The Green Economy in the Energy Transformation Process—Comparative Analysis of the European Union Member States

Abstract

The article mainly examines spatial diversification of the green economy in EU countries in 2014 and 2021 in the context of the energy transformation process. In the theoretical part of the work, the green economy concept, with reference to the conditions of the green energy, was analyzed. The research procedure used in the article is based on multidimensional comparative analysis. The empirical verification was conducted using green economy indicators that are published periodically by the OECD and Eurostat. Based on 21 indicators, a synthetic green economy index was designed for 27 EU member states. In the selected set of detailed indicators, those related to green energy economy played an important role. This approach allowed for the creation of rankings and comparisons between EU countries in 2014 and 2021, i.e., the implementation period of the Europe 2020 Strategy. In this period, the priority areas of EU development were: the low-carbon economy, including the use of renewable energy sources and improvement of energy efficiency, as well as the introduction of eco-innovation. Green energy should be the basis for the functioning of highly developed countries and socio-economic progress in the case of developing countries. Based on the analysis, a large discrepancy in terms of green economy was observed in the examined countries. Particular attention was paid to disproportions in the area of green energy. The average value of the synthetic measure of the green economy in the EU countries increased in the studied years from 0.4488 to 0.4529, which can be interpreted as a slight acceleration in the greening processes. The added value of the research presented in the paper and its novelty is the analysis of the current patterns of green transformation in EU member states, with particular emphasis on energy factors.

1. Introduction

In the conditions of global crisis, the concept of economic development is being redefined, and greater attention is being paid to new concepts of sustainable development [1]. The idea of sustainable development is multidimensional [2]. Contemporary concepts of economic growth and development increasingly emphasize the so-called environmental element [3,4,5]. This means that the country’s economic development and environmental protection should not be treated separately, but jointly [6,7]. This approach requires an effective use of available energy resources and entails the need to produce energy in such a way that the existence of future generations is not threatened by a lack of access to energy sources or by the devastation of the natural environment. According to the principle of sustainable development, the relationship between the use of energy resources and the economic growth of a particular country should mean a decrease in the negative environmental effects related to the exploitation of energy resources. A sustainable approach to the management of energy resources is an expression of their importance in the process of economic development, the limited nature of conventional energy carriers, and the negative effects of resource management on the natural environment and future development.

In the second decade of the 20th century, there is a visible tendency to eliminate the dependence of economic growth on the degradation of the natural environment. It assumes that further economic development can only occur within the limits of nature’s tolerance. Attention is drawn to the need for selective economic development, characterized by an increase in some areas and a decreasing role in others (e.g., the development of renewable energy carriers and moving away from the use of conventional energy carriers), increasing efficiency and coherence of action while ensuring the sufficiency of natural resources, including energy [8]. The vast majority of scientists believe that the material basis for the transition to a model of sustainable development is the formation and development of a specific eco-oriented sector in the structure of the economy—the green economy, which, is based on the use of clean resource-saving technologies [9]. The concept of the green economy is focused on the threats resulting from the expansive activity of humans, irreversibly destroying the natural environment and its limited resources. The use of the adjective “green” is a symbolic way of drawing attention to the need to protect the natural factor in the economy. Green economic growth may result primarily from the increasing promotion of sustainable energy and the energy mix by boosting the adoption of renewable energy. This type of policy assumes reducing the use of fossil fuels and switching to renewable energy sources, which is the basis of the energy transformation policy. Energy policy can currently be treated as actions taken by EU institutions and member states aimed at creating conditions for the development of an efficiently functioning energy sector, guaranteeing increased competitiveness and sustainable economic development, taking into account social and environmental aspects [10,11].

Many economic trends influenced the creation of the green economy concept. On the one hand, it was neoclassical economics and related environmental economics, and on the other—ecological economics and the economics of sustainable development, developing in opposition to traditional economics [12]. Among the concepts related to the pro-ecological transformation of the economy, a green economy is the broadest term in the aspect of its subject scope—it covers the low-emission economy, the circular economy, and the bioeconomy [4]. Numerous studies have emphasised the green economy as a superior alternative to conventional economic models. This includes improving human well-being, preserving natural resources, and reducing environmental risks. Furthermore, the green economy advocates for good governance and accountability as indispensable elements for achieving sustainable development [13,14].

The ongoing degradation of the environment caused by human activity drives many organisations to undertake large-scale initiatives counteracting environmental damages [15]. The idea of a green economy is currently one of the most important elements of development strategies in the European Union (EU) and in numerous international organizations [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]. The UE has been actively involved in building the concept of sustainable development. European Commission defined its approach to a green economy in an environmental action programme. The leading document from the perspective of the green economy became the Europe 2020 Strategy [32]. In this strategy, a number of specific documents related to the issue of greening the economy were developed [33]. According to the adopted assumptions, in 2050, the EU is to achieve zero net greenhouse gas emissions, and economic growth is not to depend on increasing resource consumption. It is assumed that Europe will become the first neutral continent in the world and thus implement the ideas of sustainable development. It should be emphasized that expert forecasts regarding the possibility of decoupling economic growth from increasing energy consumption are already confirmed by trends observed in some economies, especially in Sweden. Researchers have recently focused on the comparison of the status of green economy among countries and regions [3,34,35,36]. However, despite the growing interest in comparing the development level of the green economy among countries, the literature is still beset with two fundamental challenges [3]. First, no studies have a common theoretical understanding of the concept of a green economy, much less an agreeable measure for it [34]. Consequently, authors have piloted measures of the concept, through which they have assessed countries, advanced conclusions, and recommendations. The constraint of the extant literature is the number of studies assessing the green economy on a global scale.

Therefore, the issues raised in this article are important for several reasons. The first is to indicate the theoretical assumptions of the green economy concept and review the methods of its measurement. Observing and describing changes related to the green economy and energy transformation is currently one of the most important research topics, in particular at the interface of science and economic practice, because on the one hand, decision-makers need appropriate guidelines for methods of analysing the complex economy–environment system, while on the other hand, science requires conclusions and experiences in implementing practical changes. The difficulty in defining a general green economy model causes problems with its implementation in practice, including problems with measuring progress. The second reason is the assessment of the development level of the green economy in the EU member states and the related need to select indicators describing its individual areas, especially those related to green energy and energy efficiency. Green energy is a concept that has not been clearly defined. It is most often identified with energy produced from renewable energy sources. Its extraction is treated as an ecological, sustainable way of producing secondary energy, with a small environmental footprint. The development of green energy is a consequence of the increased public awareness of the negative effects of the energy and climate policies. Another important reason is that the programming documents and directives adopted in the EU, as well as preferences for the green economy under the new financial perspective 2021–2027, are of key importance for the further development of the community. Moreover, in the opinion of many experts, in the face of increasing climate change and the search for ways to achieve sustainable development goals on a global scale and in individual countries and regions, research on green economy is important and obvious [33]. The research is also justified by the increasing importance of energy policy and the strategic dimension of its impact on building a strong and competitive economy. An important reason for undertaking this research topic is also its relevance and importance for the modern world. Energy is an element that determines the existence of modern civilizations, being the basis for their functioning and development.

The main goal of the article is to present the spatial spatial diversification of the green economy in the EU countries in 2014 and 2021, including the green energy transformation. The energy transformation of the EU economy means moving away from the use of conventional energy carriers towards renewable energy sources, reducing energy consumption by increasing energy efficiency, and building a long-term competitive, socially inclusive, low-emission economy. The objects studied are 27 countries that, as the EU members, implement a common development strategy. Achieving the main goal requires setting specific goals. The first intermediate goal is to present the essence of the green economy concept and to analyze the economic, social, and environmental conditions that determine the measurement of the green transformation. The second indirect goal is to determine indicators in particular areas and create a synthetic green economy indicator as a tool for advancing the transformation towards a green economy to monitor its course over time and make international comparisons. The definitions of the green economy show the diversity of its areas and goals, measured by many variables. Therefore, the selection of variables and the creation of a synthetic indicator will enable the expression of the complexity of the green economy in a particular country in the form of one measure, which will greatly facilitate international comparisons and monitoring of the process over time. In the selected set of detailed indicators, those related to the green energy economy played an important role. The green energy indicators accounted for almost 30% of all indicators, so this effect on the values of green economy indices in countries was significant. The third intermediate goal is to assess the spatial diversity of the green economy in individual EU member states using a synthetic measure.

To be able to achieve the goal of the study, data were used and a multidimensional analysis was performed. The following research questions were posed: (1) How is the green economy defined in the literature, and which factors are indicated as important determinants of green transformation? (2) What is the development level of the green economy in the EU member states? (3) Have EU countries achieved progress in implementing the assumptions of a green economy in the financial perspective 2014–2021? Research on the identified problems is conducted from the perspective of social sciences, with particular emphasis on economics with reference to the European dimension. In this paper, statistical data used by the OECD and Eurostat to monitor the progress of the green economy were studied to examine the directions of green transformation of the EU member states. The OECD indicators regarding green transformation now constitute one of the most comprehensive databases in this scope. Statistics covering two periods (depending on data availability) were analysed: 2014 (initial data) and data from the last available year, usually 2021 (final data). In total, 21 indicators collected by OECD and Eurostat were analysed.

