[R-sig-Geo] spatial model with several observations per spatial unit

[Tom Petersen]

Dear list,
I wonder if anyone has experience of implementing a spatial model with a large
panel dataset?
Besides the spatial dimension, the data is grouped by firm and industry. So I
have several cross-sectional and time period observations in each spatial unit
(the industry effect is so far modelled with separate regression equations).
Does anybody have a piece of advise on how to progress with this
kind of data?
One possibility might be to implement a spatial SUR with one equation per time
period(?). I forgot to mention that there is also considerable time series
correlation in the data as well, as is common with economic data.
So far, I have used a non-spatial "two-step" GMM (Arellano-Bond type) with some
success, but of course without the cross-sectional correlation. Maybe it would
be possible to proceed with this method, but weighting the observations
differently. In this case, the cross-sectional (spatial) correlation must be
estimated somehow in the "first step", in order to get the regressor parameters
consistently estimated in the "second step". 
As is described above, the spatial correlation can be divided in "within area"
and "across areas" components, apart from the (autocorrelated) time series
component for each firm (and across firms, e.g. in the same spatial unit).

/Tom
============================
Tom Petersen
Transport and Location Analysis
Dept. of Transport and Economics
School of Architecture and the Built Environment
Teknikringen 78 B
KTH, SE-100 44 Stockholm
e: tomp at kth.se
t: +46 8 790 68 33 
m: +46 70 424 00 75