----- 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 this.
> 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% C.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% C.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% C.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% C.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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