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st: negative binomial models with large fixed effect group size
Hi Statalist,
1) I am having trouble making sense of the best route to take regarding
fixed effects and negative binomial regression. I have approximately 5,000
individuals with an average of 10 observations each that I would like to
obtain fixed effects estimates (within-individuals) for in a negative
binomial regression. I've read the "xtnbreg, fe" does not perform a
conventional individual fixed effects estimator, but that I can obtain what
I am looking for by running nbreg with dummy variables for each individual
and then correcting the standard errors afterwards. The problem is that it
is challenging, if not realistically impossible, time-wise, to run these
models with 5,000 dummy variables. Does anyone know of an alternative way
to achieve this goal (in Stata, or even another package)?
2) In addition, if I were to run nbreg with dummy variables for the fixed
effects, how does one interpret time-invariant independent variables in
models? I realize that in theory time-invariant variables and fixed
effects don't make sense, but in the few test models I have run (with
smaller subsets of the dataset and using reg instead of nbreg) running
"reg" with fixed effect dummy variables produces the same coefficients as
"xtreg" for the time-variant variables, but "xtreg" drops the
time-invariant one (expected) and "reg" does not. What, then, is the
meaning of the "reg" output for time-invariant variables when individual
dummies have been included in the model?
Thanks very much for your assistance!
KW
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