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  • How to compute for inverse Mills ratio from a heteroscedastic probit model

    Good day!

    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)
    Shown below is the results of the command:
    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
    Initially, I used the following commands but later realized that I might be treating it as if it's a homoscedastic probit model:
    Code:
    predict phat, xb
    gen imr = normalden(phat)/normal(phat)
    Thank you very much!
    Last edited by Emman Barnedo; 28 Dec 2020, 23:15.
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