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The use of classification models to identify factors differentiating the competitiveness of the EU-15 and EU-13 countries

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  • Agnieszka Kleszcz

Abstract

This paper reports on a study of the Global Competitiveness Index pillars, aiming to differentiate the European Union countries grouped by their accession year in terms of their competitiveness. A linear (regularised logistic regression) and nonlinear (random forests) classifiers are proposed, to model the relationship between multidimensional economic condition indicators and the country's group. The key discriminators of the competitiveness of the EU-15 (accession before 2004) and the EU-13 (accession in or after 2004) are obtained by analysis of feature importance in classification models. Upon study of 12 competitive indicators from the World Economic Reports (2007-2017 edition) we conclude that the highest disparities between the groups of countries can be observed in infrastructure. Innovation, market size and institutions are the next three most important differentiating factors. A major methodological contribution of the paper is the use of explainable statistical models for identifying key features differentiating groups of countries.

Suggested Citation

  • Agnieszka Kleszcz, 2023. "The use of classification models to identify factors differentiating the competitiveness of the EU-15 and EU-13 countries," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 13(1), pages 110-128.
  • Handle: RePEc:ids:ijcome:v:13:y:2023:i:1:p:110-128
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