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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/ * * 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/