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st: three level variance components using xtmixed


From   "Huseyin Tastan" <hntastan@hotmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: three level variance components using xtmixed
Date   Wed, 16 Aug 2006 05:36:16 -0400

Hi all,

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

This assumes that year is nested within firms and firm is nested within industries. Hence, when one changes the nesting structure variance estimates dramatically change. I also tried the following model which takes the data as one big group:

xtmixed y || _all: R.industry || _all: R.firm || _all: R.years

Is there another way to estimate these four variance components in STATA using xtmixed or some other routine?

I thank you all in advance for your help.


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