Re: st: information criterions after -xtreg, re-

[Alfonso Sanchez-Penalver <alfonso.statalist@gmail.com>]

Hi Filippo,

If you want to estimate random effects -xtreg, mle- does that using maximum likelihood. -xtreg, re- uses feasible GLS to do the random effects estimation. In many cases the maximum likelihood is more efficient and iterated FGLS converges to the maximum likelihood estimate. I say many cases because this doesn't always hold. So if you're interested in a comparison criterion for different random effects models you can always estimate them with -mle- and use AIC. You can always check how close your estimates of the coefficients are between a -re-and an -mle- estimation by running both.

Best,

Alfonso Sanchez-Penalver

> On Jan 22, 2014, at 5:40 AM, "Filippo Maria D'Arcangelo" <filippo.darcangelo@unibocconi.it> wrote:
> 
> Dear statlisters,
> 
> I have a panel dataset and I am running a set of regressions.
> They are "nested", in the sense of Wooldridge(2005), i.e. the covariates varies incrementally from a simpler model to a more "rich" one.
> For this purpose, I am using -xtreg, re-, assuming random effects toward the panel groups.
> I want to compare the regressions, using some sort of (not too fancy) criterion.
> 
> I know that a useful criterion could be Akaike's Information Criterion (AIC). I am also aware that there are a few alternatives, mostly relying on Kullback–Leibler divergence, which in turns (to the extent of my limited knowledge) relies on a likelihood calculation.  
> 
> However, -xtreg, re- does not store any likelihood measure (and therefore, no AIC). 
> Other options of -xtreg- do have this feature (e.g. [, fe] and definitely [, mle]).
> Is there any theoretical reason for the likelihood not to be calculated after a random effect regression?
> 
> Should I use something different instead, such as a goodness-to-fit criterion, i.e. adjusted-R^2? If yes, does anybody of you knows how to correct determine this parameter (adj-R^2) for panel data?
> Thank you,
> 
> 
> Filippo Maria D'Arcangelo
> 
> 
> Reference: Wooldridge, Jeffrey M. (2005) "Introductory Econometrics. A Modern Approach". p. 193
> 
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