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Re: st: Dummy variables for pooled regressions
Michael Blasnik replied to Yvonne Capstick:
> The -egen group- suggestion will provide for fully interacted effects, but
> I think that just the main effects are wanted (unless I am guessing wrong
> about the somewhat hazy intention). The only way I know of doing this is
> to allow areg or xtref, fe to absorb one of the variables and to add
> dummies for the other (e.g., using xi).
Like Michael, I too interpreted Yvonne to want two seperate fixed effects
inserted into the -i()- option for her -xtreg, fe- model, which you can't
have. Austin Nichols' rather neat suggestion
> . egen g=group(state ind)
> . areg y x, absorb(g)
does what I should have figured out: generate a single fixed effect
variable combining both sets of information. But isn't there a problem
with this: namely, the codes for this (in effect) interaction term are not
Say we have a dataset of ten states and ten industry sectors, both coded
from 1 to 10. We then run Austin's code and get our FE variable (let's
call it G) that Yvonne thinks she's got. This will give her codes running
from 1 to 100. The question is, is Yvonne comfortable with trying to
interpret lower numbers of G as representing certain industries (or
states) and higher numbers of G as representing other industries (or
states)? Since these categories that comprise G are _nominal_, rather than
ordinal, I wouldn't be comfortable with this at all.
Perhaps you can acheive this if your number of categories for each of the
variables is very small, but if not, I think you'd be easily lost in a
large mire of output codes. I know I would be. If you can figure out a way
around it, then you're a smarter bod than I.
I should also make a correction here: when I discussed time dummies in my
reply to Yvonne, I, of course, meant state dummies (which Yvonne wants).
Apologies there. Anyway, the point I was making still stands.
CLIVE NICHOLAS |t: 0(044)7903 397793
Politics |e: email@example.com
Newcastle University |http://www.ncl.ac.uk/geps
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