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st: test difference in marginal effects for the same dummy variable, computed first as difference and then as derivative
From
Luca Fumarco <[email protected]>
To
"[email protected]" <[email protected]>
Subject
st: test difference in marginal effects for the same dummy variable, computed first as difference and then as derivative
Date
Mon, 4 Mar 2013 21:21:14 +0100
Dear statalisters,
I would like to test whether the difference between the marginal effects of a dummy varaible, obtained first by computing the difference
and then by taking the derivative, is statistically significant. I want to implement this test in order to justify the utilization of the derivative.
The model I am suing is the probit model; my vars are y x1 x2 x3, where x1 and x2 are the dummy variables.
Below you can read the syntax I am using.
1) First, I generate an identical dummy var, but with a different name.
gen x1bis = x1
2) Second, I regress the probit model, compute the marginal effect of x1 computing the difference, and I store the estimate
probit y i.x1 i.x2 x3, cluster(id)
margins, dydx(x1) atmeans post
matrix list e(b)
est store mfx1
estimate query
3) Third, I regress the probit model, compute the marginal effect of x1bis taking the derivatie, and I store the estimate
probit y i.x1bis i.x2 x3, cluster(id)
margins, dydx(x1bis) cont atmeans post
matrix list e(b)
est store mfx2
estimate query
4) Eventually, I test the difference
lincom _b[1.x1] - _b[1.x1bis]
Stata returns the following result:
------------------------------------------------------------------------------
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 0 (omitted) . . . .
------------------------------------------------------------------------------
As you see, I control with "estimate query" what I have actually stored and the corresponding values: _b[1.x1] and _b[1.x1bis] corresponds to the estimates
of the marginal effects computed in the two different ways, and their value is not the same.
Is there a syntax or (worse) a methodological problem in what I am doing?
Do you have any suggestion concerning a possible correction, or even concerning a different way to implement this test?
Thank you very much!
Luca
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