Re: st: Chow test to test only slope coefficient and importance of dummy variable?

[Fernando Furquim <ffurquim@gmail.com>]

Hi Sarah,

I think your two questions are related. By including the dummy
variable group2, that model allows group2 to have a different
intercept from group1 (and if you calculate the intercept for group2,
it is 15116.17-5431.147, which equals the intercept of the model
estimated with group2==1 (9685.02) earlier in the FAQ). Without
group2, the assumption is that the intercept is the same for both
groups.

It's a similar story for the rest - the other variables are just
variables interacted with dummies indicating each group, so that the
slopes are allowed to vary for (for example) mpg in group 1 (mpg) and
mpg for group 2 (mpg2). By testing whether these interacted terms are
different from zero, you are testing whether the slopes differ between
the groups. Not sure how this translates to your particular time
series datasets, though.

Hope this helps,

Fernando

On Wed, Nov 13, 2013 at 3:35 PM,  <savinett@ucalgary.ca> wrote:
> Hi,
>
> I am new to Stata and the Chow Test. I want to compare the slopes of two
> sets of time series data using the chow test, however I am not interested
> in any differences in the intercepts of these time series data.  I have
> read the FAQs section on this and found this one:
> http://www.stata.com/support/faqs/statistics/chow-tests/ to be very
> helpful.  I do, however, have two questions:
>
> 1.   Can I use the Chow Test to test that only the slopes are different
> (not both the slope and intercepts)? I still want to include the intercept
> in the model (i.e. not use the “noconstant”). However, for the Chow Test I
> would like it to reflect that if there is a significant difference between
> the groups that this is due to a difference in their slopes (as I expect
> that their intercepts will differ and am not interested this aspect).
>
> 2.  It is not clear to me why the in the example from the Chow Test FAQ
> (link in the first paragraph) “group2” (the dummy variable) is included in
> the regression:
> . regress price mpg weight mpg2 weight2 group2
>
> If someone could please provide me with some insight that would be amazing.
> Thank you very much in advance for your help with my questions!
>
> Sarah
>
>
>
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