The Position of the Visegrád Countries by Clustering Methods Based on Indicator Environmental Performance Index (original) (raw)

Hierarchical Clustering Based on International Sustainability Indices of EU Countries

Ekonomické rozhľady – Economic Review

The presented paper focuses on the possibility to group countries by the cluster method in terms of assessing the sustainable competitiveness of European countries. Our calculation is based on HDI (Human Development Index) and EPI (Environmental Performance Index) indices. We also tried to show the differences in HDI and EPI index of the Slovak Republic and the Netherlands. The aim of this paper is to evaluate the global competitiveness regarding the environmental economics model, considering all three levels: economic, social, and environmental. We measure the socio-economic dimension using HDI according to the health and education areas, then we measure the environmental dimension using EPI, which monitors the behaviour of countries in the field of human health protection and ecosystem protection. Our question is whether there is an appropriate classification for the development of these countries that could help to reduce the differences between the average countries and the EU 2...

Hierarchical Clustering of EU Countries Based on HDI and EPI Index

EDAMBA 2021 : COVID-19 Recovery: The Need for Speed : Conference Proceedings

The aim of this paper is to evaluate the global competitiveness regarding the environmental economics model, considering all three levels: economic, social, and environmental. We measure the socio-economic dimension using HDI (Human Development Index) according to the health and education areas, then we measure the environmental dimension using EPI (Environmental Performance Index), which monitors the behaviour of countries in the field of human health protection and ecosystem protection. This paper focuses on the possibility to group countries by the cluster method in terms of assessing the sustainable competitiveness of European countries. The question is whether there is an appropriate classification for the development of these countries that could help to reduce the differences between the average countries and the EU 27 average. The approach to this topic began with the question whether these countries, which have high values of economic growth, have a high level of EPI or HDI...

Clustering Poland Among Eu Countries in Terms of a Sustainable Development Level in the Light of Various Cluster Stability Measures

Folia Oeconomica Stetinensia

Research background: Recently in the context of taxonomy methods a lot of attention has been paid to the issue of stability of these methods, i.e. the answer to the question: do the groups that were created as a result of clustering really occur (the structure is stable), or did they appear accidentally. Purpose: The article is inspired by the Reviewers of the author’s previous publications on this subject and will be a summary of research to date which has followed two paths. On one hand, they recognize ways of measuring cluster stability proposed in the literature (e.g. Rozmus, 2017). On the other, they use these measures to cluster Poland among the EU members in terms of sustainable development level (e.g. Rozmus, 2019). Research methodology: The literature proposes a number of different ways for measuring stability. Theoretical considerations have also led to the development of computer tools for the practical implementation of the proposed ways to study stability. The practical...

Cluster Analysis of the EU-27 Countries in Light of the Guiding Principles of the European Green Deal, with Particular Emphasis on Poland

Energies

The article presents a cluster analysis of the EU-27 countries. The clusters were built to identify groups of countries similar to each other in relation to the set of Eurostat indicators from the Climate Change Drivers and Environment and Energy sections. During the research, tools of spatial information systems were used, such as cluster analysis, diagram maps, rasterization and the TSA method. ARIMA prediction models were also used. The research aims to verify our hypotheses. Particular attention was paid to Poland; therefore, it was verified whether the composition of the country’s energy mix translated into excessive emissions of pollutants in relation to other EU countries. Furthermore, the level of integration of energy markets in the European Union and its changes over time were examined. The authors also proposed a methodology to create detailed energy and climate strategies for designated clusters. The results of the presented research are particularly important in light o...

Measuring of Environmental Performance Index in Europe

The paper demonstrates how indices of Environmental Performance Index (EPI) is constructed through the calculation and aggregation of nine categories reflecting national-level environmental data. This study uses the most recent performance and trend data in order to consider the evaluation of indicators affected on Environmental Performance competitiveness in Europe. Selected methods of multivariable objects hierarchy and classification have been used in the study. A wide range of the most important and most often used Environmental Performance assessment indicators based on a basic systemic classification of environmental potential will also be presented. High correlation between Environmental Performance and Human Development Index suggested that the analyzed countries should improve environmental health and ecosystem vitality to improve the overall long-term sustainable development. In other words, improvement in the partial competitiveness of a country empowers growth in its long-term environmental competitiveness. This article attempts to detail a methodology for constructing an EPI for the country and based on the EPI scores, rank the states and demonstrate commendable achievement regarding the most effective indicators of environmental sustainability and development.

