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st: RE: OLS equivalence for unbalanced panel


From   Alexander Turner <[email protected]>
To   "[email protected]" <[email protected]>
Subject   st: RE: OLS equivalence for unbalanced panel
Date   Fri, 5 Jul 2013 09:01:26 +0000

Wahooo!! 

Both of these options work. 

However, they change the coefficients in different ways - we should probably try and find some literature about whether the mle or sa option is preferable, and this might also give us some information about what the issue with traditional estimator is.

Alex
________________________________________
From: [email protected] [[email protected]] on behalf of Silviya Nikolova [[email protected]]
Sent: 04 July 2013 17:09
To: [email protected]
Subject: st: OLS equivalence for unbalanced panel

Dear Statalist,

I am estimating RE model (xtreg) using unbalanced panel dataset. Sigma_u for some reason is 0. My dependent variable is discrete with large variation. To understand why this is the case, I tried:
1. Add some iid normal noise to the data
2. Drop groups with small number of observations in them
These two approaches do not make a difference.
3. Reduce the number of variables (after sufficient number of dropped variables sigma_u became > 0).
4. Expand the data using --expand 2-- command. This generates non-zero sigma_u as well.
Is there any reasonable explanation for all 4 of these? 2 and 3 in isolation can be explained easily.

This is a snippet of the output before expand:

. xtreg q2_OHS ISTC q1_OHS ${q1_eq5d_elem_nf} q1_eq5d_health_scale ${other_health_nf} ${comorbs_nf} ${pa
> tients_nf_`severity'} ${provider_nf}, re

Random-effects GLS regression                   Number of obs      =     36090
Group variable: procode1                        Number of groups   =       246

R-sq:  within  = 0.2200                         Obs per group: min =         1
       between = 0.6405                                        avg =     146.7
       overall = 0.2415                                        max =      1017

                                                Wald chi2(45)      =  11473.56
corr(u_i, X)   = 0 (assumed)                    Prob > chi2        =    0.0000


--------------------------------------------------------------------------------------

. . .

---------------------+----------------------------------------------------------------
             sigma_u |          0
             sigma_e |  8.2124003
                 rho |          0   (fraction of variance due to u_i)
--------------------------------------------------------------------------------------



And after expand:

. preserve

. expand 2
(133799 observations created)

. xtset procode1

. xtreg q2_OHS ISTC q1_OHS ${q1_eq5d_elem_nf} q1_eq5d_health_scale ${other_health_nf} ${comorbs_nf} ${pa

> tients_nf_`severity'} ${provider_nf}, re

Random-effects GLS regression                   Number of obs      =     72180
Group variable: procode1                        Number of groups   =       246

R-sq:  within  = 0.2200                         Obs per group: min =         2
       between = 0.6400                                        avg =     293.4
       overall = 0.2409                                        max =      2034

                                                Wald chi2(45)      =  20798.64
corr(u_i, X)   = 0 (assumed)                    Prob > chi2        =    0.0000

--------------------------------------------------------------------------------------

. . .

---------------------+----------------------------------------------------------------
             sigma_u |   1.115697
             sigma_e |  8.1965088
                 rho |  .01819121   (fraction of variance due to u_i)
--------------------------------------------------------------------------------------

. restore


Thank you.

Silviya


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