The article is divided into two parts. The first one, which is cognitive, descriptive, and explanatory, presents theoretical issues regarding the essence and conditions of the green economy and ways of measuring it. In the article, by characterizing the concept of the green economy and methods of its measurement, as well as discussing the results of other studies, an overview of the latest publications included primarily in the WoS and Scopus databases was presented. This allowed for a reliable review of the literature and a discussion of the current state of knowledge, using reliable sources. The article cited original definitions formulated by, among others, the OECD, UNEP, the World Bank, and other international organizations and many authors. The second part of the article was devoted to presenting the research method and discussing the research results. The empirical study enabled a multi-faceted analysis of the territorial differentiation of the green economy, including the transition to green energy in all EU member states.

2. Literature Review

2.1. The Concept of Green Economy

The concept of a green economy was formulated in the late 1990s. The authors of the concept of a green economy are economists D. Pearce, A. Markandya, and E. Barbier. This concept was already used in a report prepared for the British government in 1989 entitled “Blueprint for a Green Economy” [37]. This report was related to the new concept of sustainable development and the implications that this development may have for determining economic progress and formulating development policy and project-evaluation methods [33]. Subsequent editions of this report (“Blueprint 2: Greeninig the world economy” and “Blueprint 3: Measuring Sustainable Development”), published in 1991 and 1994, expanded the original thematic scope to include global environmental problems such as climate change, depletion of the ozone layer, devastation of tropical forests, degradation and loss of natural resources in developing countries, etc. [38].

However, the term green economy was popularized in 2008 by the United Nations Environment Program (UNEP), which resulted in the Green Economy Initiative (GEI) [39,40]. The GEI adopted a working definition of the green economy as one that contributes to improving human well-being, while significantly reducing ecological risk and the consumption of natural resources. Moreover, in 2009, a report was prepared entitled “Global Green New Deal” [41], which considered not only environmental aspects but also referred to the search for ways to combat the global economic crisis. It was then recognized that the existing framework for shaping socio-economic development required modification due to the structural conditions of economies that had not resisted the crisis, as well as due to the challenges of ongoing climate change.

The increase in interest in the green economy also occurred in preparation for the UN Conference (Rio+20) devoted to sustainable development, which was organized in 2012. During the Rio+20 Summit, the necessary redefinition of the economy and the adoption of a new model of socio-economic development were indicated, with particular emphasis on the environmental aspect [42,43]. The aim was to reconcile the goals of the global [44]. During the preparations for the Rio+20 Summit, the European Commission defined a green economy as ”an economy that generates growth, creates jobs, and eradicates poverty by investing in and preserving the natural capital” [45,46].

In the EU, the leading document from the point of view of the green economy was the Europe 2020 Strategy [32]. The central element of this strategy was supporting sustainable development in all areas of the economy, environment, and social life [39]. The Europe 2020 Strategy and the initiatives and programs proposed under it, including the flagship initiative “Roadmap to a Resource Efficient Europe” [47] and “A Roadmap for moving to a competitive low-carbon economy in 2050” [48], confirm that the greening of the EU economy is perceived as a double dividend mechanism. Sustainable development of the community should be achieved by shifting the economy to a low-emission and resource-efficient path.

There is no single comprehensive definition of the term green economy in the literature on the subject [13,49,50,51,52]. Two other concepts are closely related to it—green growth and sustainable development. Nevertheless, M. Adamowicz [33] points out that the notion of the green economy refers to the state and structure of the economy, its nature, and its way of functioning, while the term green growth has a dynamic character and refers to the use of green production factors to increase economic effects, which can be used to accelerate development processes [4,53]. The concept of green growth can be useful in formulating green transformation policies.

One of the most widely cited definitions of the green economy was proposed by UNEP. According to UNEP, a green economy increases people’s well-being (indirectly affects the increase in quality of life) and ensures social equality (reduces inequalities, stimulates integration, and social justice). At the same time, it contributes to reducing environmental risk, reducing the consumption of natural resources, and providing fair access to manufactured goods. Moreover, UNEP indicates that the increase in income and employment in the green economy is the result of investments aimed at reducing CO₂ emissions and various types of pollution, strengthening the existing energy efficiency, and increasing the level of resource use (reducing waste in the production process), as well as preventing the loss of biodiversity and ecosystem functions [54].

This widely cited definition was the inspiration for many other similar descriptions proposed by various international organizations and research centers. When considering the issue of the green economy, one should be aware of a certain stage on the way to its creation, according to the UNEP definition. In the document entitled ”Towards a Green Economy” [54] the stages of implementation of the green economy are described, by identifying green investments focused mainly on the supply and sustainable use of natural capital and energy.

Economic development is structurally linked to policies that protect natural [55]. Therefore, a green economy is understood as a path of economic development that will permanently consider environmental constraints and criteria. Many researchers recognize the green economy as a way to operationalize the concept of sustainable development in relation to the economic sphere [3,41,56]. However, where sustainable development postulates for long-term implementation of development processes in a society-economy-environment macrosystem, the green economy focuses on the relations between the economy and the environment. Having said that, similarly to the concept of sustainable development itself, it is by no means a set of fixed rules [38], and its essence is to pinpoint courses of action that might smoothen the sensitization of an economy to environmental constraints, as well as to suggest a pathway as to how that goal might be best achieved [40].

The definition proposed by the OECD [57] defines green economy as growth that not only supports “green” management but also helps in striving for sustainable development by ensuring environmental sustainability and maintaining the conditions for continuing social progress. Most used is the OECD’s definition: the economy that contributes to the improvement of human well-being and social equality, while significantly reducing the ecological risk and consumption of natural resources [38]. The concept of a green economy includes three elements: elimination of environmental threats, rational management of resources and natural raw materials, and social inclusion and economic efficiency [39,58]. Moreover, the idea of a green economy takes into account the high level of life of the population and the rational use of natural resources in the interest of current and future generations [59].

Considering the above, it should be emphasized that a green economy should improve human well-being, increase social justice, and reduce environmental risk and the consumption of natural resources. Therefore, the notion of a green economy can have two meanings: narrow and broad. And so green economy [42]:

• In a narrower sense, these are areas directly related to the protection of the natural environment,
• In a broader sense, it also covers sectors that have an indirect impact on the natural environment.

For the purposes of this article, the green economy is understood in this narrower sense in the context of the relationship between the economy and the environment. This approach was confirmed in the study of Khoshnava’s et al. [60]. There are definitions that define green economy as a new stage of the civilization process. The elements of this process include respecting the planet’s boundaries and limiting aggressive economic and environmental expansion, which actually threaten the quality of life of people and entire ecosystems [12].

From the point of view of this article, it is important to present the opinion of the European Commission. The green economy can also be viewed as a set of principles, aims, and actions, which generally include [61]:

• Consistency with the principles of sustainable development,
• An appreciation of natural and social capital,
• Sustainable and efficient resource use, consumption, and production.

The main goals of the green economy include [42]:

• Improving social well-being, striving for equality in society, reducing shortages, and reducing environmental risks,
• Efficient use of resources, reduction of carbon dioxide emissions, and social responsibility,
• Increasing public funds allocated to combating carbon dioxide emissions, as well as creating green jobs,
• Strong commitment to energy efficiency and biodiversity.

Moreover, it should be pointed out that one of the main goals of the green economy concept is to integrate the concept of economic growth and development with the efficiency of the use of natural resources [62]. Green growth was recognised as an alternative to the traditional way of recovering from economic recession [33]. Green growth aims to support economic growth and development considering ensuring the protection and conservation of natural resources and environmental services [4]. A. Atkisson emphasizes that green growth is a tool for implementing a green economy, and a green economy is one of the important elements of sustainable development [12,63].

Therefore, when discussing terminological issues in the context of the green economy, the terms green growth and inclusive green growth cannot be omitted. According to the OECD [57], green growth means “fostering economic growth and development while ensuring that natural assets continue to provide the resources and environmental services on which our well-being relies”. The inclusive green economy refers to social inclusion in development processes. Moreover, it assumes limiting the differences between developed and developing countries in terms of the level of labor productivity and access to knowledge and technology [64,65]. The concept of green growth grew out of the interest in greening issues by institutions such as the OECD, the World Bank, and the Global Green Growth Institute (GGGI) [33]. The OECD mainly refers to the concept of green growth. According to the OECD [57], green growth means striving for economic growth and development while preventing environmental degradation, loss of biodiversity, and irrational use of natural resources.

