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st: Re: RE: Re: RE: Re: RE: Fixed-effects, unbalanced panel and time-invariant variable
You are right. Now how one can run the IV only for the TI using any
set Z of instruments? This is similar to Hausman-Taylor estimator
but only taking the first 2 steps. Pretend x4 and x5 are TI then
xtreg y x1 x2 x3, fe
predict aux1, r
bysort id: egen aux2=mean(aux1)
reg aux2 z1 z2 z3
Just this?? do we need std-errors adjustments? does this work for
unbalanced-data? I think that we don't need more adjustments.
Moreover the covariance of _b[x1] and _b[z1] is zero. Am I right?
She can take x4 and x5 in the Z set (FE+BE), run the model and
compare it with RE using Hausman test (RE is the efficient one).
PS: Do you have some ideas why GLS-RE and MLE-RE were
so different in my example?
Still not sure I understand the issue she faces.
FE - consistent estimates of the TV coefficients, but not the TI ones
because they drop out.
RE - consistent estimates of the TV and TI coefficients, if not
correlated with the group error component ("fixed/random effect").
Inconsistent estimates of both if endogenous effects.
FE+BE - consistent estimates of TV coefficients. Consistent estimates
of TI coefficients, if not correlated with group error component, i.e.,
like random effects; inconsistent estimates of TI coefficients if they
She is particularly interested in the TI coefficients. In terms of
consistency, it doesn't matter if she goes down the RE or FE+BE route.
If one estimate of the TI coefficients is inconsistent, so is the other.
Did I get this right? If so, is one conclusion that she needs
instruments for her TI variables?
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