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Re: st: RE: RE: Count data regression


From   Scott Cunningham <scunning@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: RE: Count data regression
Date   Thu, 23 Mar 2006 12:13:02 -0500

On Mar 23, 2006, at 12:00 PM, Rajesh Tharyan wrote:

Hi scott,

Re your reply to hugh..

2. For the Poisson MLE, valid inference requires equality of the conditional
mean and variance (equidispersion) - it does not require that the dependent
variable have a Poisson distribution.

I didn't get point two.. my impression was that it is the distribution of
the underlying variable which sort of dictated whether you used a poisson
regression or a nb regression..etc. but of course with a poission
distributed variable you always have mean=variance..
(Different Scott talking now).

When you don't have equidispersion, you lose precision in your estimates, but you don't lose consistency. So the Poisson is still consistent even if the conditional mean does not equal the conditional variance. Thankfully, there are ways to correct the standard errors for overdispersion. See the -poisson, robust- option and the -xtpoisson, vce(boot)-. I don't have my Cameron and Trivedi MICROECONOMETRICS handy, but if you look in there, they talk about this correct procedure, and I think -poisson, robust- does this. -sc

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