[Limdep Nlogit List] can i pick your brains?

[Bill Spitz]

This may not be the best forum for this, but I'm trying to figure out a reasonable modeling approach for the following:

I'm trying to explain changes in levels of airline service (measured as flights per day) across many different airports over about 20 years. So I have a panel set of observations y(it) for airport i and time t.

Here's the rub. Most of the candidates for explanatory variables are either:
-- "i-dominant" variables, ie., they vary significantly from one airport to another, but hardly at all over time, eg. local real income, population, distance to nearest hub, etc, (these serve to essentially provide the scale of operations at the airport); OR
--"t-dominant", they vary significantly over time, but not by airport, eg. fuel prices, airline costs, etc.

So I don't really have the traditional x(it)-type explanatory variables that vary in both dimensions where one would employ a standard panel estimator. I have quickly gotten lost in the LIMDEP manuals with all the different possible panel models that are available.

Any insights into how best to approach this from a modeling standpoint would be appreciated.
Thanks.

William Spitz


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