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st: Robust Hausman test


From   Veronica Veleanu <lexvsv1@nottingham.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: Robust Hausman test
Date   Wed, 2 Nov 2011 17:42:37 +0000

> Dear Statalist,
>
> I am writing with a query related to an older post from 2011-07 archive.
>
>
> I understand that the robust version of the Hausman test (Wooldridge 2002) compares FE versus pooled OLS, while xtoverid compares FE versus RE.
>
> How do you suggest comparing FE versus RE when the model is fitted in the following ways:
> -Pooled OLS:with newey2 or xtscc
> -FE:with xi: newey2 i.panelid lag(#) force or xtscc , fe lag(#) 
> -RE:with xtreg, re cluster(panelid) [as there is no other way to fit newey = or xtscc with RE]
>
>
> So I can compare FE versus pooled OLS in this manner:
>
> * Robust version of the Hausman test (Wooldridge 2002) quietly xtreg y x1 x2 x3 x4, re by id: gen T=3D_N gen theta=3D1-sqrt(e(sigma_e)^2/(e(sigma_e)^2+ T*e(sigma_u)^2)) foreach x in y x1 x2 x3 x4 { by id: egen mean`x' =3D mean(`x') generate md`x' =3D `x' - mean`x'
> generate red`x' =3D `x' - theta*mean`x'
> }
> quietly xtscc  redy  redx1 redx2 redx3 redx4  mdx1 mdx2 mdx3 mdx4, 
> lag(#) test mdx1 mdx2 mdx3 mdx4
>
> But I can only compare FE versus RE by using xtoverid which assumes the FE  model is fitted only with clustered standard errors (not taking account forcross-sectional dependence or MA(h) lag in residuals) so the inference fro= m xtoverid would not be completely correct, right?
>
> Lastly, related to the older post in the archive I mentioned earlier, given that these 2 tests test different things, how can you finally decide betwe= en Pooled, FE or RE? Should one just use all of them?
>
>
> Thanks very much in advance!
>
>
> Veronica
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