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RE: st: RE: xtivreg2: confusing analytical samples reported


From   "Schaffer, Mark E" <[email protected]>
To   <[email protected]>
Subject   RE: st: RE: xtivreg2: confusing analytical samples reported
Date   Tue, 19 Mar 2013 15:49:15 -0000

So the singletons are probably the answer.  xtivreg2 tells you how many
there were, so that would confirm it.

--Mark

> -----Original Message-----
> From: [email protected] [mailto:owner-
> [email protected]] On Behalf Of Kemeny, Thomas Ernest
> Sent: 19 March 2013 14:05
> To: <[email protected]>
> Subject: Re: st: RE: xtivreg2: confusing analytical samples reported
> 
> Hi Mark,
> 
> Thanks for your help. Some answers:
> 
> Versions: I am running stata 12.1; ivreg2 v3.0.06; xtivreg2 v1.0.12.
> 
> Singletons: yes! It detects singleton groups, resulting in
observations not
> used.
> 
> Coefficients- yes, same coefficients with or without partialling and
clustered
> SEs.
> 
> Thanks!
> Tom
> 
> 
> 
> On Mar 18, 2013, at 4:28 PM, "Schaffer, Mark E"
<[email protected]>
> wrote:
> 
> > Tom,
> >
> > A few thoughts...
> >
> > 1.  Can you report which versions of Stata, xtivreg2, ivreg2, etc.
you
> > are using?  (As per the Statalist FAQ.)
> >
> > 2.  Is xtivreg2 reporting anything about not using singleton
observations?  It
> is more informative in this respect than the official xtivreg and
xtreg
> commands.
> >
> > 3.  The coefficient estimates you obtain with
> >
> > xtivreg2 y (a = x z) b c d_* e_* f_*, fe ffirst partial(d_* e_* f_*)
> > cluster(g)
> >
> > you can also obtain with official xtivreg:
> >
> > xtivreg2 y (a = x z) b c d_* e_* f_*, fe
> >
> > Are they the same?
> >
> > --Mark
> >
> >> -----Original Message-----
> >> From: [email protected] [mailto:owner-
> >> [email protected]] On Behalf Of Kemeny, Thomas Ernest
> >> Sent: 18 March 2013 16:52
> >> To: [email protected]
> >> Subject: st: xtivreg2: confusing analytical samples reported
> >>
> >> I'm estimating a fixed effects model using annual panel data on
> >> individuals.There is some reason to investigate potential bias due
to
> >> endogeneity of one predictor (let's call it variable a).
> >>
> >> My base model, ignoring endogeneity issues, is as follows:
> >>
> >> .xtreg y a b c i.(d e f), fe vce(cluster g)
> >>
> >> where d, e and f represent time, geography, and industry dummy
> variables.
> >> This model runs on a certain analytical sample. This all seems
fine.
> >> Here is where the trouble starts: starting from the same data, I
then
> >> want to run a  2SLS, using instruments x and z. Before I can do so,
I
> >> have to the generate the dummy variables for d, e and f, since the
> >> i() subcommand will not work with xtivreg2.
> >>
> >> .qui tab d, gen (d_)
> >> .qui tab e, gen (e_)
> >> .qui tab f, gen (f_)
> >>
> >> Then I can run xtivreg2, as follows:
> >>
> >> .xtivreg2 y (a = x z) b c d_* e_* f_*, fe ffirst partial(d_* e_*
f_*)
> >> cluster(g)
> >>
> >> The thing is, xtivreg fe reports a smaller analytical sample than
> >> xtreg fe -- more than a third less! And, even more curiously, if
> >> after running the xtivreg2, I run the following
> >>
> >> .keep if e(sample)
> >>
> >> the kept analytical sample is actually the same as it was in the
> >> original xtreg fe command.
> >>
> >> I am perplexed. Is ixtivreg2 mis-reporting the analytical sample?
Or
> >> is something else going on here?
> >>
> >> Weirder - when I run xtivreg, the native stata panel IV command,
the
> >> analytical sample here is the same as with xtreg fe, in other words
> >> the sample issue disappears  (but i cannot cluster SEs using
xtivreg,
> >> which i can do using xtivreg2).
> >>
> >> Any thoughts?
> >>
> >> Much thanks.
> >> Tom
> >>
> >> --
> >> Thomas Kemeny
> >> Research Assistant Professor
> >> Department of Public Policy
> >> University of North Carolina at Chapel Hill
http://unc.edu/~tkemeny/
> >> *
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> >
> >
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----- 
Sunday Times Scottish University of the Year 2011-2013
Top in the UK for student experience
Fourth university in the UK and top in Scotland (National Student Survey 2012)

We invite research leaders and ambitious early career researchers to 
join us in leading and driving research in key inter-disciplinary themes. 
Please see www.hw.ac.uk/researchleaders for further information and how
to apply.

Heriot-Watt University is a Scottish charity
registered under charity number SC000278.


*
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