Green growth is connected with changing the production and consumption model to reduce pressure on the environment in an economically effective way. It involves taking actions to support economic growth and development while ensuring the constant availability of natural capital and ecosystem services. Green growth leads to the separation of the effects of economic activity from the effects of environmental activity. This concept emphasizes the importance of investing in the environment as a driving force for economic growth. As a result, green growth aims to achieve a green economy state that ensures harmony between the economy and the environment. Green growth is both the rapid growth of green industries and the “de-growth” of carbon-intensive industries that drive green economic growth [66,67].

The World Bank also refers to the concept of green growth in its documents. The World Bank defines green growth as “growth that is efficient in its use of natural resources” [65]. According to the Global Green Growth Institute (GGGI), green growth is a revolutionary new development paradigm [68]. The concept of a green economy is linked to the concept of sustainable and balanced development [13,31,33,69,70]. Practical implementation of the concept of sustainable development began to be treated as a perspective for a radical transformation to the green economy [58,60,67,71]. Currently, many experts emphasize that the green economy is the practical implementation of the concept of sustainable development, which has not yet been sufficiently reflected in practice [52,72,73].

It can be assumed that one of the paths to sustainable development is the concept of a green economy. Its advantage is greater specificity and operationalization of sustainable development. In other words, a green economy makes it possible to achieve a sustainable economy [42]. The concept of a green economy focuses on economic processes and the adjective “green” suggests the presence of ecological criteria. A new aspect of defining a green economy is to include social references and values. Greenness means considering environmental aspects in every decision and production process throughout its entire cycle, as well as respect for the natural environment and its resources, the desire to protect these resources for future generations, i.e., intergenerational justice, and access to these resources on a global scale. The axiological aspects, including among others, respect for the natural environment, respect for the needs of other generations, ethics, trust, and responsibility, make the concept of a green economy multidimensional (economic, social, and ecological dimensions) [12]. The green economy expresses all three aspects of sustainable development: economic, social, and ecological. This new development path is oriented towards new forms of qualitative rather than quantitative growth in the face of growing threats to natural and social capital.

2.2. The Measurement of the Green Economy

Measuring the implementation of the green economy is currently of interest to both researchers and practitioners [25,74,75,76,77,78,79,80,81]. The number of models presenting internal relationships between green economy areas is growing. Issues related to the selection of appropriate indicators and the selection of analytical methods allowing for conducting multidimensional comparative analyses in the situation of the complexity of the considered development problems are also becoming more and more important. The result is the number and complexity of the proposed measurement approaches and their numerous modifications, including those based on various types of international policies [4].

According to the OECD [57], green growth policies aim to support economic development and people’s living standards through the conservation and proper use of natural capital, i.e., natural resources and ecosystems that influence well-being. These policies should be based on a good understanding of the drivers of green growth and their interconnections. Considering policies also need appropriate indicators to monitor progress and evaluate results, which should meet the following criteria [4]:

• Policy relevance—the indicator should take into account issues that are of public interest and are important for policy-making,
• Analytical validity—ensuring that the indicator is based on the best available knowledge,
• Measurability—indicators must enable seasonal comparison both in time and space (in the countries or regions under study),
• Usefulness in communication—the ability to provide understandable, easily interpretable signals to target recipients.

E. Sidorczuk–Pietraszko [40] indicate that the methods used to measure the green economy are largely consistent with the issue of measuring sustainable and socio-economic development. This applies both to the selection of measurement methods and methodological problems regarding their use. Based on research on measuring sustainable and socio-economic development, four groups of measurement methods have been developed: (1) dashboards of indicators, (2) composite indicators, (3) environmental footprints, and (4) adjusted monetary measures. This classification is confirmed, among others, by the work of J. Stiglitz, A. Sen, and J. Fitoussi on measuring socio-economic development [82], or methodological works on measuring sustainable development [83] and the green economy [84,85].

In the area of the green economy, which presents the relationship between the economy and the environment, mainly sets of indicators and aggregate indicators are used. Green economy indicator sets (dashboards) have been. The most well-known and applied set of indicators is the one created by the OECD. The main areas covered by the indicators are [86]:

• Environmental and resource productivity—describe the connections between the natural environment and the economy,
• Natural asset base—is related to the state of the natural environment,
• Environmental dimension of quality of life—describe the connections between the natural environment and society,
• Economic opportunities and policy responses—is related to the instruments of impact on the economy and society,
• Socio-economic context.

The use of multiple indicators creates a complex picture of the situation but does not make it possible to use a single measure of comparison and ranking of countries. Therefore, another proposal for assessing progress in implementing green economy priorities is complex indicators [40]. These indicators make it possible to compare countries, combine them into groups with a similar level of advancement, and adapt separate action programs appropriate to individual groups of countries. The key element of the construction of such indicators is the procedure for selecting variables (partial indicators) and characterising the green economy. Synthetic indicators can include many different states and processes, expressed in various units, including qualitative indicators, which allows for a broad approach to the phenomenon under study. The most well-known indicators of this type, in relation to the goals and requirements of the green economy, are [30,31]:

• Global Green Economy Index™ (GGEI)—is published by Dual Citizen LLC, a private U.S.-based consultancy; measures the green economy performance of 160 countries across 18 indicators; is defined by four key dimensions: climate change and social equity, sector decarbonization, markets and ESG investment, and environmental health; was the first green economy index, launched in 2010 [87],
• Green Economy Index (GEI)—prepared by A. Nahman, B. Mahumani, and W. de Lange; is based on a number of indicators reflecting green economic principles and criteria across the economic, social, and environmental dimensions, of relevance to both developed and developing countries [85],
• Green Economy Progress Index (GEPI)—developed as part of Partnership for Action on Green Economy (PAGE); captures multi-dimensions of an Inclusive Green Economy; includes measurements of accumulation of capital—natural, low carbon, and resource-efficient, human or social—which serves as input for producing goods and services in an environmentally friendly manner [84,88,89],
• Green Growth Index (GGI)—prepared by Global Green Growth Institute; is a composite index combining green growth indicators from four dimensions—efficient and sustainable resource use, natural capital protection, green economic opportunities, and social inclusion; the green growth indicators are benchmarked against sustainability targets, including Sustainable Development Goals (SDGs), Paris Climate Agreement, and Aichi Biodiversity Targets [90],
• Green Economy Index—by B. Ryszawska; was calculated for the first time in 2013 and illustrates the positions of individual countries in the process of transition to the green economy based on data for 27 EU member states [12].

Composite indicators have different purposes. The index developed by PAGE focuses on progress (comparing green economy activities between countries, measuring progress on selected sustainable development goals, and measuring the achievement of national green economy priorities). The remaining indicators concern the level of advancement in the transition to the green economy and comparisons between countries. In the construction of all indicators, various types of multidimensional comparative analysis were used while considering the general assumptions described by Z. Hellwig [91,92,93].

In contrast, the UNEP proposed a different approach to monitoring the green economy. The UNEP does not adopt an arbitrary set of indicators but proposes a certain methodology for creating systems of such indicators. It was assumed that individual countries should develop their own monitoring systems adequate to specific conditions. In addition to typical environmental and social indicators, the UNEP also proposed indicators assessing initiatives undertaken by governments supporting the green economy. The proposed set of indicators covers three areas. The first are indicators assessing the state of the environment, threats, and positive trends, as well as measuring progress towards a specific environmental goal. The second are indicators showing the effect of actions taken by state governments, i.e., assessing the effectiveness of state policy. The third area concerns the impact of the green economy on the quality of people’s lives and the problem of social inequalities [12,94].

• The indicators related to the green economy and green growth are also collected and published by the European Environmental Agency (EEA). The EEA is one of the largest research institutions in the world that sets standards for diagnosing and measuring environmental problems. According to the EEA, the broadly understood concept of a green economy recognises that ecosystems, the economy, and human well-being are intrinsically linked [95]. In the process of selecting indicators, the EEA relies on its own developed method for measuring environmental problems, which includes a set of indicators abbreviated as DPSIR. The name of the DPSIR model is an acronym of the words: driving forces, pressures, state, impact, and responses [95]:
• D—Driving force indicators—describe socio-economic development, related changes in lifestyles and levels of consumption and production; the main driving forces are demographic changes and economic activity (energy consumption and transport development),
• P—Pressure indicators—describe emissions of greenhouse gases and other pollutants into air and water, resource use, and land use; indicate a change in environmental conditions and a reduction in the quantity and quality of environmental resources,
• S—State indicators—provide a comprehensive assessment of the state of the environment, describe quantitative and qualitative phenomena (e.g., temperature, concentrations of pollutants in the air or water), biological phenomena (species and habitats),
• I—Impact indicators—describe the importance of changes in the natural environment and their impact on ecosystems, the economy, human well-being, and health,
• R—Response indicators—describe the reaction of society and politicians to environmental problems and actions leading to limiting or eliminating negative pressure on the environment, stopping degradation, or adapting to the state of the environment (equipping vehicles with catalytic converters, taxes, and environmental fees).

