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" <[email protected]>
An: [email protected]
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: [email protected] [mailto:[email protected]] On Behalf Of P K
Sent: Miércoles, 20 de Mayo de 2009 04:13 p.m.
To: [email protected]
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" <[email protected]>
An: [email protected]
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: [email protected] [mailto:[email protected]] On Behalf Of P K
Sent: Miércoles, 20 de Mayo de 2009 01:52 p.m.
To: [email protected]
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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