On 28 December 2012 02:16, Allin Cottrell
<cottrell@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!