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I've not really thought through your code in detail, but
-1-normal(`x')- can often cause numerical problems. Replacing it with
-normal(-`x')- may help.
Glenn.
"Vincent, David" <[email protected]> wrote:
I would be most grateful if someone could advise me how to code method
lf for evaluating the log-likelihood function for the Heckman model. I
need to compute the MLE's for a range of sample selection type models
(options not available in STATA) and being new to programming, wanted
to start off with this well known model. The latent variable
specifications are:
yi*=x1i'b1+e1 (coded $ML_y1)
ti*=x2i'b2+e2 (coded $ML_y2)
And the code I have written is:
program dv2mle_lf
args lnf theta1 theta2 sd2 rho
tempvar A B C D
quietly {
gen double `A'=ln(1-normal(`theta1'))
gen double `B'=`theta1'-`rho'*(1/`sd2')*($ML_y2-`theta2')
gen double `C'=sqrt(1-`rho'^2)
gen double `D'=ln(normalden(($ML_y2-`theta2')/`sd2'))
replace `lnf'=(1-$ML_y1)*`A'+$ML_y1*ln(normal(`B'/`C'))-$ML_y1*ln(`sd2')+$ML_y1*`D'
}
end
When I type: ml model lf dv2mle_lf (theta1: y t = x1 x2 x3) (x1 x2)
() () STATA reports that the log likelihood = infinity and cannot be
evaluated. Any help would be gratefully appreciated!
Many thanks,
David.
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