Assessment of Green Investments’ Impact on Sustainable Development: Linking Gross Domestic Product Per Capita, Greenhouse Gas Emissions and Renewable Energy

The well-developed countries have more options to attract tourists and generate profit from the tourism development. At the same time, the high volume of CO2 emissions, ecological risks, polluted nature restrict the tourism development in the country. The reorientation of global development to green growth provokes transformations in all policies of the country’s development. It allows green countries to attract more tourists. In this case, the paper aims to analyze the relationships between economic growth, ecological indicators, and tourism development. Ukraine has chosen the EU vector of development. In this case, it is necessary to identify the targets for synchronizing the Ukrainian policies (economic, ecological, social, tourism, etc.) with the EU. The objects of the investigation were Ukraine and Visegrad countries for 2000-2020 years. The panel data was generated from World Data Bank, Eurostat, European Environmental Agency, and Ukrstat. The dependent variable – GDP (as an indicator of economic growth), independent – greenhouse gas emissions and share of renewable energy in the total energy consumption (ecological indicators), the volume of tourists (indicators of tourism development). At the first stage, the study used bibliometric analysis to identify publication activities’ general tendency on the analyzed issues. The following methods were applied to check the hypothesis on cointegration between variables: panel unit root test, Pedroni panel cointegration tests, and the fully modified ordinary least squares and dynamic ordinary least squares panel cointegration techniques. The findings confirmed the relationships between economic, ecological, and tourism development. Thus, the decline of greenhouse gas emissions leads to increasing tourists, and as a consequence, it provokes GDP growth.

Objectives: This study aims to check the impact of globalization and macroeconomic variables on environment degradation in low income countries. This study also tested the existence of Kuznets curve. Methods/Statistical Analysis: Greenhouse gases emission is used as proxy of environment degradation. Panel data was taken from 1996 to 2015 for Zimbabwe, Burkina, Uganda, Tanzania, Malawi, Mali, Guinea, Gambia, Madagascar, Central Africa, Niger, Burundi, Faso, Rwanda, Senegal, Mozambique and Benin. After checking the cross sectional dependence, Cross Sectional Augmented Dickey Fuller (CADF) panel unit root test is used to check the stationary of the variables then Pedroni Panel CoIntegration Test and Fully Modified Ordinary Least Square (FMOLS) are applied. Findings: Co-integration is found among low income countries. Globalization, urban population and renewable energy have positive effect on environment degradation while innovation index has negative effect on greenhouse gases emission. The inverted U shaped relationship is found between environment and globalization which means that globalization decrease environment degradation after reaching at specific level. Application/Improvements: To improve the environment, globalization should be increased continuously because after reaching at certain level, it will decrease the environmental degradation. Keywords: Environment Degradation; Globalization; Innovation Index; Kuznet Curve; Urbanization

The paper deals with the analysis of the green investment impact on the energy efficiency gap. The findings of the bibliometric analysis proved the increasing trend of the published documents on green investment and the energy efficiency gap. In the study, the author used Scopus Tools Analysis, Web of Science Results Analysis, and VOSviewer for providing the bibliometric analysis. In the paper the author checked the hypothesis as follows: cointegration exists between GDP, energy efficiency, green investment and share of renewable energy; green investment had a positive impact on the percentage of renewable energy; green investment had a positive effect on the countries energy efficiency and decreased the energy efficiency gap. The author used the unit root test for checking the stationarity of the selected variables. Pedroni panel cointegration test used for monitoring the cointegration between variables. Fully Modified Least Square model used for identifying the relationship between variables. The findings proved the stationarity of the data at the first level. It allowed providing the Pedroni cointegration test and long-run covariance test. Thus, the empirical results showed that increasing green investment leads to an increase in energy efficiency by 0.56 points, gross domestic product per capita – 0.18 points, renewable energy – 0.39 points. The increasing of renewable energy allowed increasing energy efficiency by 0.38 points, gross domestic product per capita – 0.19 points, green investment – 0.54 points. Besides, rising of the countries’ energy efficiency allowed growing of gross domestic product per capita by 0.27 points, green investment – 0.31 points, and declining of renewable energy by 1.14 points. If the increase of energy efficiency leads to a decrease in the energy efficiency gap the following could be concluded: increasing green investment leads to reducing of energy efficiency gap; increasing of renewable energy in the total energy consumption allowed declining the energy efficiency gap. In this case, in Ukraine, the mechanisms for improving the investment climate should be developed at the national level, considering the EU experience. Such activities allowed to attract additional green investment in renewable energy projects. Keywords: green investment, cointegration, correlation, green finance.

