How Economic Level Shapes the Effects of Sustainable Development in EU Countries?

Article Corresponding author: Renata Halásková, University of Ostrava, Faculty of Education, Fráni Šrámka 3, 709 00 Ostrava Email: renata.halasko[email protected] How Economic Level Shapes the Effects of Sustainable Development in EU Countries? Scientific Papers of the University of Pardubice, Series D: Faculty of Economics and Administration 2025, 33(1), 2378. ©The Author(s) 2025. This is an open access article under the CC-BY 4.0 license. DOI: 10.46585/sp33012378 editorial.upce.cz/SciPap Renata Halásková University of Ostrava, Faculty of Education, Department of Technical and Vocational Education, Czech Republic Martina Halásková Moravian Business College Olomouc, Department of Economics and Regional Development, Czech Republic Marek Pomp VSB -Technical University of Ostrava, Faculty of Economics, Department of Mathematical Methods in Economics, Czech Republic Abstract The study analyses sustainable development in the context of economic and environmental dimension in EU countries according to economic level. The aim is to evaluate the impact of selected indicators of economic and environmental sustainability on the economic and socio-economic development of two groups of EU countries in the period 2010-2022. The selected set is represented by EU countries with a higher and a lower economic level than the EU average. Using log-log panel regression analysis, the study provides a closer evaluation of the impact of selected economic and environmental sustainability indicators not only in EU countries (27), but also to evaluate differences in the impact of sustainable development indicators between groups of EU countries (with higher and lower economic levels). The results of EU countries with higher and lower economic levels confirmed the impact of different economic and environmental sustainability indicators on the economic and socioeconomic development. The research on the examined areas of sustainable development contributes to a more comprehensive assessment of economic and environmental sustainability, reflecting not only long-term goals, but also some newer trends, with an emphasis on the socio-economic level of development of EU countries. The findings may be useful not only for economic policymakers and environmental analysis in the European dimension, but also for the development of national sustainable development concepts and strategies. Keywords Economic and environmental sustainability, Economic development, Human development, Indicators of sustainable development JEL Classification Q01, Q56, O13 Introduction Sustainable development emphasises the interconnection between economic, social, and environmental dimension. From the perspective of these three dimensions, sustainable development is an important topic for discussion and research in international, European, national, and regional contexts (Anselmi et al., 2024). Sustainable development in the EU as an overarching goal of the European Union’s policies is one of the key issues on the world agenda (Brodny & Tutak, 2023; Ionescu et al., 2024; Kuba & Stejskal, 2024; Kuba &Hudec, 2025). The European Union has made significant progress in achieving sustainable development in all dimensions of sustainability and in all regions of the EU. Nevertheless, the dynamics of sustainability vary across EU countries and dimensions. (Gracia-de-Rentería et al., 2023). For this reason, a number of researches was the impetus for the examination of selected areas of sustainable development and the sustainable development goals (SDGs) in the context of country capabilities and conditions (Sart, 2022; Zhu et al., 2024). At the same time, the issue of sustainable development is being examined from various perspectives on a global scale. In connection with sustainable development, some authors emphasise policy coherence for sustainable development and environmental security as key, with an emphasis on eliminating or mitigating the negative impacts of the 2 SciPap 33(1) current mode of development of human society (Habel & Hakala, 2021; Prokop, et al., 2019). Key themes of sustainable development are also the digitalisation of the economy and its impact on sustainable development (Gariba et al., 2024; Li et al., 2024; Cigu, 2025; Sira & Kuzior, 2025), sustainability development in relation to good governance and education (Sart, 2022; Li et al., 2025; Stefanachi & Grecu, 2025) or the relation between green finance and public spending and their the impact on sustainability (Kurekova et al., 2023; Kpegba et al., 2025). Other researches examine sustainable development predominantly in relation to economic, social or environmental issues (Strezov et al., 2017; Prerna & Pragati, 2020; Rapsikevicius et al.,2022; Gallardo-Vazquez et al., 2025). The relationships between some sustainable development indicators and human development represented by the human development index are assessed (Korsakiene et al., 2011; Hickel, 2020; Zheng &Wang, 2022; Çalikoğlu & Łuczak, 2024). In recent years, research has