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Re: st: GMM error (bug in Stata?)
From
John Antonakis <[email protected]>
To
[email protected]
Subject
Re: st: GMM error (bug in Stata?)
Date
Sun, 30 Oct 2011 06:54:11 +0100
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
<[email protected]> 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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