Green economy indicators have a specific character because they should express and reflect several spheres of people’s lives, economic, social, and environmental, and show the connections between them. Moreover, these indicators should be proportionate and representative of the fundamental aspects of greening the economy.

3. Materials and Research Methods

The research procedure applied in the article relies on a multifaceted comparative analysis (MCA), in which the main criterion for assessing the studied phenomenon is an aggregate measure constructed on the basis of partial information contained in individual indicators. MCA is especially predisposed to explore complex phenomena described by many variables [12,58,96,97,98,99,100,101,102,103,104,105,106]. One division of multifaceted comparative analysis is the so-called taxonomic methods [107,108,109,110]. The article presents a multidimensional comparative analysis of 27 EU member states based on a set of diagnostic features relating to the green economy. The study using the MCA method included several stages:

• Conceptualization of the research—defining the subject and purpose of the study,
• Identification and selection of indicators,
• Normalization of indicators and weighting of indicators,
• Construction of the synthetic measures of development level for each distinguished group of indicators,
• Linear ordering of examined objects according to the level of measures achieved.

As part of the first stage of research, preparatory work was conducted, including critical analysis of the literature and strategic documents in the field of the green economy. The result of this stage of the proceedings was the diagnosis of a research gap regarding the recognition of the development level of the green economy in the EU member states and the development of a list of factors (conditions) that are most important for the development of the EU countries within the green economy.

The second stage of the research concerned the selection of variables for measuring green economy in EU member states. The procedure for selecting variables for measuring green economy is a key element in the construction of the synthetic indicator. The selection of variables was a multi-stage process based on several criteria [12,31,58,83,111,112,113]:

• The starting point was a set of green economy indicators published by OECD and Eurostat,
• Importance from the perspective of the analyzed problem, representativeness, and coherence in covering individual aspects of the green economy—indicators correspond to the definitions of the green economy and the areas selected for study (indicators most fully reflect various aspects of the green economy, expressed in its definitions),
• Availability of statistical data for all surveyed countries, including time availability (completeness for all countries, reliable sources)—the data covered 2014 and 2021,
• Indicators are relatively independent (no deterministic cause-and-effect connections)—a number of variables were excluded due to mutual correlation.

The starting point for the selection of variables was the analysis of the definitions of the green economy, as a result of which the most important keywords were indicated. In the next step, common topics (areas) were determined, and individual keywords were matched to these topics. Based on the selected keywords and topics, a conceptual model of green economy was developed. The proposed model shows the most important areas, variables, and the relationships between them.

For the analysis of the green economy in the EU member states, statistical data were initially collected on 123 variables (indicators) divided into three main areas (according to the classification adopted in the Green Growth Database OECD): first—environmental and resource productivity of the economy (51), second—environmental quality of life (25), and third—economic opportunities and policy responses (47). The spatial scope covered 27 EU countries, while the temporal scope was between 2014 and 2021.

Diagnostic variables were recorded as an observation matrix. It was written as X_ij:

$${\mathrm{X}}_{\mathrm{i}\mathrm{j}}=\begin{array}{cccc}{\mathrm{x}}_{11}& {\mathrm{x}}_{12}& \dots & {\mathrm{x}}_{1\mathrm{m}}\\ {\mathrm{x}}_{21}& {\mathrm{x}}_{22}& \dots & {\mathrm{x}}_{2\mathrm{m}}\\ \dots & \dots & \dots & \dots \\ {\mathrm{x}}_{\mathrm{n}1}& {\mathrm{x}}_{\mathrm{n}2}& \dots & {\mathrm{x}}_{\mathrm{n}\mathrm{m}}\end{array}$$

where:

• x_ij—denotes the values of the j-th variable for the i-th object, matrix of dnaych objects,
• i—object number (i = 1, 2, …, n),
• j—variable number (j = 1, 2, …, m).

After defining and collecting data describing the initial set of features, this set was subjected to selection. In the current publications on the use of taxonomic methods to order linearly, organize, and classify multi-feature objects, a determined approach is taken. According to this approach, when selecting the initial set of diagnostic features, two criteria for assessing the information value of the examined features are most often considered: variability and their mutual correlation. It was assumed that the features selected for the study should be characterized by appropriate variability, which would ultimately allow for effective discrimination of the examined objects. In practice, this means the elimination of features characterized by too low a coefficient of variation value, which is lower than or equal to a certain arbitrarily set threshold value, most often set at 0.1 (10%). According to this approach, features for which the coefficient of variation is less than or equal to a particular threshold value are considered quasi-constant (these are features with low variability in the set of realizations) and are eliminated from the set of potential diagnostic features.

Moreover, the initial set of variables was verified, considering their mutual correlation. The set of potential diagnostic variables was reduced by eliminating features that were highly correlated with other diagnostic features. The Pearson correlation coefficient was used for this purpose. Within the OECD database, numerous issues are described by several variables that are necessarily correlated with each other. Verification allows for the selection of variables with the greatest discriminatory ability, i.e., to identify differences between objects. Next, each of the analyzed features was assigned the symbol x_ij, where i—means the number of the dimension in which a particular feature is introduced, and j—is the number of this feature. The influence of each of these features on the analyzed phenomenon was also indicated by qualifying it to a set of features that stimulate development in a particular area (symbol S) or destimulating this development (symbol D). A detailed list of 21 indicators used in the study, divided into three indicated areas, is presented in

Table 1. The list of diagnostic indicators describing the green economy.

Symbol	Indicator Name	Source
Indicators in the field of environmental efficiency of production describe the efficiency of the use of natural resources in economic processes
CO2 Productivity
x11S	Production-based CO2 productivity, GDP per unit of energy-related CO2 emissions	OECD
x12D	Greenhouse gas emissions from production activities, kilograms per capita	Eurostat
Energy productivity
x13S	Energy productivity, GDP per unit of TES	OECD
x14S	Energy intensity, TES per capita	OECD
x15S	Renewable electricity generation, % of electricity generation	OECD
x16D	Primary energy consumption, tonnes of oil equivalent (TOE) per capita	Eurostat
Non-energy material productivity
x17S	Non-energy material productivity, GDP per unit of DMC	OECD
x18S	Resource productivity (GDP/DMC), Euro per kilogram	Eurostat
Indicators related to the environmental quality of life refer to population access to basic water and wastewater management services (that also serve to protect the environment and population). These indicators point out how environmental conditions affect the quality of life and well-being of the population
Exposure to environmental risks
x21D	Population exposure to PM2.5, micrograms/m3 (μg/m3)	OECD
x22D	Population exposed to more than 10 micrograms/m3, % of population	OECD
x23D	Mortality from exposure to lead, deaths per 1,000,000 inhabitants	OECD
Access to drinking water and sewage treatment
x24S	Population with access to improved drinking water sources, % of population	OECD
x25S	Population with access to improved sanitation, % of population	OECD
Noise
x26D	Population living in households considering that they suffer from noise, % of population	Eurostat
Indicators in the area of economic policies and their consequences describe the instruments of influence on the economy and society, which are used to achieve the desired directions of development aimed at greening the economy. These indicators relate to the effectiveness of policies in ensuring green growth and social reactions to the conditions for conducting business and maintaining employment
Technology and innovation. Patents
x31S	Development of environment-related technologies, inventions per 1,000,000 inhabitants	OECD
x32S	Relative technological advantage in environment-related technologies, index	OECD
x33S	Patents in environment-related technologies granted in % of total patents granted by the European Patent Office per capita	OECD
x34S	Eco-innovation index	Eurostat
Environmental taxes and transfers
x35S	Feed-in tariffs for solar photovoltaic, US dollars per kilowatt hour	OECD
x36S	Feed-in tariffs for wind electricity generation, US dollars per kilowatt hour	OECD
Ecological farms
x37S	Organic agricultural area in % of total agricultural area	Eurostat

Source: own elaboration based on OECD and Eurostat data.

.

In a multidimensional comparative analysis, it is important to transform the diagnostic variables and normalize the values of the variables considered in a specific range. Ratio transformation is recommended as one of the norming methods [98,114]. This formula ensures, among others, normalization of all selected variables in the range <0, 1>. It is worth emphasizing that the ratio transformation “maintains the proportions between all feature values” [115]. Therefore, in the third stage of the research, normalization of individual variables was conducted. For this purpose, a quotient transformation was performed according to the quotient formula, which [116]:

• For stimulants, variables for which high values are most desirable takes the form:

$${\mathrm{z}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{{\mathrm{x}}_{\mathrm{i}\mathrm{j}}}{{\mathrm{x}}_{\mathrm{i}\mathrm{j} \mathrm{m}\mathrm{a}\mathrm{x}}}}$$

x_ij—the value of the jth variable for the ith object

• for destimulants, variables for which low values are most desirable takes the form:

$${\mathrm{z}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{{\mathrm{x}}_{\mathrm{i}\mathrm{j} \mathrm{m}\mathrm{i}\mathrm{n}}}{{\mathrm{x}}_{\mathrm{i}\mathrm{j}}}}$$

The third stage also includes weighing diagnostic features. This is a particularly important step in the case of features describing the structure of objects that have different meanings. Nevertheless, the study assumed that all analyzed dimensions of the green economy have the same meaning and are equally important. The literature on the subject indicates that the introduction of weights and the decision on the method of introducing them depend on the nature of the phenomenon under study, the adopted criterion or criteria for analysis, and the size of the set or sets of diagnostic features [117,118,119]. This is an optional stage, and the decision to enter weights and choose the method of determining them depends primarily on the researcher. Therefore, it was decided that omitting weighting and using equal weights would provide comparable results for the analyzed dataset. This is confirmed by the recommendation of X. Gan et al. [120], who recommended the use of equal weights as the most universal weighing method in terms of spatial and temporal scale and the possibility of comparison.

