[Limdep Nlogit List] Model opinion

[Wells, Aaron]

Good morning all,

If possible, I would like to assess the scholastic opinion of those on
the listserv regarding the following issue:

I am modeling the change in medical expenditures (logged) between two
periods for 7296 individuals.  Of the 14592 observations represented by
these individuals, 6% are equal to zero; the remaining observations are
normally distributed.  To model medical expenditures over the two
periods, I have considered a random effects linear regression model, a
tobit model (limit=0), a truncated model (all expenditures > 0) and a
Heckman model.  Ideally, I would like a linear regression counterpart to
the hurdle or ZIP model for count data, though I am not sure what that
model is (the Heckman model seems to imply, from a theoretical
perspective, that there is a selection bias to be modeled, which I do
not believe is the case for whether an individual is observed as having
y = 0 or y > 0).  Does anyone have a thought on whether these options
sound legitimate, or, whether one is most appropriate?

Thank you sincerely,

Aaron


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