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Re: st: Efficient way to run regressions with many dummy variables?


From   David Jacobs <jacobs.184@sociology.osu.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Efficient way to run regressions with many dummy variables?
Date   Mon, 27 Apr 2009 16:58:52 -0400

Look up the Stata routine called -areg-.

Dave Jacobs

At 03:32 PM 4/27/2009, you wrote:
Dear Stata-list,

I am using a data set of 963,966 observations, with 26 variables (after
dropping all variables not needed for my estimation). The observations are
dyadic observations, I have in fact (1400 squared)/2 pairs of observations
 (divided by 2 because the relationship is non directional) and so in the
regressions, I need to control for 1400*2 dummy variables. I run a
regression of the form:
xi: reg y x1 x2 x3 i.observation1 i.observation2
where my dataset consists of dyadic relationships between each
observation1 and each observation2.

The problem I run into is that each regression takes an incredibly long
time (and the server crashes regularly).

In an alternative regression, I use Fafchamps and Gubert NGREG: I run:
xi: ngreg  y x1 x2 x3, id(observation1 observation2)
This also takes an incredibly long time.

My question is: Is there a more efficient way to run regressions in stata
with such an enormous amount of dummy variables?

PS: I do not care about the coefficient on the dummies per se.

Thank you very much in advance for your response.

Pauline

--
Pauline Grosjean
Ciriacy Wantrup Fellow, Department of Agricultural and Resource Economics
University of California Berkeley
Web page: http://are.berkeley.edu/~pgrosjean/
Mobile: 510 384 0141

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