>          /c10 |   .9923967   .0533734    18.59   0.000
>  >> .8877868
>  >> 1.097007
>  >>          /c11 |   .8911549   .0555809    16.03   0.000
>  >> .7822183
>  >> 1.000092
>  >>          /c12 |   -.865805   .0502334   -17.24   0.000    
> -.9642607
>  >> -.7673493
>  >>          /c13 |  -.8909156   .0537489   -16.58   0.000    
> -.9962615
>  >> -.7855697
>  >>           /c0 |  -.1046114   .0564682    -1.85   0.064
>  >> -.2152871
>  >> .0060643
>  >> --------------------------------------------------------------
>  >> ----------------
>  >> Instruments for equation 1: x_clus1 x_clus2 x_clus3 
> x_clus4 x_clus5  >> x_clus6 x_clus7 x_clus8
>  >>      x_clus9 x_clus10 x_clus11 x_clus12 x_clus13 _cons
>  >>
>  >> Best,
>  >> J.
>  >>
>  >> __________________________________________
>  >>
>  >> Prof. John Antonakis
>  >> 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  >> http://www.hec.unil.ch/people/jantonakis
>  >>
>  >> Associate Editor
>  >> The Leadership Quarterly
>  >> __________________________________________
>  >>
>  >>
>  >> On 30.10.2011 00:40, Stas Kolenikov wrote:
>  >> > John,
>  >> >
>  >> > how many clusters do you have? May be you are running 
> out  >> of clusters > in estimation of the weight matrix if 
> you have  >> fewer clusters than > parameters.
>  >> >
>  >> > On Sat, Oct 29, 2011 at 11:56 AM, John Antonakis  >> 
> <John.Antonakis@unil.ch> wrote:
>  >> >> The goal of my estimation procedure is to make cross  
> >> model comparison, where >> the model have different  >> 
> instruments ( and given the clustering I have, I >> want to  
> >> have a generalized Hausman test hence the use of gmm). I 
> want  >> to >> show that the second stage estimates don't 
> change when  >> I change the >> instruments....it's a 
> simulation study I am  >> working on, hence the >> "strangeness".
>  >>
>  >> *
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>  >> *   http://www.ats.ucla.edu/stat/stata/
> 
> *
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> *   http://www.ats.ucla.edu/stat/stata/
> 


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