The dynamics of green innovation, environmental policy and energy structure for environmental sustainability; Evidence from AfCFTA countries

Global warming and climate change are caused by anthropogenic greenhouse gas (GHG) emissions from rising energy consumption due to population and economic growth. Over the past decade, information and communication technology (ICT) usage has increased which may increase energy utilization and GHG emissions. Conversely, ICT's clean technologies can minimize pollution. Therefore, this study investigated the dynamic influences of ICT, economic growth, population, and energy use on GHG emissions in Malaysia by employing the autoregressive distributed lag (ARDL) approach using data from 1990 to 2021. The results of the ARDL bounds test indicated the existence of a long-run link between the variables. The results revealed that a 1% increase in the number of Internet users could increase GHG emissions by 0.013% in the short run but cut GHG emissions by 0.077% in the long run. Additionally, economic growth, population, and energy usage have a positive association with GHG emissions. The robustness of the ARDL outcomes has been checked by using the Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR) methods. This article offers additional policy proposals for emission reduction and sustainable development by promoting renewable energy use and financing green ICT.

Environmental sustainability constitutes a strategic priority for Germany, with the circular economy serving a crucial function in its realization. Circular practices foster sustainable development by decreasing reliance on finite resources, minimizing waste, and reducing greenhouse gas (GHG) emissions. The circular economy provides ecological advantages and strengthens economic resilience through the promotion of innovation, enhancement of supply chain efficiency, and creation of green jobs. Complementary measures, including the preservation of natural capital, the enactment of structural economic reforms, and the implementation of environmental taxes, enhance sustainability objectives. Ecosystem conservation enhances carbon absorption, structural changes facilitate low-emission industries, and environmental taxes incorporate environmental costs. In contrast, industrial activity continues to be a significant contributor to GHG emissions, necessitating policy examination. This study analyzes the relationships between the circular economy, natural capital, structural change, environmental taxation, and industrial activities on GHG emissions in Germany from the first quarter of 2010 to the fourth quarter of 2022. The study employs wavelet coherence analysis (WCA), fully modified ordinary least squares (FMOLS), and dynamic ordinary least squares (DOLS), demonstrating that circular economy practices, natural capital, structural changes, and environmental taxes significantly reduce GHG emissions. Conversely, industrial activities continually elevate GHG emissions in Germany. Moreover, WCA further reveals the time–frequency dynamics and co-movement patterns between key variables and GHG emissions, enabling the detection of both short-term and long-term dependencies. The results indicate that enhancing environmental sustainability in Germany could be effectively achieved by mandating the integration of recycled materials within key industrial sectors to improve environmental sustainability, which would help lower resource extraction and related GHG emissions.

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.

Purpose Considering the evolving importance of green finance, this study uses climate-related development mitigation finance as a proxy of green finance and investigates the impact of green finance on ecological footprint as an indicator of environmental quality along with the influence of economic growth, renewable energy, greenhouse gas emissions, trade openness and urbanization across 47 developing countries over the period 2000–2018. Design/methodology/approach After finding the presence of cross-sectional dependency among variables, the second-generation panel unit root test was employed to detect the order of integration among the variables. Since all the variables were found to be stationary, Westerlund cointegration technique was employed to detect the long-run relationship among the variables. Then, the long-run elasticity among the dependent and independent variables was tested using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and pooled mean group–autoregressive distributed lag (PMG–ARDL) approaches. Findings The empirical findings suggest the presence of long-run relationship among all the variables, namely, ecological footprint, green finance, economic growth, renewable energy consumption, greenhouse gas emissions, trade openness and urbanization for the selected developing countries in the sample. Furthermore, economic growth, greenhouse gas emissions, trade openness and urbanization, all have a positive and significant impact on the ecological footprint, whereas renewable energy consumption and green finance have a significant and negative impact on the ecological footprint, which supports the view that environmental quality is improved with the greater use of renewable energy technologies and allocation of greater amounts of more green finance. Originality/value The empirical results of this study offer policymakers and regulators some implications for environmental policy for protecting the countries from ecological issues.