The Central and Eastern European Countries: A Cluster Analysis from a Bioeconomy Perspective

Timisoara Journal of Economics and Business

The bioeconomy is an area that encompasses more economic activities and is environmentally friendly and sustainable. Bioeconomy contributes to the economic development of a state by creating new jobs, expanding the business environment and making activities more efficient. In this context, the bioeconomy is an element of economic development that helps the Central and Eastern European countries (CEECs) to bridge the gap with the other countries in the west of the continent. The article aims to analyze the grouping of CEECs based on indicators specific to the bioeconomy, to highlight similarities or discrepancies between them. Moreover, we conduct this study in order to identify Romania’s position among CEECs in terms of specific bioeconomy indicators. The study is based on the European Commission’s Joint Research Center database for the bioeconomy indexes for these particular regions. We employed a hierarchical cluster method using SPSS software. The sample consisted of the 11 CEEC ...

Indicators of sustainable development performance: Case study of European Union countries

Croatian Review of Economic, Business and Social Statistics, 2016

A sustainable development strategy is an essential long-term strategy that aims to bring about a balance of three key policy factors: sustainable economic growth and economic and technological development, sustainable development of society based on social equality, and environmental protection with a rational use of natural resources. The sustainable development strategy is very complex and contains a large number of indicators, so one of the statistical methods that can be used for this complex problem is the I-distance method. It was created as a need to rank countries according to the level of socio-economic development and the problem was how to take advantage of all the indicators in order to calculate a synthetic indicator which would represent the rank. The I-distance method in this paper is used for the ranking of 18 countries of the European Union based on ten indicators that have been selected in accordance with the EU Sustainable Development Strategy. The used headline i...

The Dynamics of Changes and Spatial Differences in the Synthetic Indicator for Evaluating Environmental Performance in Poland: Current State

International Journal of Environmental Research and Public Health , 2019

Socioeconomic development and consumption are among the key drivers of environmental degradation. Legal measures and the appropriate funding are required to effectively protect the natural environment. The aim of this study was to analyze the dynamics of changes and spatial differences in the measures undertaken to protect and improve the quality of the environment. A set of indicators for evaluating environmental performance was developed and tested on Poland as an example. The relevant data are publicly available in statistical databases. Proposed indicators can be modified for use in other countries by incorporating country-specific characteristics. The environmental protection activities implemented in Polish voivodeships at the Nomenclature of Territorial Units for Statistics (NUTS) 4 level (counties) in three financial frameworks (2004–2006, 2007–2013 and 2014–2017) were analyzed against the base year (2003). A total of 27 variables divided into four categories were analyzed: (1) water and wastewater management and water conservation, (2) waste management and protection of the Earth’s surface, (3) air pollution and climate control, (4) nature conservation and promotion of pro-environmental behaviors. A Synthetic Indicator for Evaluating Environmental Performance (SIEEP) was developed based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Based on the arithmetic mean and standard deviation, the analyzed counties were divided into four typological classes reflecting the values of the SIEEP. The research showed that the implementation of environmental protection measures financed from public funds minimizes the negative impact of human activities on the environment. Positive changes in the values of the analyzed variables and a steady increase in the number of counties with high values of the SIEEP testify to the above.

Measuring Sustainable Development at the Lower Regional Level in the Czech Republic based on Composite Indicators

Measuring sustainable development is a highly significant issue as there is neither a unified set of indicators nor any preferred methodology on how to do it. This is despite continual attempts to evaluate entities from the point of view of sustainable development. The most problematic level according to sustainable development assessment seems to be the “lower” regional levels, such as LAU 1 (former NUTS 4) level. On one hand, there are usually at this level already serious problems with data availability, on the other, it is almost impossible to regularly perform detailed questionnaire surveys in all LAU 1 regions (77 districts in case of the Czech Republic), as it is done in cities. The aim of the paper is to decide how to assess sustainability at this level. Relevant indicators, although different from indicators used at the national or NUTS 3 level, with data available for all LAU 1 regions were selected. We succeeded in filling all the three pillars of sustainable development (economic, social and environmental) with a sufficient number of suitable indicators. For the first phase, cluster analysis was applied to find coherences among regions that are affected by similar problems. Composite indicators were then constructed in order to create a ranking of all 77 districts. Ranking was derived from this composite indicator approach. Ten composite indicators were constructed to test different methods of normalisation, weighting and aggregation. The results show the ranking of LAU 1 regions in the Czech Republic from the sustainability perspective, both including and excluding the capital city of Prague as an outlying district. A good interconnection between cluster analysis and constructed composite indicators can be seen; this is also supported by the discussion of the results.