Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: margeff and margins puzzle
From
Richard Williams <[email protected]>
To
[email protected], [email protected]
Subject
Re: st: margeff and margins puzzle
Date
Thu, 28 Jul 2011 21:11:41 -0500
At 06:35 PM 7/28/2011, Patrick Roland wrote:
Hi all,
Here's a piece of code which gives peculiar results. It's a simple probit.
"margeff" calculates the marginal effect to be exactly zero, whereas margins
(correctly) doesn't. The really puzzling thing is that if "set obs 1000" is
changed to "set obs 100", they give identical results, as they should!
Anyone have any idea what might be going on here?
set seed 1
set obs 1000
gen x0 = -.25
gen x1 = runiform()
gen eps = rnormal()
gen y = x0+x1+eps > 0
probit y x1
margeff
margins, dydx(*)
I get identical results with both commands. As always, make sure you
have the latest versions of everything and try again.
. set seed 1
. set obs 1000
obs was 0, now 1000
. gen x0 = -.25
. gen x1 = runiform()
. gen eps = rnormal()
. gen y = x0+x1+eps > 0
. probit y x1
Iteration 0: log likelihood = -669.63431
Iteration 1: log likelihood = -637.00519
Iteration 2: log likelihood = -636.94994
Iteration 3: log likelihood = -636.94994
Probit regression Number of obs = 1000
LR chi2(1) = 65.37
Prob > chi2 = 0.0000
Log likelihood = -636.94994 Pseudo R2 = 0.0488
------------------------------------------------------------------------------
y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | 1.133848 .1423649 7.96 0.000 .8548182 1.412878
_cons | -.2788769 .0797004 -3.50 0.000 -.4350869 -.122667
------------------------------------------------------------------------------
. margeff
Average partial effects after probit
y = Pr(y)
------------------------------------------------------------------------------
variable | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | .4126165 .0466284 8.85 0.000 .3212265 .5040065
------------------------------------------------------------------------------
.
. margins, dydx(*)
Average marginal effects Number of obs = 1000
Model VCE : OIM
Expression : Pr(y), predict()
dy/dx w.r.t. : x1
------------------------------------------------------------------------------
| Delta-method
| dy/dx Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | .4126127 .0466285 8.85 0.000 .3212225 .5040028
------------------------------------------------------------------------------
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: [email protected]
WWW: http://www.nd.edu/~rwilliam
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/