On 28 December 2012 02:16, Allin Cottrell <cottrell(a)wfu.edu> wrote:
Select a set of regressors that are as near orthogonal as possible
;-). Seriously, gretl is better able to handle highly collinear
regressors than most econometric software; if a regressor is
dropped, it's probably not possible to estimate its coefficient
other than via multiple precision arithmetic (which gretl offers,
but for OLS only).
Okay, that's sensible advice, but with this data, these are the only
variables I have: they were chosen for their relevance, as opposed to their
orthogonality!
> (2) as there is no LDV, how do I ensure that I select robust SEs
that do
> not correct for autocorrelation?
That seems to me a non-sequitur. Why should the non-inclusion of an
LDV immunize a model against an autocorrelated error? Rather the
reverse, I would think: if you include enough lags of the dependent
variable, then maybe you have "whitened" the error term to the point
where correction for autocorrelation is redundant.
There is no LDV in the model because - correct me if I'm wrong - that would
render the parameter estimates biased in a fixed-effects LSDV model (Judson
and Owen, 1999). The solution to that would be to move to IV models, but
(a) they're not for kids; and (b) I've not yet hammered out a requisite
battery set of IVs to even think about making such a model work!
Allin Cottrell
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--
Clive Nicholas (
clivenicholas.posterous.com)
[Please DO NOT mail me personally here, but at <clivenicholas(a)hotmail.com>.
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Judson RA and Owen AL (1999) "Estimating dynamic panel data models: a guide
for macroeconomists", Economics Letters 65(1), 9-15