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st: Re: hausman test


From   Mark Schaffer <M.E.Schaffer@hw.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   st: Re: hausman test
Date   Thu, 07 Nov 2002 14:57:14 +0000 (GMT)

Hi everybody.  It turned out that the Dawn's problem -- failure to get a positive Hausman test 
statistic for endogeneity even when using the -sigmamore- option -- resulted from the fact that she 
was estimating by IV with the -robust- option.

The -sigmamore- option of the -hausman- command is incompatible with heteroskdastic-robust 
estimation because, basically, there is no single "sigma" when errors are heteroskedastic.

-hausman- without -sigmamore- will be asymptotically valid in conjunction with the robust 
covariance estimator, but then you can encounter the negative test statistic problem.

The easiest way to guarantee a positive Hausman test statistic for endogeneity is to estimate the 
model with ivreg2 (downloadable from ssc-ideas).  Estimate the efficient model using ivreg2, and 
put the variables to test for endogeneity in the -orthog- option.  This will guarantee a positive 
test statistic, even with robust covariance estimators.  (It's an application of a result described 
in Hayashi (2002), Econometrics, p. 220.  Or see our (Baum-Schaffer-Stillman) working paper, 
http://fmwww.bc.edu/ec-p/WP545.pdf.)

--Mark


> > > > Date sent:      	Wed, 6 Nov 2002 13:14:58 -0500 (EST)
> > > > From:           	Dawn M Brancati <dmb73@columbia.edu>
> > > > To:             	statalist@hsphsun2.harvard.edu
> > > > Copies to:      	M.E.Schaffer@hw.ac.uk
> > > > Subject:        	Re: st: Re: hausman test
> > > >
> > > > >
> > > > > Thanks for all the advice. I am working on it now. The sigmamore
> > > > > option is under ivreg. I had already used it, however, and still
> > > > > received the error message that I mentioned.
> > > > >
> > > > > Dawn
> > > > >
> > > > >
> > > > > On Wed, 6 Nov 2002, John A Karikari wrote:
> > > > >
> > > > > > Could I have more information on the "sigmamore" option.  I couldn't
> > > > > > find it using the search process. Thanks.
> > > > > >
> > > > > > >>> M.E.Schaffer@hw.ac.uk 11/06/02 12:06PM >>>
> > > > > > Dawn,
> > > > > >
> > > > > > If you're using -hausman- after ivreg, you won't get the "failure to
> > > > > > meet the asymptotic assumptions" problem if you use the -sigmamore-
> > > > > > option.  This guarantees that the matrix difference in the middle of
> > > > > > the standard Hausman test statistic is positive definite.
> > > > > >
> > > > > > Even simpler, just to install -ivendog- from ssc-ideas.  This will
> > > > > > give you both the Wu-Hausman artificial regression F stat, and the
> > > > > > (Durbin-Wu-)Hausman chi-sq statistic, after estimation using
> > > > > > -ivreg-.
> > > > > >
> > > > > > Hope this helps.
> > > > > >
> > > > > > --Mark
> > > > > >
> > > > > > Date sent:      	Wed, 06 Nov 2002 11:53:37 -0500
> > > > > > From:           	"WILLIAM EVEN" <EVENWE@muohio.edu>
> > > > > > To:             	<statalist@hsphsun2.harvard.edu>
> > > > > > Subject:        	st: Re: hausman test
> > > > > > Send reply to:  	statalist@hsphsun2.harvard.edu
> > > > > >
> > > > > > > An alternative approach to the Hausman test is to include the
> > > > > > residual
> > > > > > > from the reduced form equation into the primary equation and
> > > > > > > perform
> > > > > > a
> > > > > > > t-test on its significance.   This avoids any problems with the
> > > > > > > differences in the variance covariance matrices being non-positive
> > > > > > > definite that one can encounter in the original formulation of the
> > > > > > > test.
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > > Bill Even, Professor
> > > > > > > Department of Economics
> > > > > > > Miami University
> > > > > > > Oxford, OH 45056
> > > > > > >
> > > > > > > Phone: 513-529-2865
> > > > > > > Fax:  513-529-6992
> > > > > > > home page: www.sba.muohio.edu/evenwe
> > > > > > > e-mail:  evenwe@muohio.edu
> > > > > > >
> > > > > > > >>> dmb73@columbia.edu 11/06/02 10:29AM >>>
> > > > > > > Hi,
> > > > > > >
> > > > > > > I'd like to know if anyone has any suggestions on how to proceed
> > > > > > when
> > > > > > > you cannot perform the Hausman specification test because your
> > > > > > > data does not meet the asymptotic assumptions of the test. The
> > > > > > > augmented regression test is also based on the same assumptions of
> > > > > > > the Hausman and so is of no help in this regard. I am using the
> > > > > > > Hausman test as
> > > > > > a
> > > > > > > pre-test for two-way causation but cannot perform it in some
> > > > > > > instances. Is any one familiar with any alternatives to theses
> > > > > > > tests for @SLS? If not, is the best approach to report results of
> > > > > > > both the OLS models and the 2SLS models?
> > > > > > >
> > > > > > > Thanks.
> > > > > > > DB
> 
> *************************************
> Columbia University
> Political Science Department
> 420 W. 118th Street, 7th Flr.
> New York, NY 10027
> E-Mail: dmb73@columbia.edu
> 
> 

Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3008
email: m.e.schaffer@hw.ac.uk
web: http://www.sml.hw.ac.uk/ecomes
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