# st: Re: RE: Re: RE: compute elasticity: Probit VS LPM

 From "Feng Liu" To Subject st: Re: RE: Re: RE: compute elasticity: Probit VS LPM Date Tue, 18 Apr 2006 13:38:13 -0400

```I have tested your example code. I can see that y is strongly affected by
x1. But I am not sure why that would make me to trust the mfx results from
Besides, my own method is based on Probit regression and the definition of
elasticity. I wonder how Stata compute elasticity after Probit?
d(logy)/d(logx)?

Thanks!

Feng

----- Original Message -----
From: "Maarten Buis" <M.Buis@fsw.vu.nl>
To: <statalist@hsphsun2.harvard.edu>
Sent: Tuesday, April 18, 2006 12:16 PM
Subject: st: RE: Re: RE: compute elasticity: Probit VS LPM

> Feng:
> What is causing the difference between linear approximations (OLS and your
method) and probit is the very strong effect of x1. One way to see this is
to look at the predicted probabilities for different values of x2 and x1,
which you can get by using -prgen- from -spost- and create a graph of the
predicted probability versus x2. You can also plot your linear approximation
using the -twoway function- command and compare the two. See example code
below. You can see that you have a very extreme example and that you should
not trust results from OLS in this case.
> HTH,
> Maarten
>
> *-----------begin example-------------
> cd h:\temp
> use teste.dta, clear
> probit y x1 x2
> prgen x2, x(x1=1) gen(x21)
> prgen x2, x(x1=0) gen(x20)
> reg y x1 x2
> twoway line x21p1 x20p1 x21x || /*
>   */ function y = _b[_cons] + _b[x1] + _b[x2]*x, range(1.3 3.7) || /*
>   */ function y = _b[_cons] + _b[x2]*x, range(1.3 3.7) /*
>   */ legend(label(1 "probit" "x1=1") label(2 "probit" "x1=0") /*
>   */        label(3 "OLS" "x1=1")    label(4 "OLS" "x1=0") )
> *----------------------end example--------------------------
>
>
> -----------------------------------------
> Maarten L. Buis
> Department of Social Research Methodology
> Vrije Universiteit Amsterdam
> Boelelaan 1081
> 1081 HV Amsterdam
> The Netherlands
>
> Buitenveldertselaan 3 (Metropolitan), room Z214
>
> +31 20 5986715
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Feng Liu
> Sent: dinsdag 18 april 2006 17:44
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Re: RE: compute elasticity: Probit VS LPM
>
> Usually I use Probit or Logit instaed of LPM. This time I guess the
> elasticity from mfx,eyex after Probit might be wrong, so I tried LPM. Is
> there a way to verify which one is right?
> What I tried is:
> after Probit regression,
> .predict p0
> .replace x2=x2*1.1
> .predict p1
> Then I compare p0 and p1 and find it fell by 3%. This implies the
elasticity
> is -0.3, which is close to the one from LPM.
>
>
>
> *
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> *   http://www.ats.ucla.edu/stat/stata/

*
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```