The paper analyses the linkages between GDP per capita, greenhouse gas (GHG) emissions, and renewable energy (RE) in the total final energy consumption and green investments (PICE) which are measured as private investments, jobs, and gross value added related to circular economy sectors. The object of the analysis is the EU countries during the 2008-2016 period (crisis and post-crisis period). In the paper, data from the following databases was used: the Eurostat, the World Data Bank, and the European Environmental Agency. For addressing the linkages between the aforementioned indicators, the following methods were applied: panel unit root test, Pedroni panel cointegration tests, and the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) panel cointegration techniques. The findings show that FMOLS and DOLS demonstrate the same results as GHG, PICE, RE influence on GDP of the EU countries. The findings prove there is linking between gross domestic product per capita, greenhouse gas emissions, renewable energy in the total final energy consumption and green investments. The findings also show that green investment (PICE) could provoke the growth of GDP per capita by 6.4%, the decline of GHG by 3.08%, and the increase of renewable energy in the total final energy consumption by 5.6%.

Implementing Sustainable Development Goals (SDGs) and increasing environmental issues provokes changes in consumers’ and stakeholders’ behavior. Thus, stakeholders try to invest in green companies and projects; consumers prefer to buy eco-friendly products instead of traditional ones; and consumers and investors refuse to deal with unfair green companies. In this case, the companies should quickly adapt their strategy corresponding to the new trend of transformation from overconsumption to green consumption. This process leads to increasing the frequency of using greenwashing as an unfair marketing instrument to promote the company’s green achievements. Such companies’ behavior leads to a decrease in trust in the company’s green brand from the green investors. Thus, the aim of the study is to check the impact of greenwashing on companies’ green brand. For that purpose, the partial least-squares structural equation modeling (PLS-PM), content analysis and Fishbourne methods were used. The dataset for analysis was obtained from the companies’ websites and financial and non-financial reports. The objects of analysis were Ukrainian large industrial companies, which work not only in the local market but also in the international one. The findings proved that a one point increase in greenwashing leads to a 0.56 point decline in the company’s green brand with a load factor of 0.78. The most significant variable (loading factor 0.34) influencing greenwashing was the information at official websites masking the company’s real economic goals. Thus, a recommendation for companies is to eliminate greenwashing through the publishing of detailed official reports of the companies’ green policy and achievements.

The paper investigates the relationships between economic, social, and environmental dimensions of sustainable development. GDP growth represents the main economic dimension, greenhouse gas (GHG) emissions and renewable energy consumption the environmental dimension, and corruption the social dimension of sustainable development. The investigation of these relationships is based on the concept of the Environmental Kuznets Curve hypothesis about the non-linear relationship between economic growth and environmental pollution. The authors used the panel data of EU countries and Ukraine for 2000–2016 years from the Eurostat database. The obtained results confirmed the Environmental Kuznets curve hypothesis for the EU and Ukraine. All the indicators were statistically significant at 1% and 5% levels. The findings proved that increasing renewable energy (RE) by 1% led to a decline of GHG in the interval (0.166103, 0.220551), and аn increase of the Control of Corruption Index by 1% provoked a decline of GHG by 0.88%. The conducted study enabled the authors to conclude that Ukraine needs to increase the GDP level per capita given the economy diversification and via the introduction of more effective and “clean” production technologies.

This paper investigates the impact of renewable energy sources (RESs), CO₂ emissions, macroeconomics, and the political stability in a country on the Gross Domestic Product (GDP). The authors analyse the dynamics of RESs use, CO₂ emissions, and GDP development and also test the following hypotheses: (1) The country’s economic growth is related to the energy consumption, in terms of both human resources and capital; (2) the share of the renewable energy consumption of the total energy consumption has a positive impact on the economic growth; and (3) the share of the renewable energy consumption of the total energy consumption is unrelated to the economic growth. To test the above hypotheses, the authors use the modified Cobb-Douglas production function, which also considers RES production volumes, CO₂ emissions, and economic growth. The study employs data between 1995 to 2015 from the candidate and potential candidate countries for the EU membership. The data are drawn from the World Bank and Eurostat. The analyses entail panel unit root tests, Pedroni panel cointegration tests, fully modified OLS (FMOLS), dynamic OLS (DOLS) panel cointegration techniques, and the Vector Error Correction model (VECM). The findings confirm the relationship between RESs, CO₂ emissions, and the GDP. For the EU countries, RESs as human resources and capital have an impact on the GDP. Moreover, the results reveal a correction retraction when the economic growth leads to an increase in renewable energy consumption. The investigation also finds that candidate and potential candidate countries for the EU membership should foster renewable energy development. The authors conclude that developing affordable and effective instruments and mechanisms to boost the RES implementation is necessary to decrease the anthropogenic impact on the environment (in particular, decreasing CO₂ emissions) without any attendant reduction in the economic growth.

Income distribution can cause large-scale transformations in human resources structure, essential changes of economic outputs via its impact on life satisfaction and motivation of work. Thus, the overall objective of this research is to improve methodological tools of income distribution analysis based on identifying the links between different structural indicators of income inequality and the most essential features of social and economic well-being. We conducted comparative analysis of EU Member States and Ukraine. We used structural analysis based on two forms of income distribution—functional (share of “labour” in Gross domestic product - GDP) and household one (ratio of incomes measured by special decile coefficients) to identify income inequality and inconsistencies in distributive strategies. By grouping European countries according to economic well-being (described as GDP per capita) and inequality in income distribution (based on Gini coefficient), we determined apparent tendencies in distributive policies and revealed links between income distribution and connected social-economic features of well-being. We conclude that countries with the most stable and clear patterns in income distribution have distinct connections between the share of labour costs in GDP and successes in social and economic spheres, including human development level, property rights protection, GDP growth, possibilities for taxation and budgeting of social programmes.