Thanks Robert. Yes, I do want to include an interaction
experience*ability in each regression. What you suggest (splitting the
sample) is clearly a possiblity. However, with a quantile regression I
would be using the entire sample, and observations would receive a
different weight depending on how "far" they are from the quantile of
interest. I just wonder if such a thing (quantile regression with
quantiles NOT of the dependent variable but of another variable) has
been done and, more important, if it makes sense...
Tony
On 7/25/05, Robert Duval <[email protected]> wrote:
> quantile regression fits a line at different points of the CONDITIONAL
> distribution of y given x, i.e. f(y|x).
>
> At each fixed value of x (i.e. x=x0) f(y|x=x0) gives you the
> distribution of y after controlling for x (a distribution of the
> errors in other words). Qreg fits a line at a given (prespecifed)
> quantile of such distribution.
>
> If you're not including variable z as a regressor in the conditioning
> set then qreg won't give you what you want as stated in your goal (
> "coefficients of experience in a series of wage regressions by
> quantile of the distribuiton of ability").
>
> If you're willing to assume exogeneity on your excluded variable z, it
> seems to me that it would suffice to just split the sample by
> quantiles of the excluded variable and run an ordinary regression over
> each sample (a fully interactive model in other words).
>
> robert
>
>
> On 7/25/05, Antonio Fanari <[email protected]> wrote:
> > Hi,
> > is it possible to run quantile regressions where the quantiles are not
> > defined over the independent variable but over some other variable?
> > Say you have wages as a dependent variable and another variable measuring
> > ability (e.g. an IQ test). Suppose you want to see if the effect of, say,
> > experience on wages varies across quantiles of ability. One way is to
> > include interactions of experience*ability in a traditional OLS regression.
> > However, I was wondering if there is a way to run quantile regressions,
> > instead. So one would come up with coefficients of experience in a series of
> > wage regressions by quantile of the distribuiton of ability.
> > Please forgive me if the question does not make any sense, but I would
> > appreciate any feedback!
> > Thanks.
> > Tony Fanari
> >
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