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From |
"David M. Drukker, StataCorp" <ddrukker@stata.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: Re: st: xtgee robust standard errors |

Date |
Fri, 16 Aug 2002 11:35:32 -0500 |

In the continuing thread about robust standard errors after -xtgee , fam(gauss) link(id)-, Axel <A.Heitmueller@hw.ac.uk> asked: > david, are you saying that xtgee using the robust option is similar > to a hausman taylor iv estimation where one can use random effects > despite x_it correlated with u_it in order to get estimates of time > invariant variables? No, when x_it and u_i are correlated in the model y_it = B x_it + u_i + e_it with u_i ~ i.i.d over the panels e_it ~ i.i.d over all the observations x_it uncorrelated with e_it e_it uncorrelated with u_i -xtgee , fam(gauss) link(id)- will NOT provide consistent estimates of the marginal effect of x_it on y_it. In contrast, the Hausman-Taylor estimator (Hausman and Taylor 1981) can provide consistent estimates of the parameter B when x_it is correlated with u_i. The Hausman-Taylor esimator overcomes the correlation between the x_it and u_i via the method of instrumental variables. Still, there does exist a population parameter that corresponds to B for the above model with x_it correlated with u_i, although I do not know how to interpret it. -xtgee , fam(gauss) link(id)- will estimate this population parameter and specifying -robust- will provide consistent estimates of the standard error. If you are insterested interested in obtaining consistent estimates of B that are interpretable as the marginal effect of x_it when x_it and u_i are correlated, you should look into the instrumental variables estimators. Baltagi (2001) and Wooldridge (2002) both give very good introductions to these methods. --David ddrukker@stata.com Baltagi, Badi. 2001. "Econometric Analysis of Panel Data." New York: John Wiley and Sons. Hausman, Jerry and Taylor, William. 1981. "Panel Data and Unobservable Individual Effects", Econometrica, Vol 49 No 6: pp 1377-1398. Wooldridge, Jeffrey. 2002. "Econometric Analysis of Cross Section and Panel Data." Cambridge, Massachusetts: The MIT Press. * * 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/

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