Antwort: Re: RE: st: Spurious inference from endogeneity tests

[andreas.zweifel@uzh.ch]

Hi Justina

this is a good idea, I have tried both rivtest and condivreg to adress the weak instruments problem. Unfortunately however, I have two instead of only one endogeneous regressors (since I model an interaction effect of the actually endogeneous variable with a control variable where the interaction term is by definition also endogeneous), and these commands are designed for IV settings with only one troublesome regressor. 

As it seems now, the best thing to do is to drop the weakest instruments in terms of the individual t-statistics in the two first-stage regressions as long as the Anderson-Rubin test statistic is large enough to ensure that the model is still correctly specified. Hopefully, the weak instrument tests in the first stage will indicate that the remaining instruments are becoming a bit stronger. But in the end I should decide based on the Hausman test whether to use 2SLS or not. Even though the Hausman test should be performed only after testing for overidentifying restrictions - however, with the overID test being quite useless if instruments are weak...

Best, 
Andreas

-----owner-statalist@hsphsun2.harvard.edu schrieb: ----- 
An: statalist@hsphsun2.harvard.edu
Von: "Justina Fischer" 
Gesendet von: owner-statalist@hsphsun2.harvard.edu
Datum: 18.01.2012 18:14
Betreff: Re: RE: st: Spurious inference from endogeneity tests

Hi

user-written command rivtest provides robust-to-weak-instruments test statistics - what you might need here (of course it is always better to search for stronger instruments in first place). 

See also the accompanying paper:
http://econ.tulane.edu/RePEc/pdf/tul0901.pdf


-------- Original-Nachricht --------
> Datum: Wed, 18 Jan 2012 10:36:55 -0500
> Von: Austin Nichols <austinnichols@gmail.com>
> An: statalist@hsphsun2.harvard.edu
> Betreff: Re: RE: st: Spurious inference from endogeneity tests

> In re
> the poster's central question:
> "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?"
> I would answer yes.  Without better instruments, you have learned
> nothing from 2SLS, including whether OLS is biased or not.  The overID
> test is no good if you don't have strong instruments, since its
> failure to reject the overID restrictions could be due merely to the
> weakness of your excluded instruments.
> 
> On Tue, Jan 17, 2012 at 6:44 PM, Justina Fischer <JAVFischer@gmx.de>
> wrote:
> > wow. I am deeply impressed :-)
> >
> > Let us hope the authors provide user-written Stata commands soon....
> >
> > justina
> > -------- Original-Nachricht --------
> >> Datum: Tue, 17 Jan 2012 18:41:27 -0500
> >> Von: Cameron McIntosh <cnm100@hotmail.com>
> >> An: STATA LIST <statalist@hsphsun2.harvard.edu>
> >> Betreff: RE: st: Spurious inference from endogeneity tests
> >
> >> 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?
> 
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-- 
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


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