使用聚类分析对选定的多标准国际指数中欧盟成员国的分类

IF 0.4 Q4 ECONOMICS
Erika Onuferová, Veronika Čabinová, Mária Matijová
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引用次数: 2

摘要

本文的主要目的是根据选定的五个多标准指数(全球竞争力指数、经济自由指数、全球创新指数、腐败感知指数和人类发展指数),分析欧盟(欧盟)成员国(28个国家)的经济和社会发展。为了实现既定目标,使用聚类分析实现了2011年和2018年欧盟国家的多维分类。分析的目的是将各个欧盟国家归类为集群,并了解在分析期间,欧盟成员国在选定的国际指数方面的地位发生了多大变化。根据调查结果,有争议的是,无论时间段如何,根据选定的指数评估,大部分欧盟成员国都属于同一组。然而,在审查期间,有六个国家(捷克共和国、爱沙尼亚、德国、拉脱维亚、立陶宛和英国)的地位有所提高,并在2018年跻身于更繁荣的国家群。变化率(改善)量化为21.43%。根据结果,拉脱维亚和立陶宛在经济繁荣方面最相似(欧几里得距离达到3.08),而最不相似的国家是希腊和瑞典(欧几里得距离达到70.8)。欧几里得距离的下降表明,在审查期间,个别欧盟国家的经济差距有所缩小。本文旨在开展这项研究,以了解除了层次之外,我们如何从各种多标准指数的角度分析欧盟成员国。拟议的四个集群可以作为未来政策改革的起点,指出各国的弱点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Categorization of the EU Member States in the Context of Selected Multicriteria International Indices Using Cluster Analysis
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.
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
10
审稿时长
38 weeks
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