Six new Stata modules for generating spatial effect variables for spatial lag, spatial-x or spatial error models are available on SSC, courtesy of Kit Baum. Stata 9 is required and mmerge.ado must already be installed. Use -ssc- to install.
-spmon- generates a spatial effect variable for monadic data, i.e. where the estimation dataset consists of individual units.
-spundir- generates an undirected dyad contagion spatial effect variable for undirected dyadic data, in which contagion emanates from the behaviour of other dyads. An undirected dyad dataset consists of pairs of units (dyads). Whilst one can distinguish unit i from unit j, it is either not possible to distinguish between the dyad ij and the dyad ji or one does not want to make such a distinction.
-spagg-, -spspc- and -spdir- all generate different forms of spatial effect variables for directed dyadic data. In directed dyadic data, the interaction between two dyad members ij initiates with i and is directed toward j. In the directed dyad ij, unit i is called the source, while unit j is called the target of the interaction. It is different from the directed dyad ji, where, in contrast, unit j is the source and unit i is the target.
-spagg- generates an aggregate source or target contagion spatial effect variable, respectively, in which contagion emanates from the aggregate behaviour of other sources or other targets, respectively.
-spspc- generates a specific source or target contagion spatial effect variable, respectively, in which contagion emanates from the specific behaviour of other sources or other targets with respect to the specific dyad ij under observation.
-spdir- generates a dyadic dyad contagion spatial effect variable, where contagion emanates from the behaviour of other dyads.
Generating spatial effect variables for monadic data is not very difficult, but -spmon- facilitates the process.
Generating spatial effect variables for dyadic data is much more difficult. Normally, one would need a so-called 4-adic dataset, which connects dyads with dyads. In many applications, such a dataset would be far too large to be handled by a standard PC. The ado-files for dyadic data solve this problem by parsing through a virtual 4-adic dataset generated from a standard dyadic dataset. The ado-files therefore only require users to set-up a standard dyadic dataset.
More information can be accessed at http://personal.lse.ac.uk/neumayer/spatial.htm
Eric Neumayer ([email protected])
and Thomas Plümper
Please access the attached hyperlink for an important electronic communications disclaimer: http://www.lse.ac.uk/collections/secretariat/legal/disclaimer.htm
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