also focused on assessing the level of achievement of the SDGs from the perspective of EU countries or selected groups of countries (Raszkowski & Bartniczak, 2019; Kiselakova, et al., 2020; Lopatkova, 2021). The findings regarding the achievement of SDGs differ in specific EU countries or groups of countries according to their economic level. To achieve sustainable development, developed countries benefit most from a focus on social and environmental factors and that sustainable development should be measured in ways and approaches that depend on the level of development of the country (Lior et al., 2018; Bali Swain & Yang-Wallentin, 2019). In contrast, in Western European countries, social and economic goals are predominantly achieved, while in Eastern European countries social and environmental goals are achieved (Lopatkova, 2021). Some studies examine selected groups of EU countries from the perspective of sustainability, but only at the level of basic analyses. The authors of this study therefore want to focus on a more detailed assessment of economic and environmental sustainability in EU countries with lower and higher economic levels, thereby partially filling in a research gap. The motivation of the authors is to build on the findings of previous research and to use a deeper analytical approach to examine selected indicators of sustainable development in the context of socio-economic development of EU countries. The aim of the study is to evaluate the impact of selected indicators of economic and environmental sustainability on the economic and socio-economic development of two groups of EU countries in the period 2010-2022. The research contributes to a more comprehensive investigation of selected areas of sustainable development i) in the context of economic development (measured by GDP per capita) and ii) in the context of socio-economic development (measured by HDI) of EU countries. In comparison with other research, the authors strive to evaluate the impact of selected economic and environmental sustainability indicators not only in EU countries (27), but also to evaluate differences in the impact of sustainable development indicators between groups of EU countries (with higher and lower economic levels). Theoretical Background and Literature Review Theoretical Background Sustainable development is a highly complex topic that connects economic and social progress with full environmental preservation (Grzebyk et al., 2023; Anselmi et al., 2024; Brodny & Tutak, 2025). The central issue of sustainable development is to preserve the quality of life and provide for the needs of present and future generations (Firoiu et al., 2025). It takes into account not only economic growth but also social values and natural wealth and it includes a range of problems related to its evaluation and measurement (Chuffart et al., 2021; Rapsikevicius, et al., 2022; Kudelko, 2025). Sustainable development also promotes efficient management of natural resources, sophisticated production technology, alternative energy sources, and economic well-being through financial aid in a sustainable manner for current and future generations (Ijaz & Chughtai, 2022; Saud et al., 2024). Within the framework of sustainable development, we can distinguish three concepts of its conceptualisation (Biswas et al., 2021; Gallardo-Vazquez et al., 2025). The concepts of sustainable development emphasise: i) development that ensures the needs of present generations without compromising the needs of future generations; ii) development based on a balance of the three pillars (economic, social and environmental); and iii) economic principles (capital approach to sustainable development). Sustainability is then understood as the balance of development between the pillars of sustainable development, i.e. between economic development, the living standards of the population and the environmental stresses (United Nations, 2015; Anselmi et al., 2024; Ionescu et al., 2024; Firoiu et al., 2025). Sustainable economic initiatives can be driven by economic, environmental and social aspects and also apply the principles of innovation and knowledge (Biekša et al., 2022). According to some authors, it depends on whether countries are moving towards the goals at a sufficient speed and whether the sustainable development goals (SDGs) can be fully achieved (Kostetckaia & Hametner, 2022). In connection with sustainable development, attention is paid not only to the assessment of specific SDGs, but also to the achievement of the SDGs according to the dimensions or areas of sustainable development (Grzebyk et al., 2023; Pop & Stamos, 2025; Stefanachi & Grecu, 2025). Literature Review and Research Questions In the European dimension, sustainable development has been a debated topic in recent years and the subject of many economic analyses (Rapsikevicius et al., 2022). According to Kudelko (2025) the level of sustainable development of EU countries in 2010-2021 and the dynamics of development in EU increased after the adoption of the United Nations 2030 Agenda for Sustainable