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Re: st: sigma u listed as zero despite unit variance


From   "Alfonso Miranda Caso Luengo" <Alfonso.Miranda-Caso-Luengo@warwick.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: sigma u listed as zero despite unit variance
Date   Tue, 24 Feb 2004 16:08:43 +0000

Ignore my last post. In this case there is no such transformation.  

===========================================
Alfonso Miranda
PhD Student

Economics Department
University of Warwick
Coventry CV4 7AL
E-mail: Alfonso.Miranda-Caso-Luengo@warwick.ac.uk
===========================================
>>> Alfonso.Miranda-Caso-Luengo@warwick.ac.uk 02/24/04 16:03 PM >>>
I guess sigma_u = log(sigma). In many cases Stata  estimates a function of an auxiliary parameter instead of the parameter itself. This thick helps to keep estimates whithin a set of admissible values and ease ML maximisation. In any case, you could always recover the value of the parameter in the original scale applying the inverse function. Standard errors may be obtained  using the delta method.     

===========================================
Alfonso Miranda
PhD Student

Economics Department
University of Warwick
Coventry CV4 7AL
E-mail: Alfonso.Miranda-Caso-Luengo@warwick.ac.uk
===========================================
>>> aboydstun@psu.edu 02/24/04 15:39 PM >>>
I'm very confused about why the sigma_u listed in the output from a random
effects model reports a value of zero, despite the fact that I have unit
variance in my dataset (I promise).  I'm attaching the output below.  Could
someone please tell me what this means?  Thanks!




xtreg dppct educpct repubpct fundpct whitepct, re;

Random-effects GLS regression                   Number of obs      =       220
Group variable (i) : cohort                     Number of groups   =        10

R-sq:  within  = 0.0577                         Obs per group: min =        22
       between = 0.6344                                        avg =      22.0
       overall = 0.0622                                        max =        22

Random effects u_i ~ Gaussian                   Wald chi2(4)       =     14.27
corr(u_i, X)       = 0 (assumed)                Prob > chi2        =    0.0065

------------------------------------------------------------------------------
       dppct |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     educpct |   .0596706   .0526787     1.13   0.257    -.0435777    .1629189
    repubpct |   .2223392   .1046384     2.12   0.034     .0172516    .4274267
     fundpct |   .2698267   .1397987     1.93   0.054    -.0041737     .543827
    whitepct |   .2623254   .1236531     2.12   0.034     .0199697    .5046811
       _cons |   .2656249   .1358642     1.96   0.051     -.000664    .5319138
-------------+----------------------------------------------------------------
     sigma_u |          0
     sigma_e |  .09882399
         rho |          0   (fraction of variance due to u_i)
------------------------------------------------------------------------------
Amber E. Boydstun
Graduate Student
Department of Political Science
Penn State University
University Park, PA 16802-6200
aboydstun@psu.edu
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