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RE: st: Multiple endogenous regressors


From   Cameron McIntosh <cnm100@hotmail.com>
To   STATA LIST <statalist@hsphsun2.harvard.edu>
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: yuval.arbel@gmail.com
> To: statalist@hsphsun2.harvard.edu
> 
> 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 <kit.baum@bc.edu> 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: yuval.arbel@gmail.com
> 
> *
> *   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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