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Evaluating a Self-Organizing Map for Clustering and Visualizing Optimum Currency Area Criteria


  • Peter Sarlin

    () (Department of Information Technologies, Åbo Akademi University)


Optimum currency area (OCA) theory attempts to define the geographical region in which it would maximize economic efficiency to have a single currency. In this paper, the focus is on prospective and current members of the Economic and Monetary Union. For this task, a self-organizing neural network, the Self-organizing map (SOM), is combined with hierarchical clustering for a two-level approach to clustering and visualizing OCA criteria. The output of the SOM is a topologically preserved two-dimensional grid. The final models are evaluated based on both clustering tendencies and accuracy measures. Thereafter, the two-dimensional grid of the chosen model is used for visual assessment of the OCA criteria, while its clustering results are projected onto a geographic map.

Suggested Citation

  • Peter Sarlin, 2011. "Evaluating a Self-Organizing Map for Clustering and Visualizing Optimum Currency Area Criteria," Economics Bulletin, AccessEcon, vol. 31(2), pages 1483-1495.
  • Handle: RePEc:ebl:ecbull:eb-10-00756

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    References listed on IDEAS

    1. DomeNico Raguseo & Jan Sebo, 2008. "Optimum Currency Areas theory and the Slovak suitability for the euro adoption," Economics Bulletin, AccessEcon, vol. 6(40), pages 1-14.
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    More about this item


    Self-organizing maps; Optimum Currency Area; projection; clustering; geospatial visualization;

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • F0 - International Economics - - General


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