As part of the fourth stage of research, to build a taxonomic measure of the green economy development, a template-free formula for estimating the value of a synthetic variable (aggregation of variables) was used in accordance with the following formula [121]:

$${\mathrm{q}}_{\mathrm{i}}=\sum _{\mathrm{j}=1}^{\mathrm{m}}{\mathrm{w}}_{\mathrm{j}}{\mathrm{z}}_{\mathrm{i}\mathrm{j}}$$

where:

• q_i—resulting value of the synthetic variable,
• w_j—weight of the j-th diagnostic variable,
• z_ij—normalized value of the j-th variable for the i-th object,
• i = 1, 2 …, n,
• m—number of diagnostic variables,
• n—number of objects.

In the patternless method, the synthetic variable is a function of the normalized values of the input variables. The basis for the analyses conducted as part of this stage of the research was a list of m potential diagnostic features, which were then used to linear order n objects within the green economy area. The objects were ordered linearly according to the value of the designated green economy development measure (stage six).

Multi-criteria taxonomy was used in the research. Specific taxonomic analyses for each of the three criteria (areas) considered were conducted. Then, the obtained results were combined within one criterion, which can be treated as a kind of “super-criterion” [118,122]. The results obtained for individual criteria were related using the arithmetic mean [123,124]. Moreover, each of the synthetic measures was treated as a separate criterion, and, on this basis, a separate taxonomic analysis was conducted [107].

The synthetic variable qi takes values from the range <0, 1>. The values closer to 1 pointed to a relatively higher level of the green economy. The estimated synthetic measures allow for a comparative analysis of the EU member states to be conducted in 2021, in comparison to the base year.

Using the criterion of decreasing values of synthetic indicators, the EU countries were ordered according to level:

• Development of the green economy,
• Environmental efficiency of production,
• Environmental quality of life of the population,
• Economic policies and their consequences.

In the final stage of the research, the UE member states in terms of a synthetic measure for green economy were grouped. Four classes were determined using the mean (d) standard deviation (s). In the first quartile group, you can find the most developed UE countries. In the last one, you can find the least developed (due to the measure of the green economy). The grouping was made according to the formulas [35,78,122,125]:

• Group 1—The EU member states with a high level of development: q_i ≥ d + s,
• Group 2—The EU member states with a medium-high level of development: d ≤ q_i < d + s,
• Group 3—The EU member states with a medium–low level of development: d − s ≤ q_i < d,
• Group 4—The EU member states with a low level of development: q_i < d − s.

4. Research Results and Discussion

The interpretation of the results obtained is not a simple process. The literature emphasises that the leaders in terms of the green economy are the Scandinavian countries (Denmark, Norway, and Sweden), or in a broader sense, the Nordic countries (including Finland), which have managed to separate economic growth from the negative environmental impact of human activity. According to the results of the research of O. Rybalkin [28], Sweden became the leader of the list of the EU member states, considering the EEPSE Green Economy Index in 2020. The top seven countries also included the United Kingdom, Denmark, Germany, Finland, France, and the Netherlands. At the same time, the list of worst performers in the ranking embraced Poland, Bulgaria, Cyprus, Hungary, and Romania. These results are very close to those obtained by A. Kasztelan [30], who used an artificial assessment score derived from the green economy indicators in EU member states between 2000 and 2018. During this period, a decrease in the mean Green Economy Index for EU member states was noted, which should be interpreted as a step backwards in the green transformation of Europe. Out of 28 countries (including the United Kingdom), those that scored the highest for the green economy were Denmark, Austria, Sweden, France, and the Netherlands, and those that scored the lowest were Bulgaria, Hungary, and Romania.

Moreover, V. Pceļina et al. [126] analysed and compared the dynamics of green economy development in the EU member states in the period from 2015–2019. In 2015, Austria, Sweden, Denmark, Slovenia, and the Netherlands had the highest overall index for the green economy trends, while Germany, Luxembourg, Hungary, Poland, and Romania had the lowest overall index for the green economy trends. In 2019, Denmark, Italy, the Netherlands, Slovenia, and Sweden had the highest overall green economy trend index, while the Czech Republic, Germany, Cyprus, Hungary, and Poland had the lowest index. So, after 4 years, the polarisation of the Green Economy Index values increased in the EU countries. Therefore, V. Pceļina et al. [126] concluded that disparities in the Green Economy Index in EU member states do not decrease but increase.

However, according to research conducted by K. Cheb et al. in the years 2005 and 2019 [78,127], the green transformation takes a different form in the individual EU countries. The best situation in terms of the green economy occurred in three northern European countries: Ireland, Sweden, and Finland. In the same year, at the end of the ranking were Belgium, the Netherlands, and Malta. However, when analysing the green economy in 2019, it should be noted that both the top three EU member states in the ranking, and the last one, have been slightly modified. Sweden and Finland continue to top the ranking, with Sweden moving up one position (from 2 to 1). Ireland, first in the 2005 ranking, 14 years later, has dropped to fifth position, and Denmark has entered the top three (in the third position), having risen from 16th position in 2005. Belgium (one position up compared to 2005) and Malta (down two positions) are again in the last positions in the 2019 ranking. The Netherlands improved its position considerably, rising from 27th place in 2005 to 16th in 2019, while Bulgaria, which ranked 24th 14 years earlier, came in third from bottom.

And A. Kantor assessed green growth in the EU member states in 2019 [35]. She presented the calculated taxonomic values of the green growth by three groups. On this basis, three groups of countries were distinguished. The group that reports a high level of sustainable development includes three countries: the United Kingdom, Denmark, and Ireland. Meanwhile, 16 of the surveyed countries have an average level of development: Sweden, France, Luxembourg, Lithuania, Latvia, Austria, Estonia, Spain, Finland, Slovenia, Portugal, the Netherlands, Germany, the Slovak Republic, Italy, and Belgium. There are four countries with the lower level of development group: the Czech Republic, Poland, Greece, and Hungary.

The conclusions from previous studies on the green economy in EU member states presented above partially correspond to the results of our research. These discrepancies can be attributed to different time periods and methodologies. As a result of the research procedure, the spatial diversity of the EU member states in 2014 and 2021 was presented due to the level of the synthetic measure of the green economy (

Table 2. Development level of the green economy in the EU member states according to the general indicator in 2014 and 2021.

EU Member States	Value of the Indicator		Increase (+)/Decrease (−)	Ranking Position		Position Change in 2021 in Relation to 2014
	2014	2021		2014	2021
Austria	0.5482	0.5624	+	5	4	1
Belgium	0.4137	0.4153	+	17	16	1
Bulgaria	0.3659	0.3897	+	24	21	3
Croatia	0.4520	0.3916	−	11	19	−8
Cyprus	0.3784	0.3652	−	22	25	−3
Czechia	0.3764	0.3809	+	23	23	0
Denmark	0.5576	0.5477	−	4	6	−2
Estonia	0.4309	0.5371	+	13	7	6
Finland	0.6059	0.6447	+	1	1	0
France	0.4834	0.4409	−	9	11	−2
Germany	0.4958	0.5296	+	8	8	0
Greece	0.4200	0.3738	−	14	24	−10
Hungary	0.3558	0.4053	+	25	17	8
Ireland	0.4497	0.4751	+	12	10	2
Italy	0.4994	0.4816	−	6	9	−3
Latvia	0.4145	0.4256	+	16	15	1
Lithuania	0.4199	0.4038	−	15	18	−3
Luxembourg	0.5915	0.5603	−	3	5	−2
Malta	0.4042	0.4302	+	19	13	6
Netherlands	0.4960	0.5633	+	7	3	4
Poland	0.3422	0.3242	−	27	27	0
Portugal	0.4004	0.4297	+	21	14	7
Romania	0.3423	0.3391	−	26	26	0
Slovakia	0.4021	0.3849	−	20	22	−2
Slovenia	0.4108	0.3906	−	18	20	−2
Spain	0.4632	0.4354	−	10	12	−2
Sweden	0.5996	0.6029	+	2	2	0
Descriptive statistics
Arithmetic mean	0.448885	0.452996
Median	0.420000	0.429700
Coefficient of variation (%)	17.40384	18.94631
Minimum	0.342200	0.324200
Maximum	0.605900	0.644700
Asymmetry	0.680145	0.636627
Range	0.263700	0.320500
Standard deviation	0.078123	0.085826

Notes: Bold—EU member states with increased in the value of an index. Source: own elaboration.

