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RE: st: Stata 11 Random Effects--Std. Errors


From   DE SOUZA Eric <eric.desouza@coleurope.eu>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Stata 11 Random Effects--Std. Errors
Date   Sun, 23 Aug 2009 19:54:10 +0200

Mark,

You say:
2.  Het-robust SEs are valid under a broader range of assumptions than conventional SEs, but are not available as an option and can be obtained only via version control.

What exactly do you mean by "broader"? You need more restrictions on the covariance matrix to derive the het-robust covariance matrix than to derive the heteroscedasticity and seria correlation robust covariance matrix.

You say:
4.  Het-robust SEs can be superior to cluster-robust in finite samples under some circumstances (your example), but are not available as an option and can be obtained only via version control.

Allowing for heteroscedasticity consistent SEs but imposing identical serial correlation at all time lags appears odd to me. I agree that there is a sample size problem. Probably what is needed is a Windmeijer-style sample size correction.

Eric


Eric de Souza
College of Europe
Brugge (Bruges), Belgium
http://www.coleurope.eu


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Schaffer, Mark E
Sent: 23 August 2009 17:00
To: statalist@hsphsun2.harvard.edu
Subject: RE: st: Stata 11 Random Effects--Std. Errors

Austin,

Very convincing - a nice example of how het-robust may be superior to cluster-robust for the RE estimator in some circumstances.

The behaviour of -xtreg,re- under Stata 11 for reporting SEs seems very peculiar to me:

1.  The default VCE is vce(conventional).

2.  Het-robust SEs are valid under a broader range of assumptions than conventional SEs, but are not available as an option and can be obtained only via version control.

3.  The help file says vce(robust) and vce(cluster <clustvar>) are both options, but in fact the former automatically defaults to the latter.

4.  Het-robust SEs can be superior to cluster-robust in finite samples under some circumstances (your example), but are not available as an option and can be obtained only via version control.

I can't think of another example in Stata where a valid VCE (that in some cases may be the VCE of choice) can be obtained only via version control.  Seems like a bad precedent to me - what if the new version of the estimator is superior to the old version in other respects, or differs in its behaviour with respect to postestimation commands or the macros it leaves behind?

It would be much better for -xtreg,re- to revert to standard Stata behaviour and for vce(robust) to produce the usual het-robust SEs.

Just my 0.02, as they say.

--Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Austin 
> Nichols
> Sent: 22 August 2009 14:13
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: Stata 11 Random Effects--Std. Errors
> 
> For example:
> 
> clear all
> prog reclr, rclass
> version 10.1
> drawnorm x1-x10 v, n(50) clear
> forv i=1/10 {
>  replace x`i'=exp(x`i')
>  }
> g id=_n
> expand 20
> g e=rnormal()
> bys id: replace e=e[_n-1]/2+e/2 if _n>1 g y=(x1+x2+x3+x4+x5)/5+v+e 
> xtreg y x1-x10, cl(id) i(id) re test x1 x2 x3 x4 x5 return scalar 
> c1=r(p)<.05 test x6 x7 x8 x9 x10 return scalar c0=r(p)<.05 xtreg y 
> x1-x10, r i(id) re test x1 x2 x3 x4 x5 return scalar r1=r(p)<.05 test 
> x6 x7 x8 x9 x10 return scalar r0=r(p)<.05 eret clear end simul, 
> seed(1) rep(10000): reclr su
> 
> This shows rejection rates for RE of 9% for a nominal 5% alpha with 
> het-robust SEs but 41% with cluster-robust SEs.
> 
> Here's another example, where my preferred default does not do so 
> well:
> 
> clear all
> prog reclr, rclass
> version 10.1
> drawnorm x1-x10 v, n(50) clear
> g id=_n
> expand 20
> forv i=1/10 {
>  replace x`i'=exp(x`i'*4/5+rnormal()/5)  } g e=rnormal() bys id: 
> replace e=e[_n-1]*4/5+e/5 if _n>1 g y=(x1+x2+x3+x4+x5)/5+v+e xtreg y 
> x1-x10, cl(id) i(id) re test x1 x2 x3 x4 x5 return scalar c1=r(p)<.05 
> test x6 x7 x8 x9 x10 return scalar c0=r(p)<.05 xtreg y x1-x10, r i(id) 
> re test x1 x2 x3 x4 x5 return scalar r1=r(p)<.05 test x6 x7 x8 x9 x10 
> return scalar r0=r(p)<.05 xtreg y x1-x10, i(id) re test x1 x2 x3 x4 x5 
> return scalar o1=r(p)<.05 test x6 x7 x8 x9 x10 return scalar 
> o0=r(p)<.05 xtreg y x1-x10, cl(id) i(id) fe test x1 x2 x3 x4 x5 return 
> scalar fec1=r(p)<.05 test x6 x7 x8 x9 x10 return scalar fec0=r(p)<.05 
> xtreg y x1-x10, i(id) fe test x1 x2 x3 x4 x5 return scalar 
> feo1=r(p)<.05 test x6 x7 x8 x9 x10 return scalar feo0=r(p)<.05 eret 
> clear end simul, seed(1) rep(10000): reclr su
> 
> 
> On Fri, Aug 21, 2009 at 11:00 AM, Austin 
> Nichols<austinnichols@gmail.com> wrote:
> > Mark--
> > I concur that getting het-robust SEs should still be possible with 
> > -xtreg, re-.  I wonder, for example, about the relative
> performance in
> > smallish samples where T and N are both under 100 and there are many 
> > explanatory variables.  The cluster-robust SE will offer uniformly 
> > better performance as N goes to infinity, I suspect, but in
> some kinds
> > of small finite samples the het-robust SE may be better, and users 
> > should have that option IMHO. Unless there is strong evidence that 
> > cluster-robust is always better than het-robust in RE
> models, which I
> > have not seen. On the other hand, I would make
> cluster-robust SEs the
> > default (for both FE and RE), instead of
> -vce(conventional)-, and make
> > users spell out vce(conventional) [literally] to get that inferior 
> > estimator.  Of course, I would also make -fe- the default
> for -xtreg-
> > in Stata 11.1, and make users spell out -re- to get that (more often
> > inferior) estimator.  Why not help people make good choices with the 
> > defaults?  (I would also make het-robust SEs the default
> for -regress-
> > and make folks specify vce(ols) for the old default.)
> >
> > On Wed, Aug 19, 2009 at 2:19 PM, Schaffer, Mark
> E<M.E.Schaffer@hw.ac.uk> wrote:
> >> This is different from the reason provided by Stock-Watson
> (2008) for
> >> FEs (see earlier in the thread).
> >>
> >> Stock and Watson show that for the fixed effects
> estimator, the usual
> >> robust VCV - i.e., robust but not cluster-robust - is not
> consistent.
> >> It's another example of the "incidental parameters" 
> problem.  This is
> >> why Stata 10 won't report it under any circumstances,
> including version
> >> control.
> >>
> >> My suspicion was that this might carry over to the usual
> robust VCV for
> >> the random effects estimator and that this was why it was
> dropped in
> >> Stata 11, but apparently not.   Using cluster-robust with RE is 
> >> apparently just following standard practice in the literature.
> >>
> >> If so, though, then I think I'd prefer to see non-cluster
> robust SEs
> >> available with the RE estimator through an option rather
> than version
> >> control.
> >>
> >> --Mark (left scratching his head and wondering why robust
> and cluster
> >> robust are both kosher for the RE estimator, only cluster-robust is 
> >> kosher for the FE estimator, Stata's PA estimator allows
> only robust but
> >> not cluster-robust, and Stata's MLE estimator allows neither)
> >>
> >>
> >>> -----Original Message-----
> >>> From: owner-statalist@hsphsun2.harvard.edu
> >>> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of DE 
> >>> SOUZA Eric
> >>> Sent: 19 August 2009 18:37
> >>> To: 'statalist@hsphsun2.harvard.edu'
> >>> Subject: RE: st: Stata 11 Random Effects--Std. Errors
> >>>
> >>> To add more detail:
> >>> Two of the assumptions underlying the random effects
> model are that:
> >>> 1. the unobservable effects are not correlated with the 
> >>> explanatory variables 2. the residuals have the random effects 
> >>> structure The second assumption is not required for consistency.
> >>> Wooldridge's argument is: then why impose it. "With fixed T and 
> >>> large N asymptotics, we lose nothing in using robust standard 
> >>> errors and test statistics even if [the random effects error 
> >>> structure] holds".
> >>>
> >>> Eric
> >>>
> >>>
> >>> Eric de Souza
> >>> College of Europe
> >>> Brugge (Bruges), Belgium
> >>> http://www.coleurope.eu
> >>>
> >>> -----Original Message-----
> >>> From: owner-statalist@hsphsun2.harvard.edu
> >>> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of David 
> >>> M. Drukker
> >>> Sent: 19 August 2009 19:04
> >>> To: statalist@hsphsun2.harvard.edu
> >>> Subject: RE: st: Stata 11 Random Effects--Std. Errors
> >>>
> >>> Continuing the thread about why -xtreg .., re vce(robust)- changed 
> >>> its meaning between Stata 10 and Stata 11, Mark E Schaffer 
> >>> <M.E.Schaffer@hw.ac.uk> asked for a citation.
> >>>
> >>> Wooldridge (2002, section 10.4.2) recommends the new approach of 
> >>> having
> >>> -vce(robust)- mean -vce(cluster panelvar)-.
> >>>
> >>> When we first offered the -vce(robust)- and -vce(cluster
> >>> clustvar)- on -xtreg, re-, we wanted to offer users the 
> >>> flexibility to use either estimator.  We had Monte Carlo 
> >>> simulations showing that there are data generating processes for 
> >>> which -vce(robust)- performs quite well, so we allowed users to 
> >>> choose.
> >>>
> >>> Since we first offered these options, the literature has focused 
> >>> on always using -vce(cluster panelvar)- to obtain a "robust" 
> >>> estimator for -xtreg, re-.  We made the change because the new 
> >>> method is what users now expect and it offers additional 
> >>> generality.
> >>>
> >>>    David
> >>>    --ddrukker@stata.com
> >>>
> >
> 
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