Development (in social and economic development), but not in terms 3 SciPap 33(1) of environmental issues. Yildirim et al. (2025) highlight the impact of financial development and quality growth on environmental sustainability in EU countries. The findings show not only the role of the financial system in promoting environmental sustainability, but also quality growth that considers social welfare and resource efficiency in addition to economic expansion. In turn, Jahanger et al. (2022); Wyrwa et al. (2023); Anselmi et al. (2024); Zakari & Musibau (2024) mainly examined sustainable development areas such as affordable & clean energy, economic growth, industry, innovation and infrastructure, sustainable cities and communities or responsible consumption and production (D’Adamo et al., 2022; Brodny & Tutak, 2023). Another topic of sustainable development is circular economy (Gerasimova, 2024; Fernandez et al., 2025; Kakar et al. 2025). The main benefits of the circular economy are 1) reducing the cost of production materials, 2) promoting localism and self-sufficiency and energy security, 3) creating new business models and opportunities and returning to the proven roots of the “good life”, 4) reducing the carbon footprint of human activity and integrating ecological and economic approaches (Apostu et al., 2023; Gerasimova, 2024; Kakar et al. 2025). Dos Santos et al. (2022) tested the relationship between circularity and sustainable development in the EU, with a focus on economic, social and environmental indicators over the periods 2000-2020. According to the authors (Fernandez et al., 2025; Gallardo-Vazquez et al., 2025), circularity is only evident in some areas and sectors of sustainability. In order for circular economy to contribute to global sustainability, it is necessary to reduce problems related to overconsumption and waste discharge. A number of researches then have paid attention to waste management strategies and practices in the context of sustainable development (Baran, 2020; Gavrilescu et al., 2023; Tsimnadis & Kyriakopoulos, 2024). Baran (2020) evaluated the efficiency of plastic waste management in EU countries and takes a position on the challenge of achieving sustainable development goals and circular economy. Other authors (Gavrilescu et al., 2023), looked more closely at the areas of recovery and recycling of packaging waste and its impact on the environment. Important topics of sustainable development are also renewable energy production (Potrc et al., 2021; dos Santos et al., 2022; Tsimnadis & Kyriakopoulos, 2024), sustainable energy development and meeting the climate targets of the Paris Agreement (Prokop et al., 2023; Jedrzejczak-Gas et al., 2024; Saud et al., 2024; Brodny & Tutak, 2025; Mikalauskas & Stanislovaityte, 2025). Jedrzejczak-Gas et al. (2024) assessed sustainable economic development and sustainable energy and demonstrated a significant variation in the level of sustainable energy development and sustainable economic development among EU countries. According to Saud et al. (2023) the impact of renewable energy on sustainable development is beneficial, encouraging increased investment in renewable energy sectors for sustainable production. Mikalauskas & Stanislovaityte (2025) point to the fact that geothermal energy strengthens energy security, reduces greenhouse gas emissions and promotes economic growth. Other authors (Prokop et al., 2023) evaluated the part of sustainable development related to energy management and the role of gender diversity. From the perspective of selected research studies, other topics and areas of sustainable development were also examined. Apostu et al. (2023) evaluated the relationship between a green environment, economic growth and a circular economy using the panel data analysis. Gerasimova (2024) examined the transformative potential of integrating Service Design and technology within Circular Economy models, aimed at enhancing sustainability and consumer engagement. Among other authors, Kakar et al. (2025) investigated the intricate relationship between circular economy, sustainable infrastructure, green FinTech, and European biodiversity conservation. Topics such as the relationship between environmental taxes and sustainable economic development (Sabău-Popa et al., 2024) or the role of green technologies, environmental taxes and green energy in relation to environmental sustainability (Sharif et al., 2023) are also investigated. The subject of the research of the submitted study is the economic and environmental dimension of sustainable development in relation to economic and socio-economic development. The aim of this study is to evaluate the impact of selected indicators of economic and environmental sustainability on the economic and socio-economic development of two groups of EU countries in the period 2010-2022. In relation to the objective three research questions are verified for the EU countries. The source of the research question (RQ1) is the state of knowledge on sustainable development (Korsakiene et al., 2011; Lior et al., 2018; Hickel, 2020), and the source of the research questions (RQ2, RQ3) are the partial conclusions of empirical studies (Raszkowski & Bartniczak, 2019; Kiselakova et al., 2020; Lopatkova, 2021; Kozma, 2025). RQ1: Do sustainability indicators have a greater impact on economic growth than on socio-economic development in EU countries? RQ2: Are there differences in the impact of economic and environmental sustainability indicators on economic development between groups of EU countries (with higher and lower economic levels)? RQ3: Are there differences in the impact of economic and environmental sustainability indicators on socio-economic development between groups of EU countries (with higher and lower economic levels)? 