Mark,
Thanks.
Re: point 2, I read too quickly - or read what I wanted to find - namely, that you were comparing het-robust to cluster-robust.
Re: point 4, yes, I had time in mind.
I am reading Angrist and Pischke but have still to get to Chapter 8.
Eric
Eric de Souza
College of Europe
Brugge (Bruges), Belgium
http://www.coleurope.eu
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Schaffer, Mark E
Sent: 23 August 2009 20:43
To: [email protected]
Subject: RE: st: Stata 11 Random Effects--Std. Errors
Eric,
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of DE SOUZA
> Eric
> Sent: 23 August 2009 18:54
> To: '[email protected]'
> Subject: RE: st: Stata 11 Random Effects--Std. Errors
>
> 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.
In Stata-speak, "vce(conventional)" means classical iid homoskedasticity-assumed etc. etc. etc. This is the default VCE for -xtreg,re-. Het-robust SEs are valid under heteroskedasticity, conventional SEs are not, hence "valid under a broader range of assumptions".
>
> 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.
It's not odd in some applications. The easiest case I can think of is when the individual observations are not multiple obs in the time dimension. A concrete example would be a survey of individuals or firms and the panel unit is the country/state/county of residence.
> I agree that there is a sample size problem. Probably what is needed
> is a Windmeijer-style sample size correction.
Agrist and Pischke, "Mostly Harmless Econometrics" (2009), chapter 8, have a nice discussion of the cluster-robust VCE, what can go wrong with it, and what to do about it. My point is that since some of the things that can go wrong with the cluster-robust VCE estimator don't apply to the standard het-robust VCE estimator, and since the absence of clustering within panels may sometimes be a reasonable assumption, disallowing (or strongly discouraging, which is what availability solely under version control amounts to) standard het-robust SEs seems like a bad idea to me.
Cheers,
Mark
>
> Eric
>
>
> Eric de Souza
> College of Europe
> Brugge (Bruges), Belgium
> http://www.coleurope.eu
>
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of Schaffer,
> Mark E
> Sent: 23 August 2009 17:00
> To: [email protected]
> 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: [email protected]
> > [mailto:[email protected]] On Behalf Of Austin
> > Nichols
> > Sent: 22 August 2009 14:13
> > To: [email protected]
> > 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<[email protected]> 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<[email protected]> 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: [email protected]
> > >>> [mailto:[email protected]] On Behalf Of DE
> > >>> SOUZA Eric
> > >>> Sent: 19 August 2009 18:37
> > >>> To: '[email protected]'
> > >>> 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: [email protected]
> > >>> [mailto:[email protected]] On Behalf
> Of David
> > >>> M. Drukker
> > >>> Sent: 19 August 2009 19:04
> > >>> To: [email protected]
> > >>> 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
> > >>> <[email protected]> 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
> > >>> [email protected]
> > >>>
> > >
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/help.cgi?search
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
>
> --
> Heriot-Watt University is a Scottish charity registered under charity
> number SC000278.
>
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
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>
> *
> * For searches and help try:
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> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
--
Heriot-Watt University is a Scottish charity registered under charity number SC000278.
*
* For searches and help try:
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