).

Research results indicate that EU member states are developing in the area of the green economy. The analysis of the value of the green economy measure in EU member states shows that in 2021, as compared to 2014, there was an increase in the overall level of the green economy in 14 EU countries, and in the remaining 13 EU countries, there was a decrease. In comparable years, eight EU countries improved their position in the ranking, while 13 lowered their position. The changes in the position were relatively small. Only in Hungary and Portugal were relatively greater changes observed (an increase in the ranking position by seven and six positions, respectively). There were no changes in the ranking position of five EU member states (Belgium, Finland, Germany, Latvia, and Sweden). The largest increases in the level of the synthetic indicator were observed in Estonia (24.65%), Hungary (13.91%), and the Netherlands (13.57%). Nevertheless, almost half of the EU member states (48.1%) recorded a decline in the level of the synthetic indicator. The largest declines occurred in Croatia (13.36%) and Greece (11.0%).

In 2014 and 2021, the highest values of the synthetic index, calculated for the full set of diagnostic features, and the best positions in the ranking, were observed in the following countries: Finland (0.6059 and 0.6447, respectively) and Sweden (0.5996 and 0.6029, respectively). On the other hand, the group of countries with the lowest level of the synthetic index in 2014 includes Poland (0.3422), Romania (0.3423), and Hungary (0.3558), and in 2021: Poland (0.3242), Romania (0.3391), and Cyprus (0.3652).

The conducted analysis of the level of the synthetic index of the green economy showed differentiation between the examined EU member states. The coefficient of variation of the synthetic indicator in 2014 was 17.4%, and in 2021, it amounted to 18.9%. Moreover, the measure of the synthetic index calculated for individual EU countries in 2014 ranged from 0.34 to 0.61, i.e., the difference was 0.27, while in 2021, the corresponding values were from 0.32 to 0.64, respectively (range—0.32). An increase in the difference between the extreme values of the measure of the synthetic index in 2021, as compared to 2014, indicates a growing scale of differentiation in the level of the green economy in EU member states.

The average of the synthetic index in 2021 for all the analysed countries was 0.4529, and in the base year, it was 0.4488, which meant that the general level of “greening” of the economies in EU member states slightly increased. It should be emphasised that this level was relatively low considering the possible range of the synthetic index <0, 1>. The increasing differentiation of the development level of the green economy in the EU is also indicated by the reference of the synthetic indicator established for individual EU countries to the arithmetic mean of the measures for all countries. In 2014, the lowest taxonomic measure of the green economy was 76.2% of the average value, and in 2021, the corresponding indicator was 71.6%.

Additionally, the standard deviation of the synthetic indicator for EU member states testifies to a differentiation of green transition in respective countries. The standard deviation means that in individual EU member states, the aggregate measure calculated for the set of features determining the level of the green economy in the EU deviates from its average level in 2014 by 0.078123 and in 2021 by 0.085826. Consideration should be applied to the strength and sign of asymmetry coefficients. Asymmetry coefficients equal to 0.680145 in 2014 and 0.636627 in 2021, resulting in moderate righthand asymmetry, i.e., a more significant number of the EU member states reached values of the taxonomic measures below the average.

The analysis of the general level of the green economy was supplemented with the assessment of partial indicators. The linear ordering procedure was conducted for three subareas related to specific aspects of the green economy, i.e., (1) environmental and resource productivity of the economy, (2) environmental dimension of quality of life, and (3) economic opportunities and policy responses. The results obtained for EU member states in 2014 and 2021 are presented in

Table 3. Development level of the green economy in the EU member states according to the specific indicators in 2014 and 2021.

EU Member States	Environmental and Resource Productivity of the Economy		Environmental Quality of Life		Economic Opportunities and Policy Responses
	2014	2021	2014	2021	2014	2021
Austria	0.5912	0.5245	0.5432	0.5338	0.5103	0.6288
Belgium	0.4926	0.4716	0.4926	0.4949	0.2558	0.2793
Bulgaria	0.3246	0.2977	0.4485	0.4918	0.3245	0.3796
Croatia	0.5936	0.4940	0.5414	0.5214	0.2210	0.1596
Cyprus	0.4064	0.3604	0.4707	0.4850	0.2581	0.2502
Czechia	0.3597	0.3468	0.5038	0.4983	0.2659	0.2977
Denmark	0.5268	0.5220	0.5808	0.5637	0.5653	0.5572
Estonia	0.2812	0.3633	0.6503	0.8683	0.3611	0.3797
Finland	0.4028	0.4205	0.9208	0.9012	0.4940	0.6123
France	0.5494	0.5069	0.5156	0.4793	0.3853	0.3363
Germany	0.4844	0.4850	0.5198	0.5148	0.4831	0.5891
Greece	0.4352	0.4482	0.4772	0.4715	0.3477	0.2015
Hungary	0.4464	0.3973	0.4871	0.5286	0.1339	0.2900
Ireland	0.5201	0.6077	0.6348	0.6066	0.1943	0.2109
Italy	0.6411	0.5446	0.4939	0.4976	0.3631	0.4027
Latvia	0.5198	0.4759	0.4770	0.5217	0.2467	0.2793
Lithuania	0.4963	0.4532	0.5379	0.5486	0.2257	0.2096
Luxembourg	0.6112	0.6388	0.5821	0.5683	0.5813	0.4738
Malta	0.5398	0.6132	0.4579	0.4465	0.2148	0.2309
Netherlands	0.5641	0.5904	0.5432	0.5238	0.3807	0.5757
Poland	0.3554	0.3222	0.4867	0.4873	0.1846	0.1631
Portugal	0.5486	0.5222	0.4895	0.4836	0.1631	0.2834
Romania	0.4983	0.4346	0.3941	0.4332	0.1345	0.1495
Slovakia	0.4314	0.3932	0.4962	0.5202	0.2786	0.2412
Slovenia	0.4671	0.4309	0.4806	0.4759	0.2847	0.2649
Spain	0.5878	0.5263	0.5550	0.5099	0.2467	0.2699
Sweden	0.6039	0.5885	0.6844	0.6554	0.5105	0.5648
Descriptive statistics
Arithmetic mean	0.491822	0.473330	0.535744	0.541896	0.319085	0.343741
Median	0.498300	0.475900	0.503800	0.514800	0.278600	0.283400
Coefficient of variation (%)	19.06848	19.55787	18.65305	20.14671	41.33214	44.39951
Minimum	0.281200	0.297700	0.394100	0.433200	0.133900	0.149500
Maximum	0.641100	0.638800	0.920800	0.901200	0.581300	0.628800
Asymmetry	−0.523738	−0.061626	2.398902	2.517241	0.583647	0.706630
Range	0.359900	0.341100	0.526700	0.468000	0.447400	0.479300
Standard deviation	0.093783	0.092573	0.099933	0.109174	0.131885	0.152619

Notes: Bold—EU member states with increased in the value of an index. Source: own elaboration.

and

Table 4. Three areas of the green economy in the EU member states—comparison of countries positions in the rankings in 2014 and 2021.

EU Member States	Environmental and Resource Productivity of the Economy		Environmental Quality of Life		Economic Opportunities and Policy Responses
	2014	2021	2014	2021	2014	2021
Austria	5	8	8	8	3	1
Belgium	16	15	17	18	17	15
Bulgaria	26	27	26	19	12	10
Croatia	3	12	10	12	21	26
Cyprus	22	24	24	21	16	19
Czechia	24	25	14	16	15	12
Denmark	11	10	6	6	2	6
Estonia	27	23	3	2	10	9
Finland	23	20	1	1	5	2
France	8	11	13	23	7	11
Germany	17	13	12	14	6	3
Greece	20	17	22	25	11	24
Hungary	19	21	19	9	27	13
Ireland	12	3	3	3	23	22
Italy	1	6	16	17	9	8
Latvia	13	14	23	11	18	16
Lithuania	15	16	11	7	20	23
Luxembourg	2	1	5	5	1	7
Malta	10	2	25	26	22	21
Netherlands	7	3	9	10	8	3
Poland	25	26	20	20	24	25
Portugal	9	9	18	22	25	14
Romania	14	18	27	27	26	27
Slovakia	21	22	15	13	14	20
Slovenia	18	19	21	24	13	18
Spain	6	7	7	15	19	17
Sweden	3	5	2	3	3	5

Source: own elaboration.

.