4 SciPap 33(1) Research Methodology Data Secondary data from 2010-2022 from Eurostat and the Human Development Report (Eurostat, 2025a, 2025b, 2025c; UNDPHuman Development Report, 2025) are used for the analysis. The sample represents the 27 EU Member States. The time period chosen corresponds to the availability of data for all variables and EU countries analysed. Data on selected sustainable development indicators in the economic and environmental dimensions (from Eurostat database) and data on indicators representing the economic level of countries - GDP per capita (from Eurostat database) and Human Development Index (from UNDP – United Nations Development ProgrammeHuman Development Report) are used. The sustainability analysis is prepared for the period 2010-2022. It includes 13 indicators (variables) in the field of sustainable development and economic level of economies, which reflects both long-term goals and some newer trends in sustainable development. However, to the analysis it was not possible to include other originally intended indicators of economic and environmental sustainability (due to the unavailability of corresponding statistical data in a sufficiently long time series) for the use of the selected method. As independent variables, we selected 11 indicators from environmental and economic sustainability. Indicators of economic sustainability including circular economy indicators - Circular material use rate (CMUR), Material footprint (MAFO), Resource productivity (REPR), Trade in recyclable raw materials (TRRM), Generation of municipal waste per capita (GMWA), Generation of packaging waste per capita (GPWA), Share of renewable energy in gross final energy consumption by sector (SREFEC), indicators of economic/environmental sustainability - Environmental tax revenues (ETRE), Share of environmental taxes in total tax revenues (SETTRE), and indicators of environmental sustainability - Air emission intensity from industry (AEII), Air emissions accounts totals bridging to emission inventory totals (AETB). We focus on variables from the economic and environmental dimensions of sustainable development (see Table 1). The chosen dimensions of sustainable development are based on the following assumptions: 1) The economic pillar is based on companies’ ability to contribute to economic development and growth. They must encourage and promote the protection of the environment by limiting the risks posed by their production. The recycling of products and the use of renewable energy are therefore fundamental aspects of the development of the economic pillar. The ISO 50001 standard is focused on energy efficiency, with a view to reducing energy consumption and therefore contributing to economic growth (Safdie, 2024). 2) The environmental pillar is founded on a commitment to protect the environment by reducing risks and measuring the environmental impacts of companies' activities. The challenges for companies in this area are: i) Saving and preserving natural energy or agricultural resources, ii) Assessing their carbon footprint and reducing total greenhouse gas emissions and further achieving sustainable development goals; iii) prevent water scarcity and reduce overall waste for current and future generations (Anderson, 2025). For the inclusion of the selected indicators in economic sustainability, the extent to which countries are successful in aligning different areas of economic policy with sustainability requirements and, in the case of environmental sustainability, the extent to which countries are successful in aligning different areas of environmental policy with sustainability requirements is taken into account (see SGI, 2024a, 2024b for details). At the same time, we also draw on the SDGs and specific areas of sustainability (see Eurostat, 2025a, 2025b). As dependent variables, we use indicators for measuring economic growth and socio-economic progress of EU countries: • GDP per capita represents a country's economic output per person. It's a key indicator of a nation's economic prosperity and living standards, often used to compare economic performance across different countries. • The Human Development Index (HDI) is used to compare and evaluate the socio-economic progress of countries. The HDI was created to emphasise that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The indicators used for the analysis are documented in more detail in Table 1. 