st: RE: spatwmat for panel data?

[Gordon Hughes <G.A.Hughes@ed.ac.uk>]

Before you start to look for Stata routines or other software you 
should be more specific about the model that you are trying to estimate.

It cannot possibly make sense to estimate a model with spatial 
correlations between 44,000 separate units and there is no software 
that would enable you to do this - think of the size of the spatial 
weighting or correlation matrix.  What is more likely is that your 
data is clustered in some sense - i.e. the spatial correlations are 
between groups of individuals on whom you have observations.  This is 
a routine feature of large surveys and you can investigate the 
options in Stata for estimating models with cluster-adjusted standard 
errors - there are a number of -xt..- panel estimators with this 
feature or you can look at the estimators for survey data.

A further consideration is whether your interest lies in the spatial 
aspects of your data or merely in adjusting standard errors to allow 
for spatial correlation.  If it is the latter, then the -xtscc- 
module provides Driscoll-Kraay robust standard errors.  On the other 
hand, if it is the former then you may need to write your own 
routines in Mata.  There is a rapidly growing literature on the 
econometrics of spatial panel data - see papers by Baltagi, Pesaran, 
Elhorst and many others - but relatively few packaged routines that 
implement the methods which are described in the literature.

Routines to estimate models with spatial autocorrelation or spatial 
lags are primarily designed for cross-section data and tend to assume 
that you have or can calculate a spatial weighting matrix across all 
units, which is not realistic in your case.  This is why the 
distinction between clusters and spatial units is so important.

Regards

Gordon Hughes

===================

Professor Gordon Hughes
Department of Economics
University of Edinburgh
31 Buccleuch Place
Edinburgh EH8 9JT
United Kingdom

E-mail : G.A.Hughes@ed.ac.uk

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