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RE: st: What multiple regression model for extreme distributions

From   Maarten buis <>
To   stata list <>
Subject   RE: st: What multiple regression model for extreme distributions
Date   Tue, 2 Feb 2010 07:30:24 -0800 (PST)

> I have a household income survey data ( 38,000 observations), and my
> problem is doing a multiple regression on saving ( independent var) to
> ethnicity/strata/employmenttc( dependent var).
> The problem is this : 70% of my observation for the value of saving is
> zero. I had recode it to 1 and log them, but the distribution is still
> extremely skewed ( mean 0.78, std dev is 2.4  min 0 max 14). The
> historgam still looks like the letter L , exteremly skewed to the
> right with  long tail.  Obviously, OLS is out, and I tried Poisson(
> glm nbinomial) but the distribution is still not distributed normally.
> The data are in order i.e no missing values etc etc. It is clean.For
> some reason, lobit would not run.

One option is you could fit a -zip- to the original saving variable, and
use the -robust- option. That way you are modeling the mean saving as a
two-step proces, first a person decides whether or not to save, after 
that the persons that do save decide their amount. The influence of the
explanatory variables on the explained variable occurs through the log
link function, so you avoid the problem that you are no longer modeling
the mean savings when you first take the log of savings and than model 
that transformed variable. Notice that by using the -robust- option you
are only making the assumption that your model for the mean is correct,
and that you are not making additional distributional assumptions.

Hope this helps,

Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen


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