[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: RE: Tobit coefficients

From   <>
Subject   Re: st: RE: Tobit coefficients
Date   Thu, 26 Jul 2007 20:27:40 -0300 (ART)

Hi all,

I have a problem estimating predicted values that is
somehow related to the messages fro Lisa and May

I estimated I tobit model and I want E(y|x,y>0)
conditional on vector x on its mean values. After
reading the messages below I understand that the
following command gives me what I want:

mfx compute, predict(e(0,.))

(It also gives me the marginal effects, but I don't
need them)

My problem is that mfx does not give me the Standard
Error of E(y|x,y>0). And I need this.

I have tried the prvalue command. Simply typing
"prvalue", with no options", it gives me the predicted
value and a confidence interval, which would be
enough. But what prvalue estimate is E(y|x), and not

Does anyone know how to make prvalue estimate
E(y|x,y>0) after a Tobit model, rather than E(y|x)?

Or is there another way to do what I want?

Or am I getting it all wrong from the beginning and my
question makes no sense at all?!..

Thanks in advance,

----- Original Message -----
From: May Boggess <>
Subject: Re: st: RE: Tobit coefficients
Date: 03 Jan 2005 16:57:24 -0600

On Monday, Lisa wrote:
>  For the following command:
>  tobit facil4p $demo5, ll(0);
>  mfx compute,  predict(e(0,.));
>  does this give marginal effects in terms of
>  1) E(y|x,y>0)
>  OR
>  2) E(y|x) = P(y>0) * E(y|x,y>0)
>  If it is (1) (which I am pretty sure that it is)
could someone please
> tell me how to specify (2) in STATA.

It gives (1). Here is an example that shows how the
various predictions
available after -tobit- are calculated:

 sysuse auto 
 replace mpg=mpg-20
 tobit mpg len, ll(0)
 predict xb,xb
 predict y, ystar(0,.)  /*  Unconditional Expected
Value */
 predict e, e(0,.)      /*  Conditional on being
Uncensored */
 predict p, pr(0,.)     /*  Probability Uncensored */

 gen myy = p*e 
 sum y myy

 gen mye = xb + _b[_se]*normden((0-xb)/_b[_se])/p  
 sum e mye

 gen myp = norm(-((0-xb)/_b[_se])) 
 sum p myp

This shows that ystar is the function Lisa is looking
for in (2). That
means she can calculate the marginal effect, and its
standard error, as

 mfx, predict(ystar(0,.))


      Alertas do Yahoo! Mail em seu celular. Saiba mais em
*   For searches and help try:

© Copyright 1996–2017 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index