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re:re: re:st: Hausman test


From   Ricardo Ovaldia <ovaldia@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   re:re: re:st: Hausman test
Date   Tue, 3 Jan 2012 15:37:49 -0800 (PST)

Thank you Kit. That helped a lot.

Ricardo

Ricardo Ovaldia, MS
Statistician 
Oklahoma City, OK


--- On Tue, 1/3/12, Christopher Baum <kit.baum@bc.edu> wrote:

> From: Christopher Baum <kit.baum@bc.edu>
> Subject: re:re: re:st: Hausman test
> To: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
> Date: Tuesday, January 3, 2012, 3:07 PM
> <>
> Random-effects GLS regression       
>            Number of
> obs      =   
>    416
> Group variable: fam         
>                
>    Number of groups   = 
>        9
> 
> R-sq:  within  = 0.1185     
>                
>    Obs per group: min =     
>   27
>        between = 0.8693 
>                
>                
>       avg =      46.2
>        overall = 0.6005 
>                
>                
>       max =        73
> 
>                
>                
>                 Wald
> chi2(9)       =   
> 610.15
> corr(u_i, X)   = 0 (assumed)   
>                 Prob
> > chi2        =    0.0000
> 
> ------------------------------------------------------------------------------
>         chol |     
> Coef.   Std. Err.      z 
>   P>|z|     [95% Conf.
> Interval]
> -------------+----------------------------------------------------------------
>           l1
> |   6.341376   1.317354 
>    4.81   0.000   
>   3.75941    8.923342
>           l2
> |   -.170823   .0489787 
>   -3.49   0.000   
> -.2668195   -.0748265
>           l3
> |   .0016893    .000569 
>    2.97   0.003   
>   .000574    .0028046
>        2.sex |   
> 3.77881   .8776635 
>    4.31   0.000 
>    2.058621    5.498999
>              |
>       marker |
>           2  | 
> -1.579155   1.217692   
> -1.30   0.195    -3.965788 
>   .8074783
>           3  | 
> -1.128749    1.26016   
> -0.90   0.370    -3.598617 
>    1.34112
>           4 
> |   1.295496   2.350917 
>    0.55   0.582   
> -3.312217    5.903209
>           5  | 
> -.8996998   1.409237   
> -0.64   0.523    -3.661753 
>   1.862353
>           6 
> |   11.06828   3.289858 
>    3.36   0.001 
>    4.620282    17.51629
>              |
>        _cons | 
> -16.71301    11.0348   
> -1.51   0.130    -38.34082 
>   4.914797
> -------------+----------------------------------------------------------------
>      sigma_u |     
>     0
>      sigma_e |  8.1937869
>          rho |   
>       0   (fraction of
> variance due to u_i)
> ------------------------------------------------------------------------------
> 
> You have a corner solution. As you know, the estimates of
> the two error variances in RE are 'backed out' from
> estimates of other forms of the model. In your case, the
> estimate of sigma_u (and its square) is 0.0. That
> is nonsensical, as the FE form of the same model gives a
> meaningfully positive variance and the F-test for
> unobserved
> heterogeneity shows: 
> 
>      sigma_u |  5.0827273
>      sigma_e |  8.1937869
>          rho | 
> .27786908   (fraction of variance due to
> u_i)
> ------------------------------------------------------------------------------
> F test that all u_i=0:     F(8, 398)
> =     9.45       
>       Prob > F = 0.0000
> 
> indicating that there are significant panel-specific
> effects (that is, unobserved heterogeneity). A further
> reason
> to disregard the RE estimates, as you can't very well
> report the error components variances with one of them
> equal to zero (which it patently should not be; if it truly
> was, pooled OLS would be appropriate, but FE says it
> surely would not be so). 
> 
> This is probably the reason for the singularity of the
> Hausman VCE.
> 
> Cheers
> Kit
> 
> Kit Baum   |   Boston College
> Economics & DIW
> Berlin   |   http://ideas.repec.org/e/pba1.html
>                
>              An
> Introduction to Stata Programming 
> |   http://www.stata-press.com/books/isp.html
>   An Introduction to Modern Econometrics Using
> Stata  |   http://www.stata-press.com/books/imeus.html
> 
> 
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