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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 20:55:39 +0200 |

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: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Schaffer, Mark E Sent: 23 August 2009 20:43 To: statalist@hsphsun2.harvard.edu Subject: RE: st: Stata 11 Random Effects--Std. Errors Eric, > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of DE SOUZA > Eric > Sent: 23 August 2009 18:54 > To: 'statalist@hsphsun2.harvard.edu' > 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: 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 > > >>> > > > > > > > * > > * 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 > * http://www.ats.ucla.edu/stat/stata/ > > * > * 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 * http://www.ats.ucla.edu/stat/stata/ * * 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/

**References**:**RE: st: Stata 11 Random Effects--Std. Errors***From:*"Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>

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