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st: Trouble with ml init and convergence


From   Dana Chandler <[email protected]>
To   [email protected]
Subject   st: Trouble with ml init and convergence
Date   Wed, 10 Mar 2010 19:11:43 -0600

Hi fellow statalisters -

I am working with an ordered probit that is having difficulty
converging. I don't have that much experience with maximum likelihood
estimators in Stata and think I'm probably missing something obvious.
I would greatly appreciate any help or insights that you guys have.

I wrote once before when the canned oprobit command wasn't converging
(http://www.stata.com/statalist/archive/2010-01/msg00631.html). Since
then, I have figured out how to program an ordered probit using ml lf
thanks to comments from helpful statalisters and Gould's Stata MLE
book. However, I still can't figure out how to get my function to
converge.

I'm estimating a model where I have a cross-section that includes the
population and the number of religious organizations within several
hundred towns. Each town has 0 to 5 organizations (top-coded) and I'd
like to estimate an ordered probit where the outcome is the number of
religious organizations and the predictors are population or some
transformation of the population variable.

In the simplest model, I estimate "oprobit outcome pop". This works
fine. However, for another specification, I want to allow population
to have a differing effect on the outcome variable depending on how
many organizations are already in the town. Hence, I create dummies
pop_w0-pop_w5 where I calculate DUMMY(outcome>=N)*pop. Next, I
estimate "oprobit outcome pop pop_w1 pop_w2 pop_w3 pop_w4 pop_w5".
This DOESN'T work which is why I start to use the oprobit that I
programmed with ml lf where hopefully I can set initial values to help
it converge. Unfortunately, I'm still having trouble with that.

I have attached a link to a stata dataset and example do file that
explain the methodology
(http://www.4shared.com/dir/33394700/3eb89ce2/statalist.html). I
haven't had any luck setting initial values and would greatly
appreciate anyone's suggestions.

Thanks everyone,
Dana
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