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AW: st: Re: random effects panel model - interpretation of rho=0


From   P K <statistics_2009@yahoo.de>
To   statalist@hsphsun2.harvard.edu
Subject   AW: st: Re: random effects panel model - interpretation of rho=0
Date   Wed, 20 May 2009 13:20:40 -0700 (PDT)

Hi Martin,

it gives me the summary of most variables in my dataset, which are far more than the ones used in the regression. Can I limit the command somehow to 
the variables used in my estimation? ...otherwise I would have to create a separate dataset for the variables used in the regression...

thanks



----- Ursprüngliche Mail ----
Von: Martin Weiss <martin.weiss1@gmx.de>
An: statalist@hsphsun2.harvard.edu
Gesendet: Mittwoch, den 20. Mai 2009, 14:01:43 Uhr
Betreff: st: Re: random effects panel model - interpretation of rho=0

<>

What does -xtsum if e(sample)- after estimation give you?


HTH
Martin
_______________________
----- Original Message ----- From: "P K" <statistics_2009@yahoo.de>
To: <statalist@hsphsun2.harvard.edu>
Sent: Wednesday, May 20, 2009 7:52 PM
Subject: st: random effects panel model - interpretation of rho=0


> 
> Hi,
> 
> I run a random effects panel model of 64 subjects for 10 years each and have a question concerning the results: My output tells me that
> 0% of the variance of the dependent variable is between subjects and 100% is within subjects (rho).
> 
> I am not sure whether I understand the interpretation correctly, but I find this result a bit uncommon given that I test for a random effects model and
> my theory predicts a lot of variation between my subjects.
> 
> Could there by any mistake in the analysis?
> Thanks,
> Pat
> 
> Here's the STATA output:
> 
> Random-effects GLS regression                   Number of obs      = 545
> Group variable: number                          Number of groups   = 64
> 
> R-sq:  within  = 0.0138                         Obs per group: min = 2
>       between = 0.1741                                        avg = 8.5
>       overall = 0.0168                                        max = 10
> 
> Random effects u_i ~ Gaussian                   Wald chi2(7)       = 9.16
> corr(u_i, X)       = 0 (assumed)                Prob > chi2        = 0.2416
> 
> ------------------------------------------------------------------------------
> AverCh~2adj2 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> duration_c~e |  -.9013214   .3550697    -2.54 0.011    -1.597245   -.2053976
>   sicchange |   2.527742   4.073774     0.62   0.535    -5.456709 10.51219
>       ukdum |   .5491039   1.126746     0.49   0.626    -1.659277 2.757485
>     frendum |  -1.780095   1.522111    -1.17   0.242    -4.763378 1.203189
> regnlistdum |  -.6389011    1.09439    -0.58   0.559    -2.783865 1.506063
>      mutdum |   .9720512   1.790017     0.54   0.587    -2.536318 4.48042
> lgcount_st~y |  -.2016355   .6181168    -0.33   0.744    -1.413122 1.009851
>       _cons |   1.249498   1.361879     0.92   0.359    -1.419735 3.918731
> -------------+----------------------------------------------------------------
>     sigma_u |          0
>     sigma_e |  11.774903
>         rho |          0   (fraction of variance due to u_i)
> ------------------------------------------------------------------------------
> 
> 
> 
> 
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