5 SciPap 33(1) Table 1. Used indicators. Indicators/ variables Abb. Unit Source Dependent variables GDP per capita GDP Euro per capita Eurostat Human Development Index HDI Index (0-1) UNDP Independent variables /sustainable development Circular material use rate CMUR Percentage Eurostat Material footprint MAFO Tonnes per capita Eurostat Resource productivity REPR Euro per kilogram Eurostat Trade in recyclable raw materials TRRM Tonne Eurostat Generation of municipal waste per capita GMWA Kilograms per capita Eurostat Generation of packaging waste per capita GPWA Kilograms per capita Eurostat Share of renewable energy in gross final energy consumption by sector SREFEC Percentage Eurostat Environmental tax revenues ETRE Million euro Eurostat Share of environmental taxes in total tax revenues SETTRE Percentage of total revenues from taxes and social contributions Eurostat Air emission intensity from industry AEII Grams per euro Eurostat Air emissions accounts totals bridging to emission inventory totals AETB Kilograms per capita Eurostat Source: Eurostat (2025a,b); UNDP-Human development reports (2025). The original intention of the authors was to work with more indicators for the purposes of the analysis. Due to the high correlation dependencies between the selected variables, two sustainability indicators (Generation of plastic packaging waste per capita (GPPW) and Greenhouse gases emissions from production activities (GGEPA) had to be excluded (see figure 1). Fig. 1. Correlation matrix of variables. Source: Authors’ calculations. The selected set comprises 27 EU countries. For the purposes of a more detailed examination, the EU countries have been divided into two groups and evaluated (with respect to their economic levels) according to Purchasing power adjusted GDP per capita. Basic figures are expressed in purchasing power standards (PPS), which represents a common currency that eliminates the differences in price levels between countries to allow meaningful volume comparisons of GDP (Eurostat, 2025c). See Table 2 for more details. 6 SciPap 33(1) Table 2. Distribution of countries by economic levels. The group of EU countries with a higher economic level than the EU average: The group of countries with a lower economic level than the EU average: Austria, Belgium, Denmark, Germany, Ireland, France, Luxembourg, Netherlands, Finland, Sweden. Bulgaria, Czech Republic, Estonia, Greece, Spain, Croatia, Italy, Cyprus, Latvia, Lithuania, Malta, Hungary, Poland, Portugal, Romania, Slovenia, Slovakia. Source: Authors according to Eurostat (2025c). Methods We use selected scientific methods for this study. The theoretical background of the problem is elaborated using document analysis and systematic literature search. We use the method of induction and deduction in the discussion and in drawing conclusions. The evaluation of correlation dependencies between the variables under study (indicators of sustainable development) is carried out using correlation analysis. Panel data regression analysis is used to examine the impact of selected sustainable development indicators in the context of the economic level of EU countries in 2010-2022. To ensure the appropriate econometric specification for our panel data analysis, we employed a stepwise model selection approach to distinguish among the Pooled Ordinary Least Squares (OLS), Fixed Effects (FE), and Random Effects (RE) estimators. The dependent and independent variables were log-transformed to facilitate elasticity interpretation, resulting in a log-log functional form. A logarithmic-logarithmic (log-log) panel regression analysis examines the relationship between variables using panel data, where each observation represents a specific entity (like a country or firm) observed over multiple time periods. The "log-log" aspect refers to transforming both the dependent and independent variables by taking their natural logarithm. This transformation allows for the interpretation of regression coefficients as elasticities, representing the percentage change in the dependent variable for a one percent change in the independent variable (Bai & Li, 2014; Petersen, 2017). According to Taylor (2022) the log-log model is a type of statistical modelling used to analyse trends and patterns in data sets. It is a generalized linear model (GLM) that uses a logarithmic transformation for both independent and dependent variables, as well as for the error terms. The loglog model is a type of regression analysis that converts the original data into a series of multiplicative terms expressed on a logarithmic scale. This allows for better results when dealing with data featuring non-linear relationships between input and output variables [online] (Taylor, 2022). The goal of this analysis is to estimate the effect of several independent variables on a dependent variable using a log-log panel regression model, allowing for the interpretation of coefficients as elasticities (Petersen, 2017). The data has a panel structure (multiple units observed over