I have a general question about how to handle overlapping observations
in a fixed (or random) effects panel regression. Specifically, I have
quarterly observations of investment, cash flow, and a number of other
variables. The model specifies a yearly relationship where investment
in a specific product line over the 12 months is dependent on the cash
flow over the same period and the asset base at the beginning of the
12 month period.
If I simply run the regression with all of the observations, I must be
double counting information. It seems like I only have 1 real
independent observation for every 4 quarterly observations. What is
the meaningful way to adjust the estimation to take this into
account? The reason I don't simply drop the 1-3 quarter observations
is that I later end up matching the quarters to yearly data in another
sample and I want to be able to compare the data.
Is there a general understanding of how this type of estimation works?
Malcolm
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