Assessment of Sustainable Development Using Cluster Analysis and Principal Component Analysis

Magdaléna Drastichová; Peter Filzmoser

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Published: Jul 1, 2019

Authors

Magdaléna Drastichová

magdalena.drastichova@vsb.cz

VŠB-Technical University of Ostrava, Faculty of Economics, Department of Regional and Environmental Economics, Sokolská 33, 701 21 Ostrava, Czech Republic

Peter Filzmoser

peter.filzmoser@tuwien.ac.at

Vienna University of Technology, Institute of Statistics and Mathematical Methods in Economics, Wiedner Hauptstrasse 8-10, 1040 Vienna, Austria

Abstract

The European Union (EU) Sustainable Development Goals (SDG) indicator set replaced the EU Sustainable Development Strategy (SDS) in 2017. The selected indicators of this set were chosen for the analysis to classify the sample of the 28 EU countries along with Norway according to their performance in sustainability. In the selection of indicators, priority was given to the indicators reflecting the social dimension of SD, along with important representatives of the economic, ecological and institutional dimensions of SD generally. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) were applied to the data of 12 indicators in the period 2012- 2016. By means of the HCA, four clusters were created in each year of the period 2012-2016 using the indicator values of particular years and then using all the indicator values in all the monitored years for the general assignment of countries to particular clusters. According to changes in the assignment to particular clusters over the years, the sustainability of development and the path of SD in the examined countries are assessed. As regards the core countries of each cluster, cluster 1 includes the most developed EU countries and is thus evaluated as the best performing cluster. Cluster 2 including the least developed EU countries is evaluated as the worst performing cluster. Cluster 3 predominantly includes the transitive economies and it is evaluated as the second best performing cluster according to the indicators applied. Cluster 4 containing the Southern countries is assessed as the second worst performing cluster. From the shifts of countries that occurred between the years, the shift of Ireland from cluster 3 to cluster 1 in 2013 must be emphasised as the move towards higher sustainability. The shift of Slovakia and Hungary from cluster 2 to cluster 3 in 2013 is also evaluated as progress towards higher sustainability.

JEL Classification: Q01, Q50, Q51, Q54, Q56

Keywords:

European Union (EU), Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), Sustainable Development (SD), Sustainable Development Goals (SDGs)

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Drastichová, M., & Filzmoser, P. (2019). Assessment of Sustainable Development Using Cluster Analysis and Principal Component Analysis. Problemy Ekorozwoju, 14(2), 7–24. Retrieved from https://ph.pollub.pl/index.php/preko/article/view/5075

Assessment of Sustainable Development Using Cluster Analysis and Principal Component Analysis

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