I assume you are dealing with a panel where all regressors are strictly
exogenous.
Including a dummy for a subgroup is not equivalent to running separate
regressions for each subgroup. If you want to allow for subgroup-specific
heterogeneity across all the parameters then you need to add multiplicative
dummies for each regressor plus dummies for subgroup-specific constants.
Then the two methods will produce the same values for the parameters so
there is no issue of sample size. However, pooling the whole data set will
restrict the variance error to be the same across all subgroups, so if you
don't want to do so an adjustment is necessary.
See a usefull discussion in
http://www.stata.com/support/faqs/stat/awreg.html
Pooling the whole data set and adding multiplicative dummies will allow you
to test in a straightforward way whether these dummies are statistically
insignificant or not. So this approach is more efficient in the sense that
you could allow a limited only set of regressors being subgroup-specific at
the end.
Hope this helps
Vasilis
On Oct 21 2005, Dirk Nachbar wrote:
Dear all
there are two ways to deal with heterogeneity in your data set
1. you include a dummy for a sub-group
2. you run several regressions for each sub-group
Now I was thinking when do we choose one or the other . It seems that if
we do not want the same explanatory variables for each sub-group we
should use approach 2, but then maybe our sample becomes too small.
Approach 1 seems more neat and is quicker.
What do you think? Which approach is better and how should we determine
when to use which approach?
Dirk Nachbar Assistant Economist Pensim2 Department for Work and Pensions
Level 4, The Adelphi 1-11 John Adam St WC2N 6HT London 020 796 28531
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