May I please kindly ask how can I derive the inverse Mills ratio from a heteroscedastic probit model (estimated using the command hetprobit)? I will be using it for the second stage estimation of a wage model.
Code:
hetprobit h800job_2 g702age g702age_2 i.b202sex_2 i.partner i.h812recv_2 child_bmov i.relgn_christ, het(g702age i.b202sex_2 i.partner) vce(robust)
HTML Code:
Heteroskedastic probit model Number of obs = 3,167 Zero outcomes = 1,489 Nonzero outcomes = 1,678 Wald chi2(7) = 36.35 Log pseudolikelihood = -1756.303 Prob > chi2 = 0.0000 -------------------------------------------------------------------------------- | Robust h800job_2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---------------+---------------------------------------------------------------- h800job_2 | g702age | .334209 .0642149 5.20 0.000 .2083502 .4600679 g702age_2 | -.0041946 .000836 -5.02 0.000 -.0058331 -.0025562 1.b202sex_2 | -1.954624 .3479778 -5.62 0.000 -2.636648 -1.2726 1.partner | -.0644116 .1065569 -0.60 0.546 -.2732594 .1444361 1.h812recv_2 | -.4597904 .1403239 -3.28 0.001 -.7348202 -.1847605 child_bmov | .0350233 .0520128 0.67 0.501 -.0669199 .1369665 1.relgn_christ | .2872648 .1473732 1.95 0.051 -.0015813 .5761108 _cons | -4.805648 .9846948 -4.88 0.000 -6.735615 -2.875682 ---------------+---------------------------------------------------------------- lnsigma2 | g702age | .0170492 .0040073 4.25 0.000 .009195 .0249034 1.b202sex_2 | .6008698 .1568638 3.83 0.000 .2934223 .9083172 1.partner | -.3166569 .0864646 -3.66 0.000 -.4861245 -.1471893 -------------------------------------------------------------------------------- Wald test of lnsigma2=0: chi2(3) = 42.92 Prob > chi2 = 0.0000
Code:
predict phat, xb gen imr = normalden(phat)/normal(phat)
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