<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The main aim of the paper was to analyse the economic and social development of the European Union (EU) member states (28 countries) on the basis of selected five multicriteria indices (the Global Competitiveness Index, the Economic Freedom Index, the Global Innovation Index, the Corruption Perceptions Index, the Human Development Index). To perform settled aim, a multidimensional classification of EU countries for years 2011 and 2018 using cluster analysis was realized. The purpose of the analysis was to categorize the individual EU countries into clusters and to find out to what extent the position of EU member states has changed in terms of selected international indices over the analysed period. Based on the findings, it is arguable that a major part of the EU member states cluster into the same groups based on the selected indices assessment, regardless of the time period. However, six countries (Czech Republic, Estonia, Germany, Latvia, Lithuania, and United Kingdom) improved their position during the period under review and ranked into the cluster of more prosperous countries in 2018. The rate of change (improvement) was quantified at the level of 21.43%. Based on the results, Latvia and Lithuania were the most similar countries in terms of economic prosperity (Euclidean distance reached the level of 3.08), while the least similar countries were Greece and Sweden (Euclidean distance reached the level of 70.8). Declining Euclidean distances indicate that economic disparities of the individual EU countries have decreased in the period under review. This paper aims at developing the research to find out how, besides hierarchy, we can analyse the EU member states from the perspective of various multicriteria indices. The four proposed clusters could be used as a starting point for future policy reforms, pointing to the weaknesses of various countries.</p></abstract>

The main aim of the paper was to analyse the economic and social development of the European Union (EU) member states (28 countries) on the basis of selected five multicriteria indices (the Global Competitiveness Index, the Economic Freedom Index, the Global Innovation Index, the Corruption Perceptions Index, the Human Development Index). To perform settled aim, a multidimensional classification of EU countries for years 2011 and 2018 using cluster analysis was realized. The purpose of the analysis was to categorize the individual EU countries into clusters and to find out to what extent the position of EU member states has changed in terms of selected international indices over the analysed period. Based on the findings, it is arguable that a major part of the EU member states cluster into the same groups based on the selected indices assessment, regardless of the time period. However, six countries (Czech Republic, Estonia, Germany, Latvia, Lithuania, and United Kingdom) improved their position during the period under review and ranked into the cluster of more prosperous countries in 2018. The rate of change (improvement) was quantified at the level of 21.43%. Based on the results, Latvia and Lithuania were the most similar countries in terms of economic prosperity (Euclidean distance reached the level of 3.08), while the least similar countries were Greece and Sweden (Euclidean distance reached the level of 70.8). Declining Euclidean distances indicate that economic disparities of the individual EU countries have decreased in the period under review. This paper aims at developing the research to find out how, besides hierarchy, we can analyse the EU member states from the perspective of various multicriteria indices. The four proposed clusters could be used as a starting point for future policy reforms, pointing to the weaknesses of various countries.

Categorization of the EU Member States in the Context of Selected Multicriteria International Indices Using Cluster Analysis

Faculty of Management, Department of Finance

Review of Economic Perspectives

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The main aim of the paper was to analyse the economic and social development of the European Union (EU) member states (28 countries) on the basis of selected...

Categorization of the EU Member States in the Context of Selected Multicriteria International Indices Using Cluster Analysis

Data publikacji: 18 wrz 2020

Zakres stron: 379 - 401

Otrzymano: 08 sty 2020

Przyjęty: 17 sie 2020

DOI: https://doi.org/10.2478/revecp-2020-0018

Słowa kluczowe
Cluster analysis, economic development, EU member states, international indices, multidimensional classification

© 2020 Erika Onuferová et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Categorization of the EU Member States in the Context of Selected Multicriteria International Indices Using Cluster Analysis

Data publikacji: 18 wrz 2020

Zakres stron: 379 - 401

Otrzymano: 08 sty 2020

Przyjęty: 17 sie 2020

DOI: https://doi.org/10.2478/revecp-2020-0018

Słowa kluczoweCluster analysis, economic development, EU member states, international indices, multidimensional classification

© 2020 Erika Onuferová et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
Cluster analysis, economic development, EU member states, international indices, multidimensional classification