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From |
John Antonakis <john.antonakis@unil.ch> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: ivreg2 and xtoverid error |

Date |
Sat, 03 Apr 2010 22:46:31 +0200 |

Thank Kit.

1. regress y on x (obtain significant coefficient) 2. regress y on z (obtain significant coefficient) 3. regress y on x and z (obtain significant coefficient only for x)

reg y x1-x13 i.lead_num, cluster(lead_num) est store fe reg y x1-x13, cluster(lead_num) hausman fe, force

Best regards, John. ____________________________________________________

Department of Organizational Behavior University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 Faculty page: http://www.hec.unil.ch/people/jantonakis Personal page: http://www.hec.unil.ch/jantonakis ____________________________________________________ On 03.04.2010 17:14, Kit Baum wrote:

<> John saidI get exactly the same estimates and standard errors with -ivreg- and-ivregress-, with the cluster robust variance estimator. When using-ivreg2- with the -noid- option it works and I get the same estimates;more importantly, I also get the Hansen J-test, which is what interestsme most (the -ivregress- estimator does not report an overid forcluster-robust vce's):Hansen J statistic (overidentification test of all instruments):402.476, Chi-sq(404) P-val = 0.5121The one thing to worry about here is that which arises with Sargan-Hansen tests after xtabond or user-written xtabond2: the overid test may not have much power when confronted with hundreds of instruments.You also mention the test provided by 'estat endogenous', which could be done in ivreg2 via the endog() option. This Durbin-Wu-Hausman test is merely telling you that you shouldn't use OLS on this model. But you're probably convinced of that in any event. Rejecting OLS as inconsistent does not imply that IV is consistent; that depends on the overid test of the excluded instruments (which you pass, but as mentioned may have low power to detect a problem) and the proper specification of the model. You might want to use ivreg2's orthog() option to consider just the non-dummy instruments as a group, and check to see that that Hansen "GMM distance" test also supports the notion that those excluded instruments are suitably orthogonal to the error. 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/

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**Follow-Ups**:**Re: st: RE: ivreg2 and xtoverid error***From:*John Antonakis <john.antonakis@unil.ch>

**References**:**re: st: RE: ivreg2 and xtoverid error***From:*Kit Baum <Baum@bc.edu>

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