The first area, i.e., the environmental and resource productivity of the economy, was assessed on the basis of the value of the measure according to eight diagnostic features. The comparison of the indicator in this area shows that, in 2014, the best potential was observed in the following EU member states: Italy (0.6411), Luxembourg (0.6112), and Sweden (0.6039), while the lowest was recorded in Estonia (0.2812), Bulgaria (0.3246), Poland (0.3554), and Czechia (0.3597). In 2021, the leading positions in terms of the level of environmental and resource productivity were taken by the following EU countries: Luxembourg (0.6388), Malta (0.6132), and Ireland (0.6077), while the last positions were taken by Bulgaria (0.2977), Poland (0.3222), and Czechia (0.3468).

In the analysed period, positive changes in the ranking of environmental and resource productivity were observed in 10 EU member states. In Portugal, the position in terms of environmental and resource productivity has not changed. The most positive changes occurred in Ireland (nine positions up) and Malta (eight positions up). This is mainly due to:

• High values of indicators that have a positive impact on this dimension (stimulants), such as:

  −

  x₁₃ energy productivity—the highest values of indicator in Ireland and Malta,

  −

  x₁₇ non-energy material productivity—the high value of the indicator in Malta,

  −

  x₁₈ resource productivity—the high value of the indicator in Ireland,

• And low values of indicators that have a negative impact on this dimension (destimulants), such as:

  −

  x₁₁ greenhouse gas emissions from production activities—the lowest value of indicator in Malta,

  −

  x₁₆ primary energy consumption—the lowest value of the indicator in Malta.

Meanwhile, the situation in terms of environmental and resource productivity deteriorated the most in Croatia (a fall of nine positions) and Italy (a fall of five positions). This is mainly due to low values of indicators that have a positive impact on this dimension (stimulants), such as:

−

x₁₃ energy productivity—the low value of the indicator in Croatia and the relatively low value of the indicator in Italy,

−

x₁₅ renewable electricity generation—the relatively low value of the indicator in Italy,

−

x₁₇ non-energy material productivity—the relatively low value of the indicator in Croatia.

The second area, i.e., the environmental dimension of quality of life, was evaluated on the basis of the measure established for six diagnostic features. Both in 2014 and 2021, only Finland was in the most favorable situation in this respect (0.9208 and 0.9012, respectively). On the other hand, the countries with the least favorable situation in terms of the environmental dimension of quality of life in 2014 and 2021 were Romania (0.3941 and 0.4332, respectively). It should be emphasized that, in Romania, an increase in the indicator in this area was recorded in the comparable years.

The most significant positive changes in the improvement of the environmental dimension of quality of life between 2014 and 2021 were observed in seven EU member states, mainly in Latvia (12 positions up) and Hungary (10 positions up), while the most insufficient transformations occurred in 13 countries, especially in France (a decrease by 10 positions) and Spain (a decrease by 8 positions). Importantly, in as many as seven EU member states (Austria, Denmark, Finland, Ireland, Luxembourg, Poland, and Romania), the position in terms of the environmental dimension of quality of life has not changed.

The favorable changes in the environmental dimension of quality of life in Latvia and Hungary resulted from the low values of the characteristics affecting it negatively (destimulants), such as:

−

x₂₁ population exposure to PM2.5—the relatively low value of the indicator in Latvia,

−

x₂₂ population exposed to more than 10 micrograms/m³—the relatively low value of indicator in Latvia,

−

x₂₃ mortality from exposure to lead (Pb)—the relatively low values of the indicator in Latvia and Hungary.

On the other hand, the negative changes in the environmental dimension of quality of life in France and Spain resulted primarily from:

• High values of indicators that have a negative impact on this dimension (destimulants), such as:

  −

  x₂₁ population exposure to PM2.5—the relatively high values of indicator in France and Spain,

  −

  x₂₂ population exposed to more than 10 micrograms/m³—the relatively high values of indicator in France and Spain,

  −

  x₂₆ population living in households considering that they suffer from noise—the relatively high values of indicator in France and Spain,

• And low values of indicators that have a positive impact on this dimension (stimulants), such as:

  −

  X₂₅ population with access to improved sanitation—the relatively low value of the indicator in France.

The third area, i.e., economic opportunities and policy responses, was calculated on the basis of seven features describing this dimension of the green economy. The analysis of the value of the economic opportunities and policy responses measure shows that the most favorable potential in this respect in 2014 was observed in the following EU member states: Luxembourg (0.5813) and Denmark (0.5653). Meanwhile, the lowest was recorded in Hungary (0,1339) and Romania (0.1345). On the other hand, in 2021, the following EU countries were in the lead in the ranking: Austria (0.6288), Finland (0.6123), and Germany (0.5891). The lowest in the ranking were the following EU member states: Romania (0.1495), Croatia (0.1596), and Poland (0.1631).

The analysis of the indicator of economic opportunities and policy responses in 2014 and 2021 shows significant changes in its level—15 countries rose in the ranking, while 12 dropped. The most positive changes occurred in Hungary (14 positions up) and Portugal (11 positions up). This is mainly due to high values of indicators that have a positive impact on this dimension (stimulants), such as:

−

x₃₅ feed-in tariffs for solar photovoltaic—the highest value of the indicator in Hungary,

−

x₃₇ organic agricultural area in % of total agricultural area—the relatively high value of the indicator in Malta.

However, the situation in terms of economic opportunities and policy responses deteriorated the most in Greece (a fall of 13 positions), Luxembourg, and Slovakia (a fall of 6 positions). This is mainly due to low values of indicators that have a positive impact on this dimension (stimulants), such as:

−

x₃₁ development of environment-related technologies—the relatively low values of indicator in Greece and Slovakia,

−

x₃₂ relative technological advantage in environment-related technologies—the relatively low value of the indicator in Greece,

−

x₃₅ feed-in tariffs for solar photovoltaic—the relatively low values of indicator in Luxembourg and Slovakia,

−

x₃₆ feed-in tariffs for wind electricity generation—the relatively low values of indicator in Greece and Slovakia,

−

x₃₇ organic agricultural area in % of total agricultural area—the relatively low value of the indicator in Luxembourg.

The EU member states rankings based on the values of partial indicators of the taxonomic measure show, much more than the synthetic index, that the positions taken by individual EU countries in all dimensions of the green economy vary considerably. The selected descriptive characteristics, estimated for the synthetic measures of the green economy, also point to the same conclusion. For the studied areas of the green economy, the coefficients of variation were above 18%. The largest variation could be observed in the third dimension of the green economy concerning the countries’ economic opportunities and policy responses (Vs = 41.33214 in 2014 and Vs = 44.39951 in 2021), and the smallest in the first dimension involving environmental and resource productivity indicators (respectively: Vs = 19.06848 in 2014 and Vs = 19.55787 in 2021).

Interesting results may be also obtained having set up the asymmetry. Left-skewed asymmetry was identified in the first dimension of the green economy, i.e., environmental and resource productivity (respectively: As = −0.523738 in 2014 and As = −0.061626 in 2021). In 2014 the asymmetry was moderate, meaning that a greater number of countries achieved values above the mean. However, in 2021, the asymmetry was close to 0, which indicates a symmetrical distribution, meaning that for about 50% of the countries, the taxonomic measure takes a value below the average. The opposite situation (right asymmetry) can be observed for the second dimension, i.e., the environmental dimension of quality of life (respectively: As = 2.398902 in 2014 and As = 2.517241 in 2021) and the third dimension, i.e., economic opportunities and policy responses (respectively: As = 0.583647 in 2014 and As = 0.706630 in 2021), with the strength of this asymmetry being relatively high, especially in the second area. For these dimensions, the values were below the mean for most EU member states.

A multidimensional comparative analysis also made it possible to distinguish groups of countries with a similar level of green economy development. On the basis of the synthetic measure of the green economy, EU member states were classified into four groups in 2014 and 2021. To determine them, the arithmetic mean of the synthetic measure and the standard deviation of the synthetic measure were used and calculated for individual EU countries. The following range limits of the synthetic measure of the green economy were obtained for the analyzed dataset: the high level—0.5477 to 0.6447 (in 2021) and 0.5482 to 0.6059 (in 2014), the medium–high level—0.4751 to 0.5371 (in 2021) and 0.4497 to 0.4994 (in 2014), the medium–low level—0.3738 to 0.4409 (in 2021) and 0.3764 to 0.4309 (in 2014), and the low level 0.3242 to 0.3652 (in 2021) and 0.3422 to 0.3659 (in 2014). The graphic image of the division of the EU member states into similar groups according to the development level of the green economy are the maps presented in Figure 1 and Figure 2. Respective shades of blue on the figures denote the allocation of respective countries into one of four groups.

