> I have a cross-sectional data on children and their familes. I want to
> "control for" the family unobservable (the family fixed effect). I have
> used
>
> xtreg y x, fe (family_id)
>
> Now I am interested in the effect of x on a particular percentile
> (quantile) of y. I would like to "differ out" the family unobservable in
> _qreg_ or _sqreg_.
Is this really how a quantile regression to be interpreted? I was rather
thinking of it giving a quantile of a conditional distribution. If x is
age, and y is height, then -qreg- will give you something like the 25% or
75% percentiles of the children height (I would specify something like
B-splines in place of the linear term for this regression to be serious).
If y is an educational attainment, and x is income, then -qreg- will give
you the 25% or 75% or whatever percentile of the grade distribution
conditional on income... but that is not the effect of income on grades in
the poorest 25% of population.
> Your suggestion about creating dummies may not work very well in my
> case, because (1) I have a large number of families, and each family has
> a small (and unbalanced) number of children, say from 1 to 6; and (2) I
> do not need to estimate the coefficients of the fixed effect, all I want
> is to control for. I am looking for something (a STATA command) to do
> what _areg_ does for the mean response estimates.
Have you checked -xtdata- yet? It can do fixed-effect demeaning for you,
and then you can run -qreg- (even though it won't give you cluster
corrected standard errors... which is theoretically possible given that a
quantile is an M-estimate, and thus can be corrected for clustering with a
regular sandwich formula).
--- Stas Kolenikov
-- Ph.D. student in Statistics at UNC-Chapel Hill
- http://www.komkon.org/~tacik/ -- [email protected]
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