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RE: st: Multiple endogenous regressors
From
Cameron McIntosh <[email protected]>
To
STATA LIST <[email protected]>
Subject
RE: st: Multiple endogenous regressors
Date
Sat, 22 Oct 2011 09:29:58 -0400
Like Kit, I got a bit of a a surprise (and chuckle) about the example. In the Keynesian model, 2SLS, ILS, and the simple IV estimator yield identical results when instrumenting Y_t with I_t. See Chapter 11 in:
Batalgi, B.H. (2008). Econometrics (3rd. ed.). Berlin - Heidelberg: Springer-Verlag.
Let's move on,
Cam
> Date: Sat, 22 Oct 2011 10:34:30 +0200
> Subject: Re: Re: Re: RE: re:Re: st: Multiple endogenous regressors
> From: [email protected]
> To: [email protected]
>
> I would like to assure you that I would not write about this matter if
> I was not certain about my knowledge in this area.
>
> I believe you are confusing between 2SLS and IV estimators, which are
> not exactly the same:
>
> When you are talking about 2SLS you need literally to replace
> projected values from the solution equation - but here the second
> equation is simply an identity, so you cannot produce here projected
> values. I suppose what STATA did here is to use investment as
> instrumental variable to consumption in the right-hand-side of the
> consumption function. This is not 2SLS even if the command is 2SLS and
> even if the output tells otherwise!!!
>
>
>
> On Fri, Oct 21, 2011 at 9:51 PM, Christopher Baum <[email protected]> wrote:
> > <>
> > Yuval said
> >
> > Moreover, take for example the following system of Kensian (sic) equations:
> >
> > C=a+bY+u
> > Y=C+I
> >
> > Note, that the only way to get consistent estimates in this case is by
> > the ILS (you cannot employ here the 2SLS)
> >
> >
> > I''m sure the inability to use 2SLS on a simple Keynesian model will come as a surprise to those of us who write econometrics lecture notes and textbooks, as it is one of the most common textbook examples of IV.
> > An empirical counterexample:
> >
> > . webuse klein
> >
> > . ivregress 2sls consump (totinc = invest)
> >
> > Instrumental variables (2SLS) regression Number of obs = 22
> > Wald chi2(1) = 24.24
> > Prob > chi2 = 0.0000
> > R-squared = 0.8430
> > Root MSE = 2.8442
> >
> > ------------------------------------------------------------------------------
> > consump | Coef. Std. Err. z P>|z| [95% Conf. Interval]
> > -------------+----------------------------------------------------------------
> > totinc | .4593425 .0932901 4.92 0.000 .2764971 .6421878
> > _cons | 26.07967 5.571562 4.68 0.000 15.15961 36.99973
> > ------------------------------------------------------------------------------
> > Instrumented: totinc
> > Instruments: invest
> >
> >
> > Apparently Yuval did not take my response to his point (4) too seriously.
> >
> > Kit
> >
> > Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html
> > An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html
> > An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.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/
> >
>
>
>
> --
> Dr. Yuval Arbel
> School of Business
> Carmel Academic Center
> 4 Shaar Palmer Street, Haifa, Israel
> e-mail: [email protected]
>
> *
> * For searches and help try:
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> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
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