I am a geographer but I don't know much about (what is
usually called human) geography. I regarded it as my main field
of interest between 1968 and 1969, but no longer. There aren't
many geographers on this list, I think.
However, your question is not really geographical. I guess
from this that you are using lots of dummies in each case
and for once the answer is whichever set of dummies gives
you a better model, according to your criteria of model
excellence (my favourite criterion is usually minimal
structure in residuals).
In broad terms both LADs and TTWAs are fairly heterogeneous
as both spring from a idea of an area functioning together
rather than formal similarity of anything. So knowing the
area might not help enormously in predicting wage. But
whichever spatial subdivision has a finer mesh should
prove better.
Nick
[email protected]
Ada Ma
> I have a bunch of wage observations and all the observations are
> attached with two geographical identifiers - local authority districts
> (LADs) and travel to work areas (TTWAs). I want to find out how wages
> vary across different areas in UK.
>
> Now I can run wage estimations using either one of the two categorical
> variables as explanatory variable. I would however like to find out
> which categorical variable fits the data better. How do I compare the
> two sets of results given that the explanatory variables are quite
> different?
>
> Could you recommend what kind of tests I should use and if you are a
> geographer, could you tell me are there any criteria that are used by
> geographers to choose between different definitions of geographies
> (regions, as opposed to LADs, as opposed to TTWAs, etc.)
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