time). We use log-log regression models for groups of EU countries and examine the effects of selected indicators of economic and environmental sustainability on economic level of countries in the period 2010-2022. The economic level is measured according to: i) GDP per capita - for all EU countries (GDP-Model 1), for the group of EU countries with a higher economic level than the EU average (GDP - Model 1.1) and for the group of EU countries with a lower economic level than the EU average (GDP - Model 1.2.); ii) Human development index (HDI) - for all EU countries (HDI-Model 2); for the group of EU countries with a higher economic level than the EU average (HDI - Model 2.1); and for the group of EU countries with a lower economic level than the EU average (HDI - Model 2.2). Effects of selected indicators of sustainable development in logarithmic-logarithmic (log-log) regression models are evaluated according to statistical significance (Leahey, 2005). According to Baltagi (2021) and Greene (2018), to formally determine the most appropriate model, we conducted the following statistical tests: The 𝐹-test is used to determine whether the Fixed Effects model provides a significantly better fit than the Pooled OLS model. The Hausman Test is used to determine whether the Fixed Effects model provides a significantly better fit than Random Effects model. This rigorous selection process ensures the consistency and efficiency of the estimated coefficients in the log-log panel regression framework. In all examined cases, the p-values of both the F-test and the Hausman test were close to zero. In line with the alternative hypotheses of these tests, we will proceed with modelling using only the fixed effects (FE) model. For our analysis the panel data follows this structure: • 𝑖 = 1,...,27: cross-sectional units (countries), • 𝑡 =2010,...,2022: time dimension (years), • total number of observations: 27×13=351 7 SciPap 33(1) General fixed effects (FE) model is specified by the following equation 𝑙𝑜𝑔𝑦𝑖𝑡 = 𝛼𝑖+∑𝛽𝑘 𝐾 𝑘=1 𝑙𝑜𝑔𝑥𝑘𝑖𝑡 +𝜀𝑖𝑡 (1) where 𝑙𝑜𝑔𝑦𝑖𝑡 log of the dependent variables (GDP, HDI) 𝑙𝑜𝑔𝑥𝑘𝑖𝑡 logs of regressors (CMUR, MAFO, REPR, TRRM, GMWA, GPPW, GPWA, GGEPA, AEII, AETB, ETRE, SETTRE, SREFEC) 𝛽𝑘 elasticity - interpreted approximately as % change in𝑦 for 1% change in 𝑥𝑘 𝛽𝑘≈%𝛥𝑦 %𝛥𝑥𝑘 𝛼𝑖 unit fixed effect - captures unobserved, time-invariant characteristics 𝜀𝑖𝑡 idiosyncratic error Results Using log-log regression panel data analysis, the impact of selected indicators of sustainable development on the economic level of two groups of EU countries (with a higher and lower economic levels) in the years 2010-2022 is assessed. Economic and socioeconomic level of countries is measured using two indicators (GDP per capita and Human development index). The Impact of Selected Indicators of Sustainability Development on GDP per capita of EU Countries with a Higher and Lower Economic Level In the period 2010-2022 we examine the impact of selected indicators of sustainable development (in economic and environmental dimension) on economic development (measured by GDP per capita) of two groups of EU countries (with a higher and a lower economic level than the EU average). The results of the assessed sustainable development indicators on GDP per capita for the group of 10 EU Countries with a higher economic level are shown in Table 3 (GDP Model 1.1.). Table 3. The Impact of selected indicators of sustainable development on GDP per capita in years 2010-2022 for EU countries with a higher economic level (GDP - Model 1.1). term estimate std.error statistic p.value p.value.signif log(CMUR) -0.04205 0.01504 -2.797 0.006105 ** log(MAFO) 0.1765 0.03888 4.539 1.461e-05 *** log(REPR) 0.6155 0.05044 12.2 4.101e-22 *** log(TRRM) 0.02058 0.01738 1.184 0.239 ns log(GMWA) -0.03099 0.0282 -1.099 0.2742 ns log(GPWA) 0.1939 0.06011 3.225 0.001664 ** log(AEII) -0.09259 0.02559 -3.619 0.0004505 *** log(AETB) 0.3107 0.04285 7.251 6.333e-11 *** log(ETRE) 0.1109 0.0629 1.764 0.0806 ns log(SETTRE) -0.1957 0.0587 -3.333 0.001173 ** log(SREFEC) -0.01726 0.02186 -0.7897 0.4314 ns Note: *** p ≤ 0.001 highly significant, ** 0.001 < p ≤ 0.01 strongly significant, * 0.01 < p ≤ 0.05 significant, ns 0.5 < p non-significant. Source: Authors. Resource productivity (REPR) and Air emissions accounts totals bridging to emission inventory totals (AETB) have the largest statistically significant positive effect on GDP per capita at a 0.1% level. Generation of packaging waste per capita (GPWA) at a 1% level and Material footprint (MAFO) at a 0.1% level also have a positive impact on GDP per capita. This means that a 1% increase in the indicators (REPR, AETB, GPWA, MAFO) is associated with an average increase in GDP p.c. all else being equal. Specifically, a 1% increase in REPR is associated with an average increase in GDP per capita of 0.6155%, a 1% increase in AETB translates into an average increase in GDP p.c. of 0.3107%, a 1% increase in GPWA is associated with an average increase in GDP p.c. of 0.1939% and a 1% increase in MAFO with an average increase in GDP p.c. of 0.1765%, with other conditions remaining the same (Table 3 - GDP Model 1.1.). 