Re: st: three level variance components using xtmixed

["Huseyin Tastan" <hntastan@hotmail.com>]

No, I do not have multiple measurements per year. The reason for considering 
time (year) is that it captures some macroeconomic events affecting all 
firms in all industries. I want to get how much of the variation in the 
dependent variable is due to firm, industry and time affects. I can run the 
model with two levels for each year and compare the results but I want to 
know if time effect is important or not.


> From: Joseph Coveney <jcoveney@bigplanet.com>
> Reply-To: statalist@hsphsun2.harvard.edu
> To: Statalist <statalist@hsphsun2.harvard.edu>
> Subject: Re: st: three level variance components using xtmixed
> Date: Wed, 16 Aug 2006 19:23:36 +0900
>
> Huseyin Tastan wrote:
>
> I want to analyze variance components of a measure of firm performance 
> (such
> as return on equity) using random effects at three levels: industry level,
> firm level and time level.
>
> I have data on
>
> industries: i=1,2,...,20 (there are 20 industries)
>
> firms: j=1,2,...,1000 (there are 1000 firms)
>
> and
>
> years: t=1,2,...,10 (there are 10 years)
>
> The specific model is written as follows:
>
> y_ijt = a + b_i + c_j + d_t + e_ijt
>
> There are four variances to estimate in this model:
>
> var(y) = var(b) + var(c) + var(d) + var(e)
>
> I have tried xtmixed to estimate this model but the convergence was
> extremely slow (I used reml option). And for some dependent variables it
> didnt even converge. The command I used was something like this:
>
> xtmixed y || industry: || firm: || year:, variance
>
> [excerpted]
>
> --------------------------------------------------------------------------------
>
> From the description, it looks as if there are only two variance components
> above the residuals.
>
> y_ijt = mu + industry_i + firm_ij + e_ijt
>
> Try -xtmixed y || industry: || firm:, variance-.
>
> Do you have multiple measurements per year?  Is there a reason to consider
> time as random?
>
> Joseph Coveney
>
>
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