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From |
"Mark Schaffer" <M.E.Schaffer@hw.ac.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: overidxt with random effects |

Date |
Tue, 07 Sep 2004 16:28:25 +0100 |

Katie, A couple of years ago I hacked away at overidxt so that it handled random effects. It's not entirely satisfactory in its handling of finite sample corrections etc, which is partly why I didn't make it more widely available, but it's probably usable for your purposes. If you contact me off-list, I'll send it to you and we can see if it does what you want. As for Sargan vs. Hansen's J, this is partly just a terminological issue, and conventions vary. Usually, Sargan's stat refers to non- heteroskedasticity-robust statistic, even if the var-cov matrix isn't diagonal, and Hansen's J refers to some sort of robust version. But this isn't always the case. For example, the reporting used by xtabond follows Arellano-Bond (1991) and refers to a "Sargan statistic" throughout; in fact, the "one-step Sargan" is a non-het- robust stat based on a var-cov matrix with some off-diagonal correlations, and the "two-step Sargan" is a heteroskedasticity- robust version that many (including -xtabond2-) would call a "J" statistic. Others now refer to a "Sargan-Hansen" or a "Hansen- Sargan" statistic to cover all cases. Cheers, Mark Date sent: Tue, 07 Sep 2004 10:43:21 -0400 From: Katie Winder <klwinder@jhu.edu> Subject: st: overidxt with random effects To: statalist@hsphsun2.harvard.edu Send reply to: statalist@hsphsun2.harvard.edu > Dear Stata list, > I am estimating a wage equation with some endogenous regressors using a > random effects model (because a correction I am using later on for selection > bias requires it rather than fe), so I happily went about estimating > xtivreg, re. But, as I'm sure you all know, overidxt only works after fe. > The Sargan stat returned after fitting the fixed effects model is good, and > my instruments are on okay grounds theoretically, but I'm still concerned > that I can't test them directly in the random effects model (plus, it looks > strange if I report a statistic in one table and not another). > > So, my question is: Does anyone have a suggestion about how I can test the > overidentifying restrictions in a random effects IV model? > > As I've been thinking about this, I've been getting a little confused about > how I would do this. I think I need to use Hansen's J statistic instead of > Sargan's because there will be intra-person correlation in the error terms > using re. So, I can get the clustered weighting matrix from the xtivreg, re > residuals, and then use the instruments Z after putting them through the GLS > transform to construct J. I think I can modify the xtivreg ado file to do > this, but I am not even sure if this is what I want to do (and plus, given > my programming skills, it will not be pretty). > > I'd appreciate anyone's feedback on this, particularly Steve Stillman, since > I know he is an expert on this stuff and is often on the list. > > Thanks! > Katie Winder > Johns Hopkins U. > Dept. of Economics > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ Prof. Mark E. Schaffer Director Centre for Economic Reform and Transformation Department of Economics School of Management & Languages Heriot-Watt University, Edinburgh EH14 4AS UK 44-131-451-3494 direct 44-131-451-3008 fax 44-131-451-3485 CERT administrator http://www.som.hw.ac.uk/cert * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: overidxt with random effects***From:*Katie Winder <klwinder@jhu.edu>

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