Thank you Scott very much for your helpful explanation. Just one question,
please. What about the constant? If I want to report the results of
mfx compute, predict(ys(0,.))
Does not the model on the observed variable y have a constant, like the
model with the latent variable?
Or does it have a constant that I may infer like this (using your example):
> . xttobit price mpg, ll(4000) i(foreign) nolog
>
> Random-effects tobit regression Number of obs =
74
> Group variable (i): foreign Number of groups =
2
>
> Random effects u_i ~ Gaussian Obs per group: min =
22
> avg =
37.0
> max =
52
>
> Wald chi2(1) =
25.39
> Log likelihood = -597.93768 Prob > chi2 =
0.0000
>
> --------------------------------------------------------------------------
----
> price | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
> -------------+------------------------------------------------------------
----
> mpg | -327.9141 65.0826 -5.04
0.000 -455.4736 -200.3545
> _cons | 13099.53 1578.574 8.30 0.000 10005.58
16193.48
> -------------+------------------------------------------------------------
----
> /sigma_u | 707.8464 527.0417 1.34 0.179 -325.1364
1740.829
> /sigma_e | 2762.649 252.5473 10.94 0.000 2267.665
3257.632
> -------------+------------------------------------------------------------
----
> rho | .0616045 .0871224 .0016116
.4454072
> --------------------------------------------------------------------------
----
>
> Observation summary: 63 uncensored observations
> 11 left-censored observations
> 0 right-censored observations
>
> . mfx compute, nose predict(ys(4000,.))
>
> Marginal effects after xttobit
> y = E(price*|price>4000) (predict, ys(4000,.))
> = 6495.1777
> --------------------------------------------------------------------------
-----
> variable | dy/dx X
> ---------------------------------+----------------------------------------
-----
> mpg | -252.7986 21.2973
> --------------------------------------------------------------------------
-----
>
> . ****The marginal effects for the unconditional expected value of y
>
> .
>
>
> Hope this helps,
> Scott
the relation between the mpg coefficients is: -252.7986/-327.9141=0.7709
the constant of the model that I'm interested in is:
13099.53*0.7709=10099
Thank you very much for your help and any hint you could give me about this.
Sincerely,
Marina Balboa
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
