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Re: st: Obtaining marginal effects and their standard errors after estimations with interactions


From   Richard Williams <richardwilliams.ndu@gmail.com>
To   statalist@hsphsun2.harvard.edu, <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Obtaining marginal effects and their standard errors after estimations with interactions
Date   Fri, 04 Jan 2013 09:32:25 -0500

At 03:17 PM 1/3/2013, Ebru Ozturk wrote:

Dear All,

On Stata FAQs' page, there are some given examples for Probit estimation with interaction effects for Stata 10 titled as "I am using a model with interactions. How can I obtain marginal effects and their standard errors?" and the link is: http://www.stata.com/support/faqs/statistics/marginal-effects-after-interactions/

Do you think this way is still applicable to Probit estimation? and Is the below command correct when we have other independent or control variables?

I don't know if you did it right or not, but if you have Stata 11 or higher why not use -margins-, e.g.

sysuse auto, clear
probit foreign weight length c.weight#c.length, nolog
margins, dydx(*)

local xb _b[weight]*`meanwei' + _b[len]*`meanlen' + _b[wl]*`meanwei'*`meanlen' + _b[C1]*C1+_b[C2]*C2 + _b[_cons] // if more variables //

/////// example /////////

sysuse auto, clear
generate wl=weight*length
probit foreign weight length wl, nolog
quietly summarize weight if e(sample)
local meanwei = r(mean)
quietly summarize length if e(sample)
local meanlen = r(mean)

local xb _b[weight]*`meanwei' + _b[len]*`meanlen' + _b[wl]*`meanwei'*`meanlen' + _b[_cons]
predictnl dydw =  normalden(`xb')*(_b[weight]+ _b[wl]*`meanlen') in 1, se(sew)
list dydw sew in 1

predictnl dydl = normalden(`xb')*(_b[len]+ _b[wl]*`meanwei') in 1, se(sel)
list dydl sel in 1

predictnl dydlw =normalden(`xb')*(-(`xb'))*(_b[weight]+ _b[wl]*`meanlen')*(_b[len]+ _b[wl]*`meanwei') + normalden(`xb')*( _b[wl]) in 1, se(selw)
list dydlw selw in 1

Ebru

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Richard Williams, Notre Dame Dept of Sociology
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