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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   Fri, 23 May 2008 14:44:28 +0200

Many thanks for this suggestion also Austin. I will try to check how
it works. My sample is actually of 500000 observation for like 40000
individuals. However I will try also to run the command with some
random subsample of my dataset (just for computational need).
For the question of instrumenting I will read the references you cite
and try to apply them using mata.
if you have something more to suggest me, it is welcome of course.

2008/5/23 Austin Nichols <[email protected]>:
> alessia matano <[email protected]>:
> I believe someone at Statacorp is working on an "xtqreg", but that
> won't be available in time to help you.  qreg doesn't support cluster,
> but bootstrap does:
> but you will want to run some simulations to see how your approach
> works in finite samples, I think.
> On Fri, May 23, 2008 at 6:14 AM, alessia matano <[email protected]> wrote:
>> Dear Austin and Brian.
>> Thanks first for your answers. Austin I probably missunderstood the
>> answer of Brian in that previous message suggesting such a procedure,
>> I thought it was to solve this kind of problem. Anyway I should be
>> more explicity about the data I use. I have individual panel data
>> (with wages and a set of individual characteristics) and I matched
>> them with provincial variables whose I would like to estimate the
>> impact on differnet points of workers wage distribution.
>> Hence I have two problems I'd like to solve.
>> - The first is that because of likely endogeneity I would like to
>> instrument my provincial variable and perform a quantile regression.
>> This is the reason why of my post. I thought that it could have been
>> possible to run a first stage and then correcting the standard errors
>> performing the qreg estimation. But it is not correct. Thank for this
>> - The second. I would like to correct for individual unoberved
>> heterogeneity and hence to see if it is possible to estimate  a
>> quantile fixed effects estimation. I know that also this question is
>> not easy to solve. I red another stata faq that suggests to use
>> xtdata, fe and then apply qreg clustering the standard errors with a
>> general sandwich formula (?!?). The last point I did not well
>> understood, and also qreg does not allow clustering options. If you
>> have something to advice also on this topic, many thanks. Below the
>> link of the related stata faq.
>> thank you again
>> alessia
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