To rehash, Joana Quina <[email protected]> reported,
1. She has estimated the parameters of a model using -xtreg, fe- and
that the reported correlation between u_i and X_ij*b is .9249.
2. She has estimated the parameters of the same same model on
the same data. She then performs a Hausman test that fails to
reject random effects.
I agree with Mark Schaffer <[email protected]>, who wrote,
> I wonder if this is being driven by the "omnibus" nature of your Hausman
> test. In your application, it has 12 degrees of freedom, one for each
> coefficient. I can imagine that, loosely speaking, if one coefficient is
> "significantly different" between the 2 specifications, and the other 11 are
> "very similar", then your Hausman test could fail to reject the null that
> the specifications are both consistent.
In Joana's case, one coefficient changed a lot. The Hausman test is known
to lack power in such cases.
-- Bill
[email protected]
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