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Re: RE: st: Spurious inference from endogeneity tests


From   Austin Nichols <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: RE: st: Spurious inference from endogeneity tests
Date   Wed, 18 Jan 2012 10:36:55 -0500

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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