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Re: st: Re: hausman test


From   "Mark Schaffer" <M.E.Schaffer@hw.ac.uk>
To   "John A Karikari" <KarikariJ@GAO.GOV>, statalist@hsphsun2.harvard.edu
Subject   Re: st: Re: hausman test
Date   Wed, 6 Nov 2002 17:43:19 -0000

John,

Date sent:      	Wed, 06 Nov 2002 12:36:48 -0500
From:           	"John A Karikari" <KarikariJ@GAO.GOV>
To:             	<statalist@hsphsun2.harvard.edu>, <M.E.Schaffer@hw.ac.uk>
Subject:        	Re: st: Re: hausman test

> Could I have more information on the "sigmamore" option.  I couldn't
> find it using the search process. Thanks.

-help hausman- gives you the following explanation of this option:

"sigmamore allows you to specify that the two covariance matrices 
used in the test be based on a common estimate of disturbance 
variance (sigma2); the variance from the more (fully) efficient 
estimator.  This option provides a proper estimate of the contrast 
variance for so-called tests of exogeneity and over-identification in 
instrumental variables regression. Note that this option can only be 
specified when both estimators save e(sigma) or e(rmse)."


That's it in a nutshell though there's more to it if you're 
interested, e.g., it's not valid after estimation using -robust-. 

--Mark

> 
> >>> 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
> > 
> > 
> > *
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> 
> 
> Prof. Mark E. Schaffer
> Director
> Centre for Economic Reform and Transformation
> Department of Economics
> School of Management & Languages
> Heriot-Watt University, Edinburgh EH14 4AS  UK
> 44-131-451-3494 direct
> 44-131-451-3008 fax
> 44-131-451-3485 CERT administrator
> http://www.som.hw.ac.uk/cert 
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Prof. Mark E. Schaffer
Director
Centre for Economic Reform and Transformation
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS  UK
44-131-451-3494 direct
44-131-451-3008 fax
44-131-451-3485 CERT administrator
http://www.som.hw.ac.uk/cert
*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/



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