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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 16:24:13 -0700 (PDT)

thanks. 
When I enter the dummies in a multi-stage approach, rho is always zero, and stays zero throughout the adding of more dummies.
Is there another way to detect collinearity between the dummies and the constant term (such as pwcorr for the independent variables' correlation)?



----- Ursprüngliche Mail ----
Von: "Villa Lora, Juan Miguel" <JUANMIGUELV@Contractual.iadb.org>
An: statalist@hsphsun2.harvard.edu
Gesendet: Mittwoch, den 20. Mai 2009, 16:35:30 Uhr
Betreff: RE: st: RE: random effects panel model - interpretation of rho=0

Perhaps there's a problem with the specification of your equation regarding to the dummies variables: the variance of the estimation could be affected by a possible collinearity between dummies and the constant term as it's std. err is quite high. For bearing out this: What it happens to 'rho' if you include the dummies one by one (multi-stage)? 

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of P K
Sent: Miércoles, 20 de Mayo de 2009 04:13 p.m.
To: statalist@hsphsun2.harvard.edu
Subject: AW: st: RE: random effects panel model - interpretation of rho=0

thanks. Here's the result of the xtdes command:


. xtdes

  number:  1, 2, ..., 67                                     n =         67
    year:  1995, 1996, ..., 2004                             T =         10
           Delta(year) = 1 unit
           Span(year)  = 10 periods
           (number*year uniquely identifies each observation)

Distribution of T_i:   min      5%     25%       50%       75%     95%     max
                        10      10      10        10        10      10      10

     Freq.  Percent    Cum. |  Pattern
---------------------------+------------
       67    100.00  100.00 |  1111111111
---------------------------+------------
       67    100.00         |  XXXXXXXXXX

. 
end of do-file





and here's the command line of the xtreg command:

xtreg AverChangeROEadj2 duration_change sicchange ukdum frendum lgcount_strategy mutdum lloylistdum lloynlistdum, re


(FYI- sicchange ukdum frendum lgcount_strategy mutdum lloylistdum lloynlistdum are all control dummies)

Pat


----- Ursprüngliche Mail ----
Von: "Villa Lora, Juan Miguel" <JUANMIGUELV@Contractual.iadb.org>
An: statalist@hsphsun2.harvard.edu
Gesendet: Mittwoch, den 20. Mai 2009, 14:02:56 Uhr
Betreff: st: RE: random effects panel model - interpretation of rho=0

I would need further information. Please copy the result of the execution of the command xtdes and the command line of the regress..., re

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of P K
Sent: Miércoles, 20 de Mayo de 2009 01:52 p.m.
To: statalist@hsphsun2.harvard.edu
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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