[Limdep Nlogit List] standard errors in random effects regression

[Andreas Drichoutis]

Thanks for the quick reply. I added the ; PANEL and now I'm getting this
error message in every regression:

Error   425: REGR;PANEL. Could not invert VC matrix for Hausman test.


What does it mean? Should I ignore it?

-----Original Message-----
From: limdep-bounces at limdep.itls.usyd.edu.au
[mailto:limdep-bounces at limdep.itls.usyd.edu.au] On Behalf Of William Greene
Sent: Thursday, October 15, 2009 6:12 PM
To: Limdep and Nlogit Mailing List
Subject: Re: [Limdep Nlogit List] standard errors in random effects
regression

Your LIMDEP command is missing ;PANEL. You are not computing
GLS estimates, you are computing OLS with a 10 period Newey-West
correction. A striking thing is that Stata seems to be reporting
the OLS estimates with some other kind of standard errors. 
It looks like neither set of results is the feasible GLS estimates
you appear to be looking for.
/Bill Greene

----- Original Message -----
From: "Andreas Drichoutis" <adrihout at aua.gr>
To: "Limdep and Nlogit Mailing List" <limdep at limdep.itls.usyd.edu.au>
Sent: Thursday, October 15, 2009 11:07:39 AM GMT -05:00 US/Canada Eastern
Subject: [Limdep Nlogit List] standard errors in random effects regression

Can please someone explain the difference I'm getting from a random effects
regression in Limdep and Stata? Coefficient estimates are the same but
standard errors are completely different. I tend to get more statistical
significant variables in Limdep and tried this with several regressions.
Which ones should I report?

According to Limdep my treatment variable (TREAT_TR) is significant at the
10% level but is not significant according to Stata. In other regressions
I'm getting larger differences.

 

Regards,

Andreas Drichoutis

 

--> namelist ; x1=gender,age, period,treat_pr,treat_tr,one $

--> skip $

--> regress ; lhs=bet2lot5 ; rhs=x1 ; pds=10 $

 

+----------------------------------------------------+

| Ordinary    least squares regression               |

| Model was estimated Oct 15, 2009 at 05:47:51PM     |

| LHS=BET2LOT5 Mean                 =   1.532028     |

|              Standard deviation   =   1.210199     |

| WTS=none     Number of observs.   =        710     |

| Model size   Parameters           =          6     |

|              Degrees of freedom   =        704     |

| Residuals    Sum of squares       =   966.4366     |

|              Standard error of e  =   1.171657     |

| Fit          R-squared            =   .0692925     |

|              Adjusted R-squared   =   .0626823     |

| Model test   F[  5,   704] (prob) =  10.48 (.0000) |

| Autocorrel   Durbin-Watson Stat.  =   .4687073     |

|              Rho = cor[e,e(-1)]   =   .7656464     |

| Robust VC    Newey-West, Periods  =         10     |

+----------------------------------------------------+

+--------+--------------+----------------+--------+--------+----------+

|Variable| Coefficient  | Standard Error |b/St.Er.|P[|Z|>z]| Mean of X|

+--------+--------------+----------------+--------+--------+----------+

|GENDER  |     .35515          .22113828     1.606   .1083    .3943662|

|AGE     |    -.01294          .05868952     -.221   .8255   20.732394|

|PERIOD  |     .06909***       .02287902     3.020   .0025   5.5000000|

|TREAT_PR|     .01037          .20414538      .051   .9595    .4929577|

|TREAT_TR|     .34429*         .20105428     1.712   .0868    .5070423|

|Constant|    1.10060         1.23528145      .891   .3729            |

+--------+------------------------------------------------------------+

| Note: ***, **, * = Significance at 1%, 5%, 10% level.               |

+---------------------------------------------------------------------+

 

 

xtreg bet2lot5 gender age period treat_pr treat_tr, re

 

Random-effects GLS regression                   Number of obs      =
710

Group variable: id                              Number of groups   =
71

 

R-sq:  within  = 0.0876                         Obs per group: min =
10

       between = 0.0612                                        avg =
10.0

       overall = 0.0693                                        max =
10

 

Random effects u_i ~ Gaussian                   Wald chi2(5)       =
65.57

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

 

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

    bet2lot5 |      Coef.   Std. Err.      z    P>|z|     [95% Conf.
Interval]

-------------+--------------------------------------------------------------
--

      gender |   .3551551   .2502641     1.42   0.156    -.1353535
.8456638

         age |  -.0129431   .0767783    -0.17   0.866    -.1634259
.1375397

      period |   .0690943   .0088273     7.83   0.000      .051793
.0863956

    treat_pr |   .0103745   .2413856     0.04   0.966    -.4627327
.4834816

    treat_tr |   .3442994   .2429732     1.42   0.156    -.1319193
.820518

       _cons |   1.100601   1.635651     0.67   0.501    -2.105216
4.306418

-------------+--------------------------------------------------------------
--

     sigma_u |  .98865592

     sigma_e |  .67559506

         rho |  .68168039   (fraction of variance due to u_i)

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

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