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st: rho, sigma_u, sigma_e in xtreg


From   "Katherine Packman" <[email protected]>
To   [email protected]
Subject   st: rho, sigma_u, sigma_e in xtreg
Date   Fri, 30 Apr 2010 14:34:12 -0600

I have somewhat of a basic question.

I am running xtreg assuming random effects for 150 observations (cross-section is 10 and timeseries is 15). I was wondering if anyone could explain what rho, sigma_u and sigma_e mean. This is an example of my output:


. xtreg pmor dumcov dumuni dum_cu lnprd prduni

Random-effects GLS regression                   Number of obs      =       150
Group variable: session                         Number of groups   =        10

R-sq:  within  = 0.2093                         Obs per group: min =        15
       between = 0.6968                                        avg =      15.0
       overall = 0.3196                                        max =        15

Random effects u_i ~ Gaussian                   Wald chi2(5)       =     50.32
corr(u_i, X)       = 0 (assumed)                Prob > chi2        =    0.0000

------------------------------------------------------------------------------
        pmor |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dumcov |   .1254805   .0344025     3.65   0.000     .0580529    .1929082
      dumuni |  -.0042582   .0392887    -0.11   0.914    -.0812628    .0727463
      dum_cu |  -.1437736   .0444134    -3.24   0.001    -.2308223   -.0567249
       lnprd |   -.077336   .0130727    -5.92   0.000     -.102958    -.051714
      prduni |   .0101917    .002951     3.45   0.001     .0044079    .0159756
       _cons |    .886512   .0343942    25.78   0.000     .8191005    .9539234
-------------+----------------------------------------------------------------
     sigma_u |  .02692048
     sigma_e |   .0829595
         rho |  .09526924   (fraction of variance due to u_i)
------------------------------------------------------------------------------


Any help would be appreciated.

Cheers

--
Katherine
University of Alberta




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