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# Re: st: testing the joint significance

 From Maarten buis <[email protected]> To [email protected] Subject Re: st: testing the joint significance Date Tue, 11 Jan 2011 09:56:18 +0000 (GMT)

```--- On Tue, 11/1/11, Nirina F wrote:
> I would like to see the effect of being married on lw.
>
> The married variable dummy is "mrt"
>
> I will multiply all the variables with the "mrt" dummy and
> then I would like to test the joint significance of the
> main slope and intercept. I know how to test the joint
> significance of the variables but I don't know how to do
> the joint significance of the main slope and intercept.

Taking the question literaly, then the answer is just using
-test- for the main effect and the interactions. In that
case it can be useful/convenient to use the new factor
variable notation (and the -coeflegend- option to find out
how these coefficients are called):

*----------------------- begin example -----------------------
use http://fmwww.bc.edu/ec-p/data/hayashi/griliches76.dta
reg  lw i.mrt##(c.s c.expr c.tenure i.rns i.smsa c.iq), coefl
test 1.mrt        ///
1.mrt#c.s    ///
1.mrt#c.expr ///
1.mrt#1.rns  ///
1.mrt#1.smsa ///
1.mrt#c.iq
*----------------------- end example -------------------------
(For more on examples I sent to the Statalist see:
http://www.maartenbuis.nl/example_faq )

If you look at the effect of married by also including the
interactions between married and the other variables then you
are probably interested in doing an Blinder-Oaxaca decomposition:

Ben Jann (2008) "The Blinder–Oaxaca decomposition for linear
regression models" The Stata Journal, 8(4):453-479.
<http://www.stata-journal.com/article.html?article=st0151>

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://www.maartenbuis.nl
--------------------------

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```