okay. Thanks for your reply. I get the impression that the
appropriate approach to implementing an analog of "fixed effects" for
quantile regression would be to remove the respective quantile value
of the dependent variable. In other words, if I'm estimating qreg for
the 0.25 quantile would a more sensible fixed effects analog be to
subtract the average of the 0.25 quantile of the DV for each panel?
person ID time explan. variable DV
1 1998
1 1999
1 2000
1 2001
2 1998
2 1999
so take the 25th percentiles of the DV in 1998, 1999, 2000, 2001, &
2002, sum and divide by 5?
It seems like this could be done to the data first then qreg could be
run. What do you think?
Woolton
On 10/31/07, Maarten buis <[email protected]> wrote:
> --- Woolton Lee <[email protected]> wrote:
> > Is there any way to suppress the constant term when one estimates
> > quantile regression using qreg? I've fixed effects into the equation
> > and many of the dummy variables are omitted because of collinearity
> > with the constant term.
>
> No, see: http://www.stata.com/statalist/archive/2007-10/msg00809.html
>
> Anyhow, even if it were possible I don't think it would be advisable,
> as the dropping of many dummies suggests more serious problems to me.
> Also I am not sure if adding dummies will give you a fixed effects
> model in this case: I always think of a fixed effects model in terms of
> demeaning, and demeaning doesn't seem quite right in quantile
> regression (maybe "demedianing").
>
> -- Maarten
>
>
> -----------------------------------------
> Maarten L. Buis
> Department of Social Research Methodology
> Vrije Universiteit Amsterdam
> Boelelaan 1081
> 1081 HV Amsterdam
> The Netherlands
>
> visiting address:
> Buitenveldertselaan 3 (Metropolitan), room Z434
>
> +31 20 5986715
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
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