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RE: st: Spurious inference from endogeneity tests


From   Cameron McIntosh <cnm100@hotmail.com>
To   STATA LIST <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Spurious inference from endogeneity tests
Date   Tue, 17 Jan 2012 18:41:27 -0500

The following papers will also be helpful:
Murray, M.P. (2006). Avoiding Invalid Instruments and Coping with Weak Instruments. Journal of Economic Perspectives, 20(4), 111-132.http://www.eui.eu/Personal/Guiso/Courses/Econometrics/Murray_IV_jep_06.pdf

Chao, J.C., & Swanson, N.R. (2005). Consistent estimation with a large number of weak instruments. Econometrica, 73(5), 1673–1692.http://gemini.econ.umd.edu/jrust/econ623/files/chao_swanson_econometrica.pdf

Nevo, A., & Rosen, A.M. (2010). Identification with Imperfect Instruments. The Review of Economics and Statistics, Accepted for publication. 	

Kolesár, M., Chetty, R., Friedman, J.N., Glaeser, E.L., & Imbens, G.W.  (October 2011). Identification and Inference with Many Invalid Instruments. NBER Working Paper No. 17519. http://www.nber.org/papers/w17519

Cam
> Date: Wed, 18 Jan 2012 00:06:34 +0100
> From: JAVFischer@gmx.de
> Subject: Re: st: Spurious inference from endogeneity tests
> To: statalist@hsphsun2.harvard.edu
> 
> Hi Andreas
> 
> for judging whether instruments are weak or not I would as first step look into the first stage regression results, look at the Shea R2, the F-test on the instruments, the single estimates....that tells you already a lot. Maybe use ivreg2.
> 
> Maybe you have only one weak instrument in a set of instruments you should exclude  (so the set is then strong, even though one single weak instrument may bias your results)
> 
> Best
> 
> Justina
> 
> 
> -------- Original-Nachricht --------
> > Datum: Tue, 17 Jan 2012 22:12:36 +0100
> > Von: andreas.zweifel@uzh.ch
> > An: statalist@hsphsun2.harvard.edu
> > Betreff: st: Spurious inference from endogeneity tests
> 
> > Dear Statausers,
> > 
> > I am concerned with an endogeneity problem in my sample of 126 firms when
> > investigating the relationship between managerial disclosure and cost of
> > capital effects. After running the ivreg28 command, the Cragg-Donald test
> > F-statistic is 2.27, which indicates that my instruments are rather weak.
> > However, my model appears to be correctly identified, because the Anderson test
> > statistic for the first stage equation yields a p-value lower than 0.01
> > and the Sargan test statistic is insignificant (p-value = 0.59). Since my
> > instruments have passed the overidentification test, I run the ivendog command
> > which is equivalent to a Hausman test. Again, the test statistic is
> > insignificant (p-value = 0.48). 
> > 
> > If I compare OLS and 2SLS, I find that only the former yields a
> > significant coefficient of managerial disclosure in the model regressing cost of
> > capital on managerial disclosure. Considering the specification tests above, it
> > seems unlikely that 2SLS is an improvement over OLS. Thus I assume that I
> > can take the OLS estimates for causal inference. Is this correct? If yes,
> > the point why I should not use 2SLS is likely due to the weakness of the
> > instruments and the small-sample bias. So I have to conclude from my
> > specification tests that my coefficient estimates from both OLS and 2SLS cannot be
> > interpreted because 2SLS does not succeed in resolving the endogeneity
> > problem?
> > 
> > Your answers will be highly appreciated.
> > 
> > Thanks, Andreas
> > *
> > *   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/
> 
> -- 
> Justina AV Fischer, PhD
> COFIT Fellow
> World Trade Institute
> University of Bern
> 
> homepage: http://www.justinaavfischer.de/
> e-mail: javfischer@gmx.de. justina.fischer@wti.org
> papers: http://ideas.repec.org/e/pfi55.html
> 
> 
> *
> *   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/
 		 	   		  
*
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