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st: xtpoisson, fe marginal effects interpretation


From   john sanders <desmochada@gmail.com>
To   statalist <statalist@hsphsun2.harvard.edu>
Subject   st: xtpoisson, fe marginal effects interpretation
Date   Tue, 3 May 2011 13:52:35 -0400

Hi Everyone,

I am estimating a count data model with fixed effects, trying to look
at how events (i.e. the count variable) across geographic areas (i.e.
the level of observation) are related to a continuous variable (the
regressor).

I first xtset the data:
"xtset geography time"

I run the following command:
"xtpoisson events continuous_variable + controls, fe"

which gives me regression estimates. I then use the postestimation command
"margins, nu0"

which should give the marginal effects under the assumption that the
multiplicative fixed effect is equal to 1. This strikes me as a bit
strange, as I am used to a linear model where the fixed effect is
additive, essentially shifting the intercept, and where we would not
think that a fixed effect equal to 0 (or log(1)) makes any a priori
sense.

The further issue is that I have no idea how to intepret the
estimates. Are these counts or rates? Looking at the documentation (as
well as Cameron and Trivedi's STATA book) would suggest they are
counts (i.e. dy/dx = Beta*E(Y|x,controls,fixed effect)), but I always
thought of Poisson estimates as being equivalent to rates.

Lastly, since each of these geographic units are of a different
population size, I want my coefficient estimates to reflect this. In a
linear probability world, I would simply use aweight, but this is not
possible using xtpoisson, fe.

Any and all help is greatly appreciated.

Best,

John Sanders

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