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st: RE: RE: RE: RE: ivreg vs ivreg2, both with cluster


From   <J.Fischer@lse.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: RE: RE: RE: ivreg vs ivreg2, both with cluster
Date   Fri, 23 Jun 2006 21:48:13 +0100

Hi Mark

I see. It is because of the nice ivreg2 test statistics.

So I would appreciate to ge that beta-version - this would save me some
headache.

Thanks and enjoy the weekend
Justina 

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Schaffer,
Mark E
Sent: 23 June 2006 21:29
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: RE: RE: ivreg vs ivreg2, both with cluster

Justina,

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> J.Fischer@lse.ac.uk
> Sent: 23 June 2006 21:18
> To: statalist@hsphsun2.harvard.edu
> Subject: st: RE: RE: ivreg vs ivreg2, both with cluster
> 
> Hi Mark
> 
> Yes I am very much interested in your beta-Version. If you could sen 
> it to me....
> 
> Based on your comment: does it imply that the stata command ivreg uses

> a somewhat different estimator from ivreg2, obviously not a GMM 
> estimator (looks like an OLS ?) ?

No, IV and OLS are examples of GMM estimators, and ivreg2 does straight
IV just like IV - see the help file.  The problems arise when an
estimate of the covariance matrix of orthogonality conditions is needed
in order to do efficient GMM, or to do testing afterwards.

Cheers,
Mark

Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS tel +44-131-451-3494 / fax
+44-131-451-3296
email: m.e.schaffer@hw.ac.uk
web: http://www.sml.hw.ac.uk/ecomes
 
> Best and thanks
> 
> Justina
> 
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Schaffer, 
> Mark E
> Sent: 21 June 2006 22:58
> To: statalist@hsphsun2.harvard.edu
> Subject: st: RE: ivreg vs ivreg2, both with cluster
> 
> Justina,
> 
> > -----Original Message-----
> > From: owner-statalist@hsphsun2.harvard.edu
> > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> > J.Fischer@lse.ac.uk
> > Sent: 21 June 2006 13:39
> > To: statalist@hsphsun2.harvard.edu
> > Subject: st: ivreg vs ivreg2, both with cluster
> > 
> > Hi
> > 
> > I am estimating a pooled cross section with 26 states, 10 time 
> > variables, and, many additional explanatory variables, of
> which one is
> 
> > endogenous. Clustering at the state level is supposed to
> account for
> > serial autocorrelation of any kind.
> > 
> > Using ivreg2, which I prefer for its test statistics, I receive the 
> > error message:
> > "number of clusters must be greater than instruments" (in principle 
> > fine with me)
> > 
> > Using ivreg and the same model specification, however,
> carries out the
> 
> > estimation without problems.
> > 
> > Does anybody know why this is the case ? How can I make
> > ivreg2 work for me without having to reduce the number of
> explanatory
> > variables ?
> 
> This restriction in the current version of ivreg2 arises because when 
> the number of clusters is smaller than the number of instruments, the 
> variance-covariance matrix of orthogonality conditions (central to 
> GMM) is not of full rank, and this can cause problems.
> 
> It's also a problem when the number of clusters is small in an 
> absolute sense.  Put another way, in your application you are relying 
> on only 26 observations when estimating the standard errors in your 
> regression.
> 
> That said, we have a version of ivreg2 on the way that has a new 
> option,
> -fwl- (for Frisch-Waugh-Lovell), which provides a way of addressing 
> the issue.  The variables in the varlist provided to -fwl- are 
> exogenous regressors that are "partialled out"
> of the remaining variables.  This solves the problem because the 
> var-cov matrix of orthog conditions then becomes full rank.  ivreg2 
> will report the coeffs for the remaining variables only.  All you need

> to do is specify enough exogenous regressors in -fwl- so that the 
> number of remaining instruments (exogenous regressors + excluded 
> instruments) is no longer greater than the number of clusters.
> 
> We're somewhere between programming and testing this option, so I'm 
> not sure when it will be generally available, but if the need is 
> urgent on your part, I can send you a beta version.
> 
> Cheers,
> Mark
> 
> Prof. Mark Schaffer
> Director, CERT
> Department of Economics
> School of Management & Languages
> Heriot-Watt University, Edinburgh EH14 4AS tel +44-131-451-3494 / fax
> +44-131-451-3296
> email: m.e.schaffer@hw.ac.uk
> web: http://www.sml.hw.ac.uk/ecomes
> 
> > 
> > Thanks
> > 
> > Justina
> > 
> > 
> > 
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