Abstract
The Economic and Monetary Union (EMU) is the culmination of the European integration process from a financial perspective, whose main aim is the implantation of a one and only one currency for all the member states included in this integration project taking place in early 2002. To decide the relation of countries included in this phase it was established a group of economical regulations (macroeconomics rules) known as Convergence Criteria or Maastricht Criteria which must be fulfilled to guarantee the economic convergence among countries sharing the same currency. Nevertheless, these criteria are not enough to assure the effective convergence among states as far as enterprises is concerned, due to internal national differences in microeconomic structures, which affect competitiveness among firms and could distort a lot the effect of the union in favour of some countries and against others. The use of unsupervised artificial neural networks, specifically the employment of self-adaptive models based on Kohonen’s proposal, makes easier to analyze the microeconomic differences by getting a visual image of a concrete dispersion of the differences through two-dimensional topological maps.
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López, R.F. (2004). Effective Position of European Firms in the Face of Monetary Integration Using Kohonen’s SOFM. In: Chen, SH., Wang, P.P. (eds) Computational Intelligence in Economics and Finance. Advanced Information Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06373-6_9
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DOI: https://doi.org/10.1007/978-3-662-06373-6_9
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