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Re: st: Interpreting triple interactions


From   Erasmo Giambona <[email protected]>
To   [email protected]
Subject   Re: st: Interpreting triple interactions
Date   Fri, 10 Sep 2010 00:12:44 +0200

Hi Phil,

This was really helpful. Thanks a lot,

Erasmo

On Wed, Sep 8, 2010 at 5:12 PM, Philip Ender <[email protected]> wrote:
> Erasmo Giambona <[email protected]> wrote:
>
> I am using panel data to estimate an Investment model. On the
> right-hand-side, I have a triple interaction term involving 3 dummy
> variables. Namely, whether the firm is Small (S), whether the firm is
> European (E), and finally wether New Accounting (NA)standards are in
> place. The regression also includes all the individual dummies as well
> as their pairwise interactions. 7 regressors in total. My variable of
> interest is the triple interaction, which essentially is a
> difference-in-difference-in-differences estimator. The triple
> interaction (S*E*NA)enters the regression with a positively
> significant coefficient.
>
> I am having hard time interpreting this result. Does the positive
> triple interaction mean that Small, European firms, after New
> Accounting standards are investing more than Small European firms
> prior to the New Accounting standards?
>
> Can somebody provide some help including some good reference if available?
>
> -------------------
>
> Dear Erasmo-
>
> One way of looking at this interaction is that there is a 2-way
> interaction that differs for each level of the third variable.  A good
> starting point is to get your eight cell means and try graphing them
> in various combinations.  You didn't mention which version of Stata
> that you use so below there are links for both Stata 11 and earlier.
>
> If you have Stata 11, you might find this page helpful:
>
> http://www.ats.ucla.edu/stat/stata/faq/margins_3way.htm
>
> Id you are using Stata 10 or earlier this presentation at the 2008
> Fall North American Stata Users Group meeting may be useful:
>
> ender_3way_anova.pdf
>
> Best of luck.
>
> --
> Phil Ender
> UCLA Statistical Consulting Group
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>

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