Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

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


From   [email protected]
To   [email protected]
Subject   Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests
Date   Fri, 20 Jan 2012 21:22:54 +0100

Hi

I think you are quite right, and my intuition also tells me something else. Let's assume I have only one endogenous regressor,
but more than one instrument candidates since there is no theoretical foundation for choosing the 'right' instruments for the
endogenous variable. If I include all of these instruments and the -overid- test statistic is still not significant, there is
likely something wrong with the instruments. This is because theory claims that one instrument should suffice here, and each
additional instrument included merely increases the standard deviation of the IV estimator. As a consequence, the model must
be overidentified from a theoretical view. However, if the Sargan test fails to detect overidentification, this can only be 
due to the fact that the selected instruments are quite weak...

Best,
Andreas

[email protected] schrieb: ----- 
An: [email protected]
Von: "Justina Fischer" 
Gesendet von: [email protected]
Datum: 19.01.2012 23:22
Betreff: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests

nope.. the bias could turn the direction of observed influence - how do you know then which one is correct (OLS or IV)?

Rule of thumb is: better no instrument (OLS) than weak ones !!

it is sufficient to provide good convincing arguments why you selected the instruments; there is no need for theoretical models suggesting the instrument explicitly. Let your phantasy work !

Cheers
Justina

-------- Original-Nachricht --------
> Datum: Thu, 19 Jan 2012 23:00:00 +0100
> Von: [email protected]
> An: [email protected]
> Betreff: Antwort: Re: RE: st: Spurious inference from endogeneity tests

> Thanks for this clarifying remark.
> 
> In addition, literature always stresses the requirement that
> IVs should be selected in line with theoretically motivated 
> arguments. But economic theory may sometimes be limited in its 
> capability to yield valid instruments. However, when instruments
> are therefore weak, I expect the bias of the IV estimator to be
> similarly large as the OLS estimator. Maybe then it would make
> sense to prefer one of the two estimators in terms of theory
> driven expectations as the lesser evil?
> 
> [email protected] schrieb: ----- 
> An: [email protected]
> Von: Austin Nichols 
> Gesendet von: [email protected]
> Datum: 18.01.2012 16:37
> 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 <[email protected]>
> 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 <[email protected]>
> >> An: STATA LIST <[email protected]>
> >> 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: [email protected]
> >> > Subject: Re: st: Spurious inference from endogeneity tests
> >> > To: [email protected]
> >> >
> >> > 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: [email protected]
> >> > > An: [email protected]
> >> > > 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?
> 
> *
> *   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/
> *
> *   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: [email protected]. [email protected]
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/
*
*   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/


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index