The analysis of the four groups of the EU member states showed that, in 2021, the first group, featuring the highest level of the green economy, consisted of six member states: Finland, Sweden, the Netherlands, Austria, Luxembourg, and Denmark (in 2014: Finland, Sweden, Luxembourg, Denmark, and Austria, respectively). The second group included the following EU member states: Estonia, Germany, Italy, and Ireland (in 2014: Italy, the Netherlands, Germany, France, Spain, Croatia, and Ireland, respectively). The next third group included: France, Spain, Malta, Portugal, Latvia, Belgium, Hungary, Lithuania, Croatia, Slovenia, Bulgaria, Slovakia, Czechia, and Greece (in 2014: Estonia, Greece, Lithuania, Latvia, Belgium, Slovenia, Malta, Slovakia, Portugal, Cyprus, and Czechia, respectively). This group was the most numerous group of the EU member states, featuring, on average, lower green economy ratings. The last, fourth group (the weakest) included: Cyprus, Romania, and Poland (in 2014: Bulgaria, Hungary, Romania, and Poland, respectively).

In 2021, progress in this dimension was made by the Netherlands (to the first group), Estonia (to the second group), and Bulgaria and Hungary (to the third group). However, regression (decrease) was observed in France, Spain, Croatia (in the third group), and Cyprus (in the fourth group).

In addition,

Table 5. Results of grouping the EU member states by areas of the green economy in 2014 and 2021.

Area	Year	Group 1.	Group 2.	Group 3.	Group 4.
Environmental and resource productivity of the economy	2014	Italy, Luxembourg, Sweden, Croatia, Austria, Spain	Netherlands, France, Portugal, Malta, Denmark, Ireland, Latvia, Romania, Lithuania, Belgium	Germany, Slovenia, Hungary, Greece, Slovakia, Cyprus, Finland	Czechia, Poland, Bulgaria, Estonia
	2021	Luxembourg, Malta, Ireland, Netherlands, Sweden	Italy, Spain, Austria, Portugal, Denmark, France, Croatia, Germany, Latvia	Belgium, Lithuania, Greece, Romania, Slovenia, Finland, Hungary, Slovakia	Estonia, Cyprus, Czechia, Poland, Bulgaria
Environmental quality of life	2014	Finland, Sweden, Estonia	Ireland, Luxembourg, Denmark, Spain, Austria, Netherlands, Croatia, Lithuania	Germany, France, Czechia, Slovakia, Italy, Belgium, Portugal, Hungary, Poland, Slovenia, Greece, Latvia, Cyprus, Malta, Bulgaria	Romania
	2021	Finland, Estonia, Sweden	Ireland, Luxembourg, Denmark, Lithuania	Austria, Hungary, Netherlands, Latvia, Croatia, Slovakia, Germany, Spain, Czechia, Italy, Belgium, Bulgaria, Poland, Cyprus, Portugal, France, Slovenia, Greece, Malta	Romania
Economic opportunities and policy responses	2014	Luxembourg, Denmark, Sweden, Austria, Finland, Germany	France, Netherlands, Italy, Estonia, Greece, Bulgaria	Slovenia, Slovakia, Czechia, Cyprus, Belgium, Latvia, Spain, Lithuania, Croatia, Malta, Ireland	Poland, Portugal, Romania, Hungary
	2021	Austria, Finland, Germany, Netherlands, Sweden, Denmark	Luxembourg, Italy, Estonia, Bulgaria	France, Czechia, Hungary, Portugal, Belgium, Latvia, Spain, Slovenia, Cyprus, Slovakia, Malta, Ireland, Lithuania, Greece	Poland, Croatia, Romania

Source: own elaboration.

presents the results of grouping the EU member states by areas of the green economy in 2014 and 2021.

Table 5 shows that, in the analyzed period, there were different development conditions in individual areas of the green economy. The first and second groups include countries with above-average development levels of the green economy. The third and fourth groups have synthetic variable values lower than the mean.

5. Conclusions

The presented results of multi-aspect analyses allowed the following conclusions to be formulated:

• The analysis of the literature and reports of the largest international organizations shows that the concept of the green economy is a development opportunity for the EU member states and is important for solving global threats related to climate change and the depletion of natural resources. Moreover, “greening” the economy supports the implementation of most sustainable development goals. It can contribute to increasing the prosperity and social equality of future generations and the right balance between the economy and ecosystems. The change of thinking in the direction of the green economy can be observed not only in highly developed countries but also in developing ones [4,128]. Increasingly diverse factors are currently being used in research on the green economy [129]. Their scope is not limited. Numerous factors that describe the social situation in individual countries are also increasingly gaining in importance [127].
• There are specific relationships between the elements of the green economy (environment, economy, and society), which were used to examine three areas of the green economy, i.e., the environmental and resource productivity of the economy—including indicators describing the connections between the natural environment and the economy, the environmental dimension of quality of life—presents indicators for assessing the connections between the natural environment and society and the economic opportunities and policy responses—contains indicators characterizing the instruments of impact on the economy and society, creating the desired directions of development aimed at “greening” the economy.
• An important element of the article is the linear ordering and classification of EU member states using the method of multidimensional statistical analysis. When comparing two fairly distant periods of research (2014 and 2021), it was possible to identify the direction in which green transformation is proceeding in the examined countries. On the basis of the analysis conducted, there is a large variation among the EU countries regarding green economy. Depending on the area of the green economy, the maximum differences in positions are from 6 to 14 (area three). There are no changes in the classification only in the case of one country in the first area and seven countries in the second area. A spectacular improvement of the ranking position, based on all of the analysed indicators, applies mostly to Hungary (eight positions up, from 25th position to 17th). This is a result of very significant changes in the third area under analysis—economic opportunities to policy responses (advance by 14 positions, from last position to 13th position). Similar changes were also noted for Portugal, which, during the first analysed year, gained 21 positions in the general ranking, and then improved it by seven positions (up to 14th) in the final year—also mainly due to the positive changes in the third area (11 positions up, from 25th to 14th).
• Despite differences in the linear ordering of the EU member states depending on the adopted green economy area, certain regularities are visible. The first places in the presented rankings, regardless of the analysed dimension of the green economy, are usually occupied by Scandinavian countries, especially Finland, which is most often in first place. These countries, for many years, have been implementing technological solutions aimed at combating the degradation of the natural environment. As was pointed out by many authors [78], these are actually the only countries in Europe that have managed to separate permanently their economic growth from the negative pressure exerted on the natural environment. These dependencies are also visible in the analyses conducted for this study. It is worth emphasizing that the Nordic model has not been widely copied by other EU countries. This model has many advantages, including the development of environment-friendly technologies and the appropriate organization of the tax system.
• The values of the synthetic measure of the green economy were also used to divide the set of surveyed countries into groups characterized by similar development. The use of a multi-criteria taxonomy allowed for the division of the EU member states into four groups according to the development level of the green economy. Despite the different number of EU member states qualified to the first (the best) typological group, both in 2014 and 2021, there were countries such as Finland, Sweden, Luxembourg, Denmark, and Austria. The countries located in Northern and Western Europe were most often classified into the highest typological groups in all areas describing the green economy.
• The evaluation of the processes marking countries’ transitions to a green economy is a complex issue that needs advanced methods of analysis. A multifaceted comparative analysis proved to be an adequate tool for designing the synthetic measure of the green economy and for the linear ordering of the EU member states. The added value of the study comprises developing a comprehensive evaluation method through designing the synthetic measure of the green economy, preceded by a thorough analysis of reference literature and the identification of 21 detailed indicators. The informative value of the synthetic measure of the green economy should improve monitoring, planning, and implementing the assumptions of the green economy in the EU member states.
• The empirical results obtained and findings on the green economy may help identify critical conclusions concerning the rules and ways of measurement of the green transformation, the comparison of the level and direction of this transformation, and the identification of the condition of this process. The information thus obtained can provide valuable guidance for taking specific, practical steps useful during the transformation of national economies into modern and competitive systems with minimal possible environmental impact. The growing pressure on the use of environmental resources, especially non-renewable ones, forces various official entities to take actions aimed at improving production efficiency in this area. It is recommended to use more tidal energy, solar energy, wind power, bioenergy, and hydropower instead of fossil fuels, for the sustainable attainment of higher economic growth, devoid of pollution [130]. The implementation of these activities should be monitored to assess their effectiveness. The conclusions from the conducted research are important for EU countries, especially for countries shaping the model of energy sector development. The results presented in the article constitute knowledge that facilitates a better understanding of the instruments used in the energy transformation processes in EU countries, which constitutes the innovative nature of the work.
• The research conducted has its limitations. A significant limitation of the research on green economy is the access to reliable and comparable statistical data. Public statistics databases do not always provide complete and up-to-date information. It is a typical limitation of research using data from official statistics. The final result is also the effect of the applied data-analysis method. For this reason, in this type of research, it is important to look for regularities, the confirmation of which can be found in the studies by other authors. This type of approach was used in this paper.

To summarize, it should be emphasized that the theoretical concepts and empirical research results presented in the article constitute an attempt to comprehensively describe the determinants of the development of the green economy without developing all aspects of the problem. An important direction for future research should be the analysis of the connections between the green economy and sustainable development. In the context of future research in this dimension, it is also vital to look for new factors that may influence the course of the green transformation process and to combine quantitative desk research with qualitative research conducted among the main stakeholders of this process—the residents, entrepreneurs, and public institutions.