Thank you Scott for your help. It seems that the relation between the
marginal effects of the unconditional expected value and the latent variable
is the same for all the variables, including the constant. I will see if
papers include the constant when they report marginal effects of the
unconditional expected value and the interpretation.
Sincerely,
Marina Balboa
----- Original Message -----
From: "Scott Merryman" <[email protected]>
To: <[email protected]>
Sent: Friday, July 25, 2003 3:44 AM
Subject: st: Re: Re: Re: marginal effects
> ----- Original Message -----
> From: "Marina.Balboa" <[email protected]>
> To: <[email protected]>
> Sent: Thursday, July 24, 2003 3:20 AM
> Subject: st: Re: Re: marginal effects
>
>
> > 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 t
his.
> > Sincerely,
> > Marina Balboa
> >
>
> This procedures seems to generate the same coefficient for the constant
that one
> would get after -dtobit- , but I am unsure of the interpretation of the
marginal
> effects of a constant.
>
>
> Scott
>
>
> . clear
>
> . use "C:\Stata8\auto.dta", clear
> (1978 Automobile Data)
>
> . replace price = 4000 if price <4000
> (11 real changes made)
>
> . qui tobit price mpg, ll(4000)
>
> . dtobit
>
> Marginal Effects: Latent Variable
> --------------------------------------------------------------------------
----
> variable | dF/dx Std. Err. z P>|z| X_at [ 95%
I. ]
> ---------+----------------------------------------------------------------
----
> mpg | -293.3453 60.82228 -4.82 0.000
21.2973 -412.555 -174.136
> _cons | 12125.15 1316.403 9.21 0.000 1 9545.05
14705.3
> --------------------------------------------------------------------------
----
>
> Marginal Effects: Unconditional Expected Value
> --------------------------------------------------------------------------
----
> variable | dF/dx Std. Err. z P>|z| X_at [ 95%
I. ]
> ---------+----------------------------------------------------------------
----
> mpg | -218.8408 45.37451 -4.82 0.000
21.2973 -307.773 -129.908
> _cons | 9045.577 982.0601 9.21 0.000 1 7120.77
10970.4
> --------------------------------------------------------------------------
----
>
> Marginal Effects: Conditional on being Uncensored
> --------------------------------------------------------------------------
----
> variable | dF/dx Std. Err. z P>|z| X_at [ 95%
I. ]
> ---------+----------------------------------------------------------------
----
> mpg | -155.8101 32.30571 -4.82 0.000
21.2973 -219.128 -92.4921
> _cons | 6440.265 699.2065 9.21 0.000 1 5069.84
7810.68
> --------------------------------------------------------------------------
----
>
> Marginal Effects: Probability Uncensored
> --------------------------------------------------------------------------
----
> variable | dF/dx Std. Err. z P>|z| X_at [ 95%
I. ]
> ---------+----------------------------------------------------------------
----
> mpg | -.0331409 .0068714 -4.82 0.000
21.2973 -.046609 -.019673
> _cons | 1.369848 .1487217 9.21 0.000 1 1.07836
1.66134
> --------------------------------------------------------------------------
----
>
>
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