Re: st: RE: Re: RE: Re: Two way Fixed Effects & Autocorrelation& Heteroskedasticity

[kosak@gmx.de]

Rodrigo,Mark,
thank you very much for your advice.I will try xtivreg2.
I have antother short question:
Am i right, that for a one-way fixed effect model with the same problems
areg be the appropriate solution?
Best,
Max


--- Urspr�ngliche Nachricht ---
> Von: "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
> An: <statalist@hsphsun2.harvard.edu>
> Betreff: st: RE: Re: RE: Re: Two way Fixed Effects & Autocorrelation& 
> Heteroskedasticity
> Datum: Thu, 30 Mar 2006 23:09:50 +0100
> 
> Rodrigo, 
> 
> > -----Original Message-----
> > From: owner-statalist@hsphsun2.harvard.edu 
> > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> > Rodrigo Alfaro
> > Sent: 30 March 2006 23:03
> > To: statalist@hsphsun2.harvard.edu
> > Subject: st: Re: RE: Re: Two way Fixed Effects & 
> > Autocorrelation& Heteroskedasticity
> > 
> > Mark's suggestion is a addendum to my second option. The 4th 
> > proposes to use Least Square without lag dependent variable 
> > but with manual fixed-effects and with correction of the 
> > standard errors: -newey y x1 x2 ind*, lag(1)- Rodrigo.
> 
> That is what I meant.  -xtivreg2- will estimate least squares models as
> well as IV models:
> 
> xtivreg2 y x1 x2, i(ind) bw(2)
> 
> or, using cluster-robust SEs,
> 
> xtivreg2 y x1 x2, i(ind) cluster(ind)
> 
> Cheers,
> Mark
> 
> > 
> > 
> > ----- Original Message ----- 
> > From: "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
> > To: <statalist@hsphsun2.harvard.edu>
> > Sent: Thursday, March 30, 2006 3:44 PM
> > Subject: st: RE: Re: Two way Fixed Effects & Autocorrelation& 
> > Heteroskedasticity
> > 
> > 
> > > Max, Rodrigo,
> > >
> > > Just a brief addendum to Rodrigo's 4th option:
> > >
> > >> -----Original Message-----
> > >> From: owner-statalist@hsphsun2.harvard.edu
> > >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
> > >> Rodrigo Alfaro
> > >> Sent: 30 March 2006 21:28
> > >> To: statalist@hsphsun2.harvard.edu
> > >> Subject: st: Re: Two way Fixed Effects & Autocorrelation&
> > >> Heteroskedasticity
> > >>
> > >> Dear Max
> > >>
> > > <snip>
> > >>
> > >> (4) A way to solve the problem without a lag dependent
> > >> variable is using a standard error correction that takes care
> > >> of the behavior of the error term but does not change the
> > >> Least Square estimation of the parameters. You can use
> > >> -newey- with manually fixed effect, but you have adjust the
> > >> degree of freedom (I wrote a command for that I can send you
> > >> if you are interesting).
> > >
> > > -xtivreg2- will do this.  The fixed effects are handled 
> > automatically,
> > > as is the dof adjustment.  However, you need respectable number of
> > > periods for this to work, since the asymptotics require t to go to
> > > infinity.  The alternative is cluster-robust standard 
> > errors, which are
> > > robust to arbitrary autocorrelation and which will work 
> > with any number
> > > of periods (since the asymptotics require only the number of cross
> > > sections to go to infinity).  -xivreg2- will do this too.  -findit
> > > xtivreg2- will find it for you.
> > >
> > > Cheers,
> > > Mark
> > >
> > >>
> > >> Rodrigo.
> > >>
> > >>
> > >> ----- Original Message -----
> > >> From: <kosak@gmx.de>
> > >> To: <statalist@hsphsun2.harvard.edu>
> > >> Sent: Thursday, March 30, 2006 11:11 AM
> > >> Subject: st: Two way Fixed Effects & Autocorrelation&
> > >> Heteroskedasticity
> > >>
> > >>
> > >> > My problem was already discussed before,but i didn`t found
> > >> an appropriate
> > >> > solution to it.-
> > >> > I have a big panel data set (1500 observations over 20
> > >> years).I want to
> > >> > estimate a model with time and group specific fixed effects
> > >> (Hausman Test
> > >> > performed). The Model suffers from autocorrelation and
> > >> > heteroskedasticity.The problem is that the cluster option
> > >> is not possible
> > >> > for xtregar. Can i use xtgls or areg?As i understood xtgls
> > >> estimates a
> > >> > random effet model.
> > >> > Any suggestions?
> > >> > Max
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