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

Author

Listed:
  • Peter Sarlin

    (Department of Information Technologies, Åbo Akademi University)

Abstract

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

    as
    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.
    2. Artis, M.J. & Zhang, W., 2002. "Membership of EMU: A Fuzzy Clustering Analysis of Alternative Criteria," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 17, pages 54-79.
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    4. repec:ebl:ecbull:v:6:y:2007:i:25:p:1-15 is not listed on IDEAS
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    More about this item

    Keywords

    Self-organizing maps; Optimum Currency Area; projection; clustering; geospatial visualization;
    All these keywords.

    JEL classification:

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

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