Abstract
This exploratory study examines the extent to which non-spatial determinantsof foreign direct investment (FDl) organize themselves in a mannerthat 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. Inthis 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 itsdistribution, we demonstrate an untapped utility in the visualization andanalysis of economic data.
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