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From |
Tingting Tong <pumpkinting@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: One question about XTOVERID |

Date |
Wed, 28 Dec 2011 12:13:01 -0500 |

Dear Kit, Thank you for your quick reply. After doing the FE and RE, I need to do the PMG (Pool mean group) and FMOLS (Fully modified OLS) since I have a large T and large N panel. However, both PMG and FMOLS is based on Fixed effect model. So I wish my test result would be fixed effect model. I cannot perform Hausman test and robust hausman test due to my data problem. (I have time variant and individual invariant variables.) My XTOVERID result indicates a RE model. Furthermore, the intercept, coefficients and S.D. of my FE and RE model results are quite similar. I think this furture proves that RE is better. With all evidence, I am not sure about should I insist that FE is better in my case? Could you please give me some guidance or reference? Thank you very much. Tingting Tong On Wed, Dec 28, 2011 at 12:01 PM, Christopher Baum <kit.baum@bc.edu> wrote: > <> > > > I saw a lot of introduction about XTOVERID on internet. But i still > have one simple question. > > When using XTOVERID determine FE and RE, can anybody tell me what is > the null hypothesis? > > For instance, in my case, when running XTOVERID, my p-value is bigger than 0.1. > > Does it mean FE model is better? > > > > As the help file for Schaffer & Stillman's -xtoverid- (from SSC) explains, the "Hausman test" for FE vs RE can > also be cast as a test of the additional overidentifying restrictions that RE imposes. FE (xtreg, fe) is consistent > iff X \perp \epsilon, where X contains regressors and \epsilon is the idiosyncratic error. FE does not require > that X \perp u, where u is the fixed effect. RE does require that X \perp u, so there are additional overidentifying > restrictions associated with RE. The null of either the Hausman form of the test or of the test performed by > xtoverid is that RE is consistent. A large value of the test statistic (or a small p-value of the statistic) is a rejection > of that null, saying that RE is inconsistent. If you are getting a p-value of 0.15 or 0.20, then the evidence > against RE is not that strong, and you can get away with the RE assumptions on the error process. > > 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/ * * 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/

**References**:**re: st: One question about XTOVERID***From:*Christopher Baum <kit.baum@bc.edu>

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