8 SciPap 33(1) In 2010-2022 for group of EU countries with a higher economic level the share of environmental taxes in total tax revenues (SETTRE) at a 1% level had the largest statistically significant negative impact on GDP per capita. A smaller statistically significant negative impact on GDP p.c. was also observed for Air emission intensity from industry (AEII) at a 0.1% level and Circular material use rate (CMUR) at a 1% level. Specifically, this means that a 1% increase in SETTRE is associated with an average reduction in GDP p.c. of 0.1957%, a 1% increase in AEII is associated with an average reduction in GDP p.c. of 0.09259% and a 1% increase in CMUR translates into an average reduction in GDP p.c. of 0.04205%, all else being equal (Table 3 - GDP Model 1.1). The impact of the assessed sustainable development indicators on economic development for the group of 17 EU countries with a lower economic level than the EU average in 2010-2022 is shown in Table 4 - (GDP Model 1.2). Table 4. The Impact of selected indicators of sustainable development on GDP per capita in years 2010-2022 for EU countries with a lower economic level (GDP - Model 1.2). term estimate std.error statistic p.value p.value.signif log(CMUR) -0.01043 0.007745 -1.346 0.1798 ns log(MAFO) 0.1784 0.03513 5.078 8.959e-07 *** log(REPR) 0.0792 0.03443 2.3 0.0225 * log(TRRM) 0.0189 0.006222 3.038 0.002708 ** log(GMWA) 0.01959 0.0237 0.8266 0.4095 ns log(GPWA) 0.07678 0.02202 3.487 0.0006055 *** log(AEII) -0.01198 0.009576 -1.251 0.2125 ns log(AETB) 0.1308 0.02407 5.432 1.664e-07 *** log(ETRE) 0.3509 0.02781 12.62 5.215e-27 *** log(SETTRE) -0.3546 0.03268 -10.85 1.009e-21 *** log(SREFEC) 0.06134 0.01687 3.637 0.0003541 *** Note: *** p ≤ 0.001 highly significant, ** 0.001 < p ≤ 0.01 strongly significant, * 0.01 < p ≤ 0.05 significant, ns 0.5 < p non-significant. Source: Authors. The largest statistically significant positive impact on GDP per capita is from environmental tax revenues (ETRE), followed by material footprint (MAFO) and Air emissions accounts totals bridging to emission inventory totals (AETB) at a 0.1% level. This means that a 1% increase in ETRE is associated with an average increase in GDP per capita of 0.3509% all else being equal. At the same time 1% increase in MAFO and AETB is associated with a 0.1784% increase in GDP p.c. and a 0.1308% increase in GDP p.c., with other conditions remaining the same. In contrast, the largest negative impact on GDP p.c. is the share of environmental taxes in total tax revenues (SETTRE) at a 0.1% level. This means that a 1% increase in SETTRE is associated with an average reduction in GDP per capita of 0.3546%, all else being equal (see Table 4, GDP - Model 1.2). For group of EU countries with a lower economic level than the EU average, a smaller statistically significant positive impact on GDP per capita is represented by resource productivity (REPR) at a 5% level, generation of packaging waste per capita (GPWA) and share of renewable energy in gross final energy consumption by sector (SREFEC) at a 0.1% level, This means that a 1% increase in REPR, GPWA, SREFEC is associated with an average increase in GDP per capita, all else being equal. Specifically, a 1% increase in REPR is associated with a 0.0792% increase in GDP per capita, a 1% increase in GPWA is associated with a 0.07678% increase in GDP per capita, and a 1% increase in SREFEC is associated with a 0.06134% increase in GDP per capita, with other conditions remaining the same (see Table 4, GDP - Model 1.2). The Impact of Selected Indicators of Sustainability Development on Human Development Index of EU Countries with a Higher and Lower Economic Level The impact of selected indicators of sustainable development (in economic and environmental dimensions) on the socio-economic level of two groups of EU countries is further investigated for the period 2010-2022. The socioeconomic level of development of countries is measured by the HDI. The results of the impact of the examined sustainable development indicators for the group of 10 EU countries with a higher economic level than the EU average are shown in Table 5 - HDI Model 2.1. Generation of packaging waste per capita (GPWA) and environmental tax revenues (ETRE) have the largest statistically significant positive effect on HDI at a 0.1% level. This means that a 1% increase in GPWA and ETRE is associated with an average increase in HDI, all else being equal (0.04054% for GPWA and 0.03664% for ETRE). A smaller positive effect on HDI is also represented by Material footprint (MAFO) and Trade in recyclable raw materials (TRRM) at a 1% level. That is, a 1% increase in MAFO is associated with a 0.01592% increase in HDI, and a 1% increase in TRRM is associated with a 0.006675% increase in HDI, all else being equal (see Table 5, 9 SciPap 33(1) HDI Model 2.1 for more details). Table 5. The impact of selected indicators of sustainable development on HDI in years 2010-2022 for EU countries with a higher economic level (HDI - Model 2.1). term