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Re: st: Multivariate Poisson - Correlation of Error Terms

From   "Joseph Coveney" <>
To   "Statalist" <>
Subject   Re: st: Multivariate Poisson - Correlation of Error Terms
Date   Wed, 9 Jul 2008 11:37:35 +0900

U.G. Narloch wrote (excerpted):

I have the following model:

y1 =   X’ β1 + Z1’ γ1 + ε1
y2  = X’ β2 + Z2’ γ2 + ε2
y3  = X’ β3 + Z3’ γ3 + ε3
y4 = X’ β4 + Z4’ γ4 + ε4.

The dependent variables are count variables and X is a vector of explaining
variables that is identical in each equation whereas Z includes
equation-specific variables that differ from equation to equation.

I assume that the four count processes are related to one another, so that
the disturbance terms should be correlated. To estimate these four
equations in a multivariate model I follow the approach suggested at:

First, I estimate each Poisson regressions separately and second I combine
these results in a joint model via a Seemingly Unrelated Estimation
(SUEST). Having done this, I would like to test if the error terms are
really correlated, so that the count regressions cannot be estimated
independent from each other.



My understanding is that combining the separate equations with -suest- isn't
really the same as simulatneously fitting them, and so it doesn't seem that
you could estimate multivariate correlation of error terms with -suest- as
if for a jointly fit set of equations.

For this, you'd probably have to go the route that Stas Kolenikov suggested
in the second post that you cite, viz., -gllammm-.

The set of equations looks as if you could recast them and use -gllamm- in
the manner as for structural equations modeling with count or categorical
variables.  As I recall, the -gllamm- user manual ( or the
U.C. Berkeley website) can help you set things up with this approach.  The
authors also have a book* that's available from StataCorp's online

Joseph Coveney

*A. Skrondal & S. Rabe-Hesketh, _Generalized Latent Variable Modeling.
Multilevel, Longitudinal, and Structural Equation Models_. (Boca Raton,
Fla.: Chapman & Hall/CRC, 2004).

*   For searches and help try:

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