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st: probit - estimating mfx for different categorical variables


From   emmmasa <[email protected]>
To   [email protected]
Subject   st: probit - estimating mfx for different categorical variables
Date   Sat, 7 Apr 2007 06:44:12 -0700 (PDT)

Dear all:

I have a problem with generating the marginal effects
for a simple probit model.

I am looking at the effect of a range of factors upon
the probability of being poor. The independent
variables include a categorical variable denoting
educational level, as well as an area poverty variable
(continous).

I have calculated the mfx of area poverty upon the
predicted probability of individual poverty.

Now I would like to find out how this varies for
different education levels other than the mean.

I am using the following code:

gen AreaPov=_n+0 in 1/40
gen p_pov=.
forvalues i=0(1)40{

mfx, at (mean edgroup=1 Areapov = `i') var (Areapov)
replace p_pov=e(Xmfx_y) if Areapov==`i'
}

I have five educational groups - and upon calculating
the marginal effects using this code, I realized that
exactly the same results were generated for each
educational grouping.

There must be some problem with the code, but I can't
figure out what it is.

I'd be grateful for any advice.

Many thanks in advance.

best regards,
Emma


 
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