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RE: st: testing across different sub-samples


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: testing across different sub-samples
Date   Thu, 24 Sep 2009 17:29:42 +0100

This kind of thing is not my territory at all, but I wondering if
fitting  models in which x1+x2+x3 were summed to be a single predictor
would make this easier. 

Nick 
n.j.cox@durham.ac.uk 

Francesco Trivieri

thank you very much for your help.  I am trying to assess whether a sum
of 
three coefficients from a given model (fixed effexts model, as suggested
by 
xtoverid) is the same in two different two-samples. I have just tried
the 
command -suest- suggestd by John, using - reg- instead of xtreg and
allowing 
for fixed effects with dummies (id). Please find below the lines I wrote

xi: reg y x1 x2 x3 x4 x5 i.time i.id if D==0
estimates store zero
xi: reg y x1 x2 x3 x4 x5 i.time i.id if D==1
estimates store one
suest zero one
test 
[zero_mean]x1+[zero_mean]x2+[zero_mean]x3=[one_mean]x1+[one_mean]x2+[one
_mean]x3

From: "Martin Weiss" <martin.weiss1@gmx.de>

> "There is a quick way to do this using -suest-"
>
> Can you give an example? -suest- is not available after -xt-
commands...

John Antonakis

> What you need to do is a Chow test--i.e., test whether the set of
> coefficients differ across samples.
>
> There is a quick way to do this using -suest-
>
> Model the fixed effects with dummies, if you have any.

> On 24.09.2009 15:08, Francesco Trivieri wrote:
>
>> thank you again for your answer. I thought about using a Hausman
test,
>> but I couldn't figure out how to actually implement it in stata for
my
>> case. Please find below a more detailed description of my problem:
>>
>>
>> I am estimating the following model
>>
>> xtreg y b1x1 b2x2 b2x3 b4x4 b5x5 (fe or re)
>>
>> on two different sub-samples (A and B), which can be individuated by
a
>> dummy D. In both cases, I compute an index given by the sum of the
>> first three coefficients (b1+b2+b3). Then I need to assess whether
the
>> two indexes from the two sub-samples are statistically different.  In
>> other words, I need to test whether  (b1+b2+b3)  in A = ( b1+b2+b3)
>> in B.

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