# st: Re: RE: RE: RE: time random effects

 From Giovanni Bruno <[email protected]> To [email protected] Subject st: Re: RE: RE: RE: time random effects Date Thu, 23 Jun 2005 16:24:31 +0200

```As Scott Merryman clearly suggested, -xtreg- can only estimate one-way
*random* effect models, with either time or cross-section heterogeneity.
-xtmixed-, however, can easily estimate the two-way random effect
panel data model.

As explained in [Baltagi (2005), Econometric analysis of panel data, ch. 3]
there are various ways to estimate the two-way random effect model in
econometrics. Using the Grunfeld's data set

<http://www.wiley.com/legacy/wileychi/baltagi3e/data_sets.html>

the following -xtmixed- instruction produces  estimates for parameters and
standard deviations that are identical to those reported in Baltagi's (2005)
Table 3.1 under the IMLE (iterated maximum likelihood estimator) method,
implemented by Baltagi using TSP (FN=firm index; YR=time index; I=investments;
F=value of the firm; K=capital stock):

. xtmixed I F K || _all: R.FN || _all: R.YR,mle

Performing EM optimization:

Iteration 0:   log likelihood = -1095.3809
Iteration 1:   log likelihood = -1095.2502
Iteration 2:   log likelihood = -1095.2485
Iteration 3:   log likelihood = -1095.2485

Computing standard errors:

Mixed-effects ML regression                     Number of obs      =       200
Group variable: _all                            Number of groups   =         1

Obs per group: min =       200
avg =     200.0
max =       200

Wald chi2(2)       =    661.07
Log likelihood = -1095.2485                     Prob > chi2        =    0.0000

------------------------------------------------------------------------------
I |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
F |   .1099009   .0103779    10.59   0.000     .0895606    .1302413
K |   .3092262   .0172179    17.96   0.000     .2754798    .3429726
_cons |  -58.27126   27.76275    -2.10   0.036    -112.6853   -3.857264
------------------------------------------------------------------------------

------------------------------------------------------------------------------
Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
_all: Identity               |
sd(R.FN) |   80.41164   18.42471       51.3196    125.9954
-----------------------------+------------------------------------------------
_all: Identity               |
sd(R.YR) |   3.860627   15.29474      .0016384    9096.692
-----------------------------+------------------------------------------------
sd(Residual) |   52.34756   2.904361       46.9537    58.36104
------------------------------------------------------------------------------
LR test vs. linear regression:       chi2(2) =   193.11   Prob > chi2 = 0.0000

Note: LR test is conservative and provided only for reference

Giovanni

Scrive Wanli Zhao <[email protected]>:

> Thank you, Scott. Without disrespect, I am still a little bit unsure about
> this. Several small points raise my concern. On the -help xtreg- page in
> Stata, on the bottom are some command examples and none of them show time
> random effects explicitly. Also, on the -findit xtreg- page, there is an
> example for chapter 14 of Greene's book. I checked it, the original text
> book chapter has two way effects in the table. On the Stata webpage for
> this, seems that it stops on the time random effects part. In addition,
> seems that when you do not specify i() in xtreg (but you specify panel tis
> beforehand) and estimate random effects, it means only the cross-section
> random effects, not both. I hope you could enlighten me. Just say you tried
> this before. :-)
>
> Wanli
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of Scott Merryman
> Sent: Wednesday, June 22, 2005 8:38 PM
> To: [email protected]
> Subject: st: RE: RE: time random effects
>
> If you want random time effects without cross section effects you can use
> -xtreg-.  Simply specify the "i(varname)" option with the time variable
> (i.e.  -xtreg depvar indepvar, i(time)-)
>
> For two-way random effects take a look at -xtmixed- or -gllamm-
>
> Scott
>
>
> > -----Original Message-----
> > From: [email protected] [mailto:owner-
> > [email protected]] On Behalf Of Wanli Zhao
> > Sent: Wednesday, June 22, 2005 3:52 PM
> > To: [email protected]
> > Subject: st: RE: time random effects
> >
> > I asked the same question before and stared at the list every day and
> > got no reply. I did some homework and found people say that Stata can
> > do the two-way effects panel model (error component model by another
> > name). I still cannot figure out how to do it in Stata. Adding time
> > dummies to do fixed effects is simple (with/without cross-section
> > effects). But how to do time random effects, with/without
> > cross-section effects? In the literature and text books, error
> > component model with time variation and cross-section variation is
> > just there. If you know how to do it in Stat, pls help.
> > Thanks
> > a lot.
> >
> > Wanli Zhao
> > Using Stata 9
> >
> >
> > *
> > *   For searches and help try:
> > *   http://www.stata.com/support/faqs/res/findit.html
> > *   http://www.stata.com/support/statalist/faq
> > *   http://www.ats.ucla.edu/stat/stata/
>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/support/faqs/res/findit.html
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/support/faqs/res/findit.html
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>

--
Giovanni Bruno
Istituto di Economia Politica, Universit� Bocconi
Via U. Gobbi, 5, 20136 Milano
Italy
tel. + 02 5836 5411
fax. + 02 5836 5438
*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/
```