Dear all,

I am struggling to compute the average marginal effects using a Tobit allowing for heteroskedasticity. Any suggestions on this will be highly appreciated.

My dependent variable is a continuous variable that takes nonnegative values only when observations in my data violated some economic assumptions. Otherwise, it is zero (54% of the sample). This variable measures the amount of budget that can be extracted from an individual who violated those assumptions. Hence, I think a Tobit model would be suitable.

I conducted a Likelihood-ratio test, which rejected the null of homoskedasticity.

Therefore, I am running the following heteroskedastic Tobit:

Code:
capture program drop het_tob
program define het_tob
   qui {
    args lnf XB WA
    replace `lnf' = -0.5*(ln(2*_pi)+ln(exp(`WA')^2)+(($ML_y1-`XB')^2/exp(`WA')^2)) if $ML_y1>0 & $ML_y1!=.
    replace `lnf' = ln(1-normprob(`XB'/exp(`WA'))) if $ML_y1<=0
    }
    end

ml model lf het_tob (Tobit: MPImax = crtstd age_years age2) (Tobhet: crtstd age_years age2), title(Tobit with Heteroscedasticity)

ml maximize,  difficult nolog

Tobit with Heteroscedasticity                   Number of obs     =        205
                                                Wald chi2(3)      =      11.79
Log likelihood = -64.449366                     Prob > chi2       =     0.0081

------------------------------------------------------------------------------
      MPImax |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Tobit        |
      crtstd |  -.0448083    .021168    -2.12   0.034    -.0862968   -.0033199
   age_years |  -.0160767   .0066348    -2.42   0.015    -.0290807   -.0030726
        age2 |   .0002018   .0000952     2.12   0.034     .0000153    .0003883
       _cons |   .2392886   .1001342     2.39   0.017     .0430292    .4355481
-------------+----------------------------------------------------------------
Tobhet       |
      crtstd |   .1956093   .0843663     2.32   0.020     .0302543    .3609642
   age_years |   .0084042    .025229     0.33   0.739    -.0410436    .0578521
        age2 |    .000042   .0003784     0.11   0.912    -.0006997    .0007838
       _cons |  -1.757924   .3580635    -4.91   0.000    -2.459716   -1.056133
------------------------------------------------------------------------------
I would like to compute the average marginal effects of the variable "crtstd" and its significance. I think I am missing some relevant option while using the margins command since once I ran it I obtained the estimated coefficient of "crtstd":

Code:
margins, dydx(crtstd)

Average marginal effects                        Number of obs     =        205
Model VCE    : OIM

Expression   : Linear prediction, predict()
dy/dx w.r.t. : crtstd

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      crtstd |  -.0448083    .021168    -2.12   0.034    -.0862968   -.0033199
------------------------------------------------------------------------------

I appreciate any advice on this.

Thanks!
Gastón