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st: Log Likelihood for Linear Regression Models

From   leechtcn <[email protected]>
To   [email protected]
Subject   st: Log Likelihood for Linear Regression Models
Date   Thu, 30 Oct 2003 03:42:40 -0800 (PST)

Dear Listers,

I have asked this question before. I am posting it a
second time in case you guys have not received it.

I am sorry for the all convinence caused!

I have a question concerning William Gould and William
Sribney's "MAximium Likelihood Estimation" (1st

In its 29th page, the author write the the following

   For instance, most people would write the log
likelihood for the linear regression model as:

  LnL = SUM(Ln(Normden((yi-xi*beta)/sigma)))-ln(sigma)

But in most econometrics textbooks, such as William
Green, the log likelihood for a linear regression is

  LnL = SUM(Ln(Normden((yi-xi*beta)/sigma)))          

that is, the last item is dropped

I have also tried to use (2) in stata, it will give
"no concave" error message. In my Monte Carlo
experiments, (1) always gives reasonable results.

Can somebody tell me why there is a difference between
stata's log likelihood and those of the other

thanks a lot


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