st: probit with interaction dummies (significance and marginal effects)

[Andrea Bennett <mac.stata@gmail.com>]

Dear all,

I am a little confused after reading multiple posts from the Statalist  
how I can make sure I do interpret interaction dummies correctly when  
using a probit estimation. For example I would like to estimate - 
male*low_education-, -male*mid_education- and -male*high_education- in  
a probit model. But, in this article posted on Statalist (http://www.stata.com/statalist/archive/2005-07/msg00559.html 
) it says that "surprisingly, the sign may be different for difierent  
observations. The statistical significance cannot be determined from  
the z-statistic reported in the regression output." Does this really  
mean that even if the interaction dummy shows a P-value of "0.000" I  
cannot take it for being significant?
The authors then state that one should instead use -inteff- for these  
kind of tests. But another article on the Statalist (http://www.stata.com/statalist/archive/2008-03/msg00549.html 
) says that -inteff- cannot do interactions like the one above and  
refers back to -mfx- or -margeff-.

So, if anyone knows an easy to understand procedure how I can tell  
that an interaction dummy in a probit estimation is significant and  
additionally how I can compute marginal effects for it, that would be  
great. I'm rather new to probit estimations, so solid but not all too  
fancy solutions would be preferred (if there are any).

Many thanks for your considerations,

Andrea
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