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Re: st: instrumental variable for quantile regression

From   "alessia matano" <[email protected]>
To   [email protected]
Subject   Re: st: instrumental variable for quantile regression
Date   Wed, 28 May 2008 14:22:45 +0200

Dear Austin.

You are right I tried to demean the data myself, since when I used
xtdata....., fe i(ind) it didn't create deviations from time average
for each individual (ind). But, then I asked myself if it does not in
fact do that, but just prepare the data for such a transoformation.
Any help regarding this is welcome.

Secondly i applied a bootstrap procedure like the following (after
time demeaning the data)

prog me
 qreg dmwage dmindchar dmspec  dmd1995-dmd2004 dmsectors dmarea, q(0.1)
bs, cluster(ind): me

I before tsset the data
tsset ind year
and it recognize that it is a panel. Then when I apply the program he
wrote repeated time values within panel. hence, my question about
Moreover generally, in fixed effects estimates I also clustered the
observations for area (to deal with heteroskedasticity questions), and
I do not know if I can do it now.
Last, I tried the same with clustering() (see below) and it stopped at
the third bootstrap writing something like:

prog me
 qreg dmwage dmindchar dmspec  dmd1995-dmd2004 dmsectors dmarea, q(0.1)
bs, cluster(): me

Thanks again for any help

2008/5/27 Austin Nichols <[email protected]>:
> alessia matano <[email protected]>:
> Perhaps if you show what you typed, folks on the list can offer
> advice.  Even better, show an example using a publicly available
> dataset, e.g. start your example code with
> webuse psidextract, clear
> tsset
> Probably you need at least the idcluster(newvar) option on
> -bootstrap-.  How are you demeaning yourself?  Better to use an -xt-
> commmand.
> On Tue, May 27, 2008 at 6:13 AM, alessia matano <[email protected]> wrote:
>> Dear Austin,
>> I attempt to do the estimation with bootstrap....after time-demeaning
>> my observation. I have just a doubt. It is true that bootstrap allows
>> the cluster option, what i do not understand well is for what should i
>> clustered my observations to allow correct standard errors after
>> time-demenaing myself the observations. generally i clustered them not
>> for individual, but for provinces where they live (cause of
>> heteroskedasticity). However bootstrap either using the individual
>> cluster or using the province ones does not work, saying that there
>> are time repeated values within the panel, while when I tsset them it
>> understands the panel structure. May you help me with this also? It
>> works only when I cluster() with no variables inside.
>> May you suggest me something? Also to read about?
>> thank you very much
>> alessia
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