This exploratory study examines the extent to which non-spatial determinants
of foreign direct investment (FDl) organize themselves in a manner
that mimics the spatial proximity of twenty-five Eurasian transition economies.
The Kohonen algorithm is used to create a self-organizing map (SOMs)
of a data set that features vectors of twenty-one socioeconomic variables. In
this analysis, clusters emerge among the Central European, Balkan, Baltic,
and Caucasus/Central Asian regions, leaving Russia as a regional outlier.
By introducing SOMs to the discussion of FDI and the factors governing its
distribution, we demonstrate an untapped utility in the visualization and
analysis of economic data.
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