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Re: st: Maximum likelihood estimation

From   Joseph Monte <>
To   statalist <>
Subject   Re: st: Maximum likelihood estimation
Date   Wed, 13 Feb 2013 21:27:55 +0000

Dear Statalisters,

I'll try again with a little more info since I did not get any
responses. Here is the code I have so far (based on previous Statalist
posts and "Maximum Likelihood estimation with Stata" by
Gould, Pitbaldo and Poi, 4th ed.). The paper I cited in my first email
below models the log of the variance of the regression error in
equation 2 while I believe I have modelled the log of sigma. I would
preferably like to model the log of the variance as in the paper cited
but am not sure how.

  program mynormal_lf1
          version 12
                  args todo b lnfj g1 g2
          tempvar mu lnsigma sigma
                  mleval `mu' = `b', eq(1)
                  mleval `lnsigma' = `b', eq(2)
          quietly {
                                gen double `sigma' = exp(`lnsigma')
                                replace `lnfj' =
                                if (`todo'==0) exit
                                tempvar z
                                tempname dmu dlnsigma
                                gen double `z' = ($ML_y1-`mu')/`sigma'
                                replace `g1' = `z'/`sigma'
                                replace `g2' = `z'*`z'-1

ml model lf1 mynormal_lf1 (mu: y = x1 x2 x3 x4 x5 x6 x7 x8 x9)
(lnsigma: y = x1 x2 x3 x4 x5 x6 x7 x8 x9)
ml max



On Tue, Feb 12, 2013 at 9:54 AM, Joseph Monte <> wrote:
> Dear Statalisters,
> I need to do a maximum likelihood estimation very similar to that in
> equations (1) and (2) on page 439 of Lowry et al. (2010). Note that
> equation 2 has the same independent variables as equation 1. I would
> appreciate it if someone would let me know the code I need to use with
> the help of an example. I use Stata 12.
> References
> Lowry, M., Officer, M.S., Schwert, G.W., 2010. The variability of IPO
> initial returns. The Journal of Finance 65, 425-465
> Thanks,
> Joe
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