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Re: st: sigma_u = 0 in xtreg, re
From
John Antonakis <[email protected]>
To
[email protected]
Subject
Re: st: sigma_u = 0 in xtreg, re
Date
Tue, 30 Aug 2011 08:18:51 +0200
OK. Thus, Lloyed might as well use pooled OLS with cluster robust
standard errors, right?
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 30.08.2011 00:05, Schaffer, Mark E wrote:
I think it's true in finite samples as well. At least, that's how I read what Baltagi has to say about it in chap 2 of his textbook ("Econometric Analysis of Panel Data" - it's in the section on the random effects model).
--Mark
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of
Stas Kolenikov
Sent: 29 August 2011 22:26
To: [email protected]
Subject: Re: st: sigma_u = 0 in xtreg, re
John,
certainly so asymptotically when the true sigma_u = 0.
Whether that is exactly true in finite samples, I don't know,
although at the face of it, it looks reasonable:
set seed 1234
set obs 100
gen id = _n
gen ni = rpoisson(5) + 1
expand ni
gen x = uniform()
gen y = x + rnormal()
xtreg y x, i(id)
reg y x
On Mon, Aug 29, 2011 at 4:14 PM, John Antonakis
<[email protected]> wrote:
One clarification; when rho = 0 aren't these estimates
simply OLS estimates?
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 29.08.2011 22:50, Stas Kolenikov wrote:
Note that you have a very decent R^2, especially the
between one. It
looks, hence, that all of the bewteen-panel variability in Y is
explained by the between-panel variability in X's (the ICC's were
quite similar for each of the variables), so there indeed
is little
left that needs explaining. -xtsum- is somewhat misleading
here, as
this is a marginal measure, not a conditional one (which is what
matters for the regression).
Technically speaking, you are hitting a corner solution
for sigma_u.
In the simplest form of the estimator for sigma_u, it is formed as
[mean total square] - [mean within square], so substraction of two
non-negative quantities gave you a negative quantity (which was
truncated upwards to zero). More elaborate estimators exist that
guarantee both within and between sigmas to be positive, but for a
vast majority of situations, the simple one should do just
fine, so
that's what -xtreg, re- does.
On Mon, Aug 29, 2011 at 1:45 PM, Lloyd
Dumont<[email protected]>
wrote:
Hello, Statalist.
I am a little confused by the output from an -xtreg, re- estimate.
Basically, I end up with sigma_u = 0, which of course
yields rho = 0.
That seems very odd to me. I would guess that that should only
happen if there is no between-subject variation. But, (I
think) I
can tell from examining the data that that is not the case.
I have tried to create a mini example... First, I will
show the xtreg
results. Then, I will show you what I think is the evidence that
there really IS some between-subject variation.
Am I missing something obvious here? Thank you for your help and
suggestions. Lloyd Dumont
. xtreg Y X, re
Random-effects GLS regression Number of
obs =
3133
Group variable: ID Number of
groups =
31
R-sq: within = 0.4333 Obs per
group: min =
1
between = 0.8278
avg =
101.1
overall = 0.4579
max =
124
Wald
chi2(1) =
2644.38
corr(u_i, X) = 0 (assumed) Prob>
chi2 =
0.0000
--------------------------------------------------------------------
----------
Y | Coef. Std. Err. z P>|z|
[95% Conf.
Interval]
-------------+------------------------------------------------------
-------------+----------
X | -.0179105 .0003483 -51.42 0.000 -.0185932
-.0172279
_cons | 1.004496 .0017687 567.92 0.000 1.001029
1.007963
-------------+------------------------------------------------------
-------------+----------
sigma_u | 0
sigma_e | .07457648
rho | 0 (fraction of variance due to u_i)
--------------------------------------------------------------------
----------
. xtsum X
Variable | Mean Std. Dev. Min Max |
Observations
-----------------+--------------------------------------------+-----
-----------------+--------------------------------------------+-----
-----------------+--------------------------------------------+-----
-----------------+--------------------------------------------+-
X overall | 3.277883 3.875116 0
42.5 |
N =
3137
between | 1.286754 0
6.890338 | n
=
31
within | 3.729614 -3.612455
42.24883 | T-bar
=
101.194
. xtsum Y
Variable | Mean Std. Dev. Min Max |
Observations
-----------------+--------------------------------------------+-----
-----------------+--------------------------------------------+-----
-----------------+--------------------------------------------+-----
-----------------+--------------------------------------------+-
Y overall | .9457124 .1025887 0
1 |
N =
3133
between | .0315032 .8387879
1 | n
=
31
within | .0985757 -.0235858
1.106925 | T-bar
=
101.065
.
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--
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.
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