How do I assign more weight to certain variables?

[kjd31]

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[EViews Glenn]

You can't do this with EViews least squares. And to be honest, I'm not entirely certain what you are asking for would mean in the context of least squares.

[edit] Just a note to indicate that the original questions has been deleted.

[Dave_the_Forecaster]

On a (not so) similar topic, I've been trying to devise a method by which I can assign more 'weight' to certain cross-sections in a panel regression. The idea being that when the coefficients are estimated, rather than using all cross-sections equally, the estimates are biased in such a way that the final model is more accurate for certain cross section at the expense of others.

The obvious one to try is to simply duplicate the relevant cross-sections in the data, so if I have 10 x-sections, and I want x-section Y to be twice as important as the others, I simply re-structure the data to have 11 x-sections, with the 11th being a copy of Y.

However, this solution causes issues when it comes to forecasting. I'd be more than grateful if anyone has any ideas about how I could achieve this, or can give me solid reasons why I shouldn't even be trying!


Cheers.