estimate std.error statistic p.value p.value.signif log(CMUR) -0.003839 0.002159 -1.778 0.07827 ns log(MAFO) 0.01592 0.005584 2.851 0.00522 ** log(REPR) 0.009492 0.007244 1.31 0.1928 ns log(TRRM) 0.006675 0.002496 2.674 0.00865 ** log(GMWA) -0.009365 0.00405 -2.312 0.02266 * log(GPWA) 0.04054 0.008633 4.696 7.771e-06 *** log(AEII) -0.009631 0.003674 -2.621 0.01002 * log(AETB) -0.02084 0.006153 -3.387 0.0009845 *** log(ETRE) 0.03664 0.009033 4.056 9.405e-05 *** log(SETTRE) -0.007416 0.00843 -0.8797 0.381 ns log(SREFEC) 0.00193 0.00314 0.6147 0.54 ns Note: *** p ≤ 0.001 highly significant, ** 0.001 < p ≤ 0.01 strongly significant, * 0.01 < p ≤ 0.05 significant, ns 0.5 < p non-significant. Source: Authors. For EU countries with a higher economic level than the EU average, the largest statistically significant negative effect on HDI is represented by air emissions accounts totals bridging to emission inventory totals (AETB) at a 0.1% level, meaning that a 1% increase in AETB is associated with an average reduction in HDI of 0.02084%, all else being equal. Further, air emission intensity from industry (AEII) and generation of municipal waste per capita (GMWA) at a 5% level are statistically significant but smaller negative impacts on HDI. That is, a 1% increase in AEII is associated with an average reduction in HDI of 0.009631% and a 1% increase in GMWA translates into an average reduction in HDI of 0.009365%, all else being equal. The results are shown in more detail in Table 5 - HDI Model 2.1. Table 6. The impact of selected indicators of sustainable development on HDI in years 2010-2022 for EU countries with a lower economic level (HDI - Model 2.2). term estimate std.error statistic p.value p.value.signif log(CMUR) 0.005101 0.001942 2.627 0.009311 ** log(MAFO) 0.005786 0.008809 0.6569 0.512 ns log(REPR) 0.02375 0.008633 2.751 0.006516 ** log(TRRM) 0.001047 0.00156 0.6711 0.503 ns log(GMWA) -0.00988 0.005942 -1.663 0.09799 ns log(GPWA) 0.01613 0.005521 2.922 0.003888 ** log(AEII) 0.004957 0.002401 2.065 0.0403 * log(AETB) -0.0004221 0.006036 -0.06993 0.9443 ns log(ETRE) 0.03247 0.006972 4.657 5.954e-06 *** log(SETTRE) -0.02952 0.008194 -3.602 0.0004014 *** log(SREFEC) 0.01295 0.004229 3.062 0.002512 ** Note: *** p ≤ 0.001 highly significant, ** 0.001 < p ≤ 0.01 strongly significant, * 0.01 < p ≤ 0.05 significant, ns 0.5 < p non-significant. Source: Authors. The impact of the assessed sustainable development indicators on the HDI for group of EU countries with a lower economic level than the EU average in 2010-2022 is shown in Table 6 (HDI - Model 2.2). The largest positive impacts on HDI in the years under review were Environmental tax revenues (ETRE) at a 0.1% level and Resource productivity (REPR) at a 1% level. That is, a 1% increase in ETRE is associated with an average increase in HDI of 0.03247% and a 1% increase in REPR is associated with an average increase in GDP p.c. of 0.02375%, other things being equal. Generation of packaging waste per capita (GPWA) and share of renewable energy in gross final energy consumption by sector (SREFEC) at a 1% level also had a positive impact on HDI. That is, a 1% increase in GPWA is associated with an average increase in GDP p.c. of 0.005101% and a 1% increase in SREFEC is associated with an average increase in HDI of 0.01295%, all else being equal. A smaller statistically significant 16 SciPap 33(1) Annexes Annex 1. The Effect of selected indicators of sustainable development on GDP per capita for 27 EU countries in 2010-2022 (GDP – Model 1). term estimate std.error statistic p.value p.value.signif log(CMUR) -0.004356 0.00783 -0.5564 0.5784 ns log (MAFO) 0.229 0.03004 7.623 2.98e-13 *** log (REPR) 0.2306 0.03151 7.32 2.112e-12 *** log(TRRM) 0.02825 0.00728 3.88 0.0001272 *** log(GMWA) -0.03901 0.02224 -1.754 0.08044 ns log(GPWA) 0.08501 0.02548 3.337 0.0009503 *** log(AEII) -0.02397 0.01138 -2.107 0.03594 * log(AETB) 0.1902 0.02631 7.23 3.715e-12 *** log(ETRE) 0.3269 0.02905 11.26 6.606e-25 *** log(SETTRE) -0.3564 0.03276 -10.88 1.369e-23 *** log(SREFEC) 0.02578 0.01451 1.776 0.07669 ns Note: *** p ≤ 0.001 highly significant, ** 0.001 < p ≤ 0.01 strongly significant, * 0.01 < p ≤ 0.05 significant, ns 0.5 < p non-significant. Source: Authors. Annex 2. The Impact of selected indicators of sustainability development on HDI for 27 EU countries in 2010-2022 (HDI – Model 2). term estimate std.error statistic p.value p.value.signif log(CMUR) 0.004379 0.001415 3.094 0.002154 ** log(MAFO) 0.00602 0.005431 1.109 0.2685 ns log(REPR) 0.01995 0.005695 3.504 0.0005257 *** log(TRRM) 0.002748 0.001316 2.088 0.03758 * log(GMWA) -0.01037 0.004021 -2.579 0.01038 * log(GPWA) 0.01986 0.004606 4.312 2.172e-05 *** log(AEII) 0.001604 0.002057 0.7798 0.4361 ns log(AETB) -0.01101 0.004755 -2.316 0.0212 * log(ETRE) 0.02978 0.005251 5.672 3.204e-08 *** log(SETTRE) -0.02334 0.005922 -3.941 0.0001003 *** log(SREFEC) 0.009135 0.002623 3.482 0.000568 *** Note: *** p ≤ 0.001 highly significant, ** 0.001 < p ≤ 0.01 strongly significant, * 0.01 < p ≤ 0.05 significant, ns 0.5 < p non-significant. Source: Authors.