Tourism drives economic growth and impacts the environment. This study examines the nonlinear relationships among tourism development, economic growth, foreign direct investment, economic globalization, renewable energy consumption, and greenhouse gas (GHG) emissions in the Organization for Economic Co-operation and Development economies from 1995 to 2020. It also explores how green technological innovation (GTI) moderates and influences the link between tourism development and GHG emissions. We employ panel data analysis techniques, including fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), canonical cointegrating regression (CCR), feasible generalized least squares (FGLS), and the method of moments quantile regression (MMQR). We find an inverted U-shaped relationship between tourist numbers and GHG emissions and a U-shaped relationship between tourism receipts and GHG emissions. The moderating effect of GTI flattens the inverted U-shaped curve, thereby reducing the negative environmental impact of tourism to some extent. Our findings suggest that advancing GTI in the tourism industry is crucial for mitigating environmental degradation while promoting economic growth.

The rapid growth of negative consequences from climate changes provokes divergent effects in all economic sectors. The experts proved that a core catalyst which bootstrapped the climate changes was greenhouse gas emission. This has led to a range of social, economic, and ecological issues. Such issues could be solved by extending innovation and information technology. This paper aimed to check the hypothesis that innovation and information technology allowed for a reduction of greenhouse gas emissions. The author used such methodology as OLS, fully modified OLS (FMOLS), dynamic OLS (DMOLS), Dicky-Fuller and Phillips-Perron tests. The research is informed by the report of the World Economic Forum, World Data Bank, Eurostat for the Visegrád countries (Hungary, Poland, Check Republic, Slovakia) for the period of 2000–2019. The findings were confirmed in models without control variables, and an increase of 1% of patents led to reducing greenhouse gas (GHG) emissions by 0.28% for Poland, 0.28% for Hungary, 0.38% for the Slovak Republic and 0.46% for the Czech Republic. At the same time, for the models with control variables, only Hungary experienced a statistically significant impact. There, an increase of patents by 1% led to reduction of GHG emissions by 0.22%. The variable R&D expenditure was statistically significant for all countries and all types of models (with and without control variables). The increase of R&D expenditure provoked a decline of GHG emissions by 0.29% (without control variables) and 0.11% (with control variables) for Poland, by 0.26% (without control variables) and 0.41% (with control variables) for Hungary, by 0.3% (without control variables) and 0.23% (with control variables) for the Slovak Republic and by 0.54% (without control variables) and 0.38% (with control variables) for the Czech Republic.

Economic growth drives increased demand for resources, placing greater pressure on the agricultural sector. While the adoption of advanced technologies and increased capital investment can enhance productivity, they also have environmental consequences, contributing to greenhouse gas emissions. Based on this interconnected issue, this study aims to examine the long-term relationships between economic growth, agricultural productivity, gross fixed capital formation, and greenhouse gas emissions in Indonesia, utilizing data from the period 1965-2021. The study employs the Dynamic Ordinary Least Squares (DOLS) and Fully-Modified Ordinary Least Squares (FMOLS) methods, and includes robustness checks using the Canonical Cointegration Regressions (CCR) method. To provide a more comprehensive insight, the study also employs the pairwise Granger causality approach to detect the direction of the relationships. In concise terms, the results suggest that agricultural productivity, gross fixed capital formation, and greenhouse gas emissions have a positive long-term influence on economic growth. Additionally, gross fixed capital formation has a negative effect, while economic growth has a positive long-term impact on agricultural productivity. Furthermore, agricultural productivity has a negative impact, while economic growth indicates a positive long-term effect on gross fixed capital formation. Moreover, economic growth positively influences greenhouse gas emissions over the long term. Lastly, the study found three bidirectional causalities, with greenhouse gas emissions as the central figure. These important findings provide crucial information for policymakers, economists, and environmentalists, giving a nuanced understanding of the intricate relationships between economic activities and environmental consequences, as well as aiding in the formulation of sustainable strategies for green economic growth, especially in Indonesia.

The development of green innovation in achieving Sustainable Development Goals (SDGs) is gaining popularity in recent works. However, the perspective from emerging economies is limited leaving them behind in the drive toward global sustainability. Therefore, this study provides new insights into how green innovation development and the quality of institutions have influenced green energy adoption and overall Sustainability using 30 emerging economies from 1990 to 2020. The study employs three econometric models—Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Ordinary Least Squares (OLS) to make a comparative analysis. The findings show the varying and pivotal role of technological advancements, institutions, and green energy in reducing carbon footprints based on models. Notably, it was found that green innovation had a positive effect (FMOLS), and negative effect (DOLS and OLS) on CO2 emissions. Renewable energy had a negative effect (FMOLS and OLS), and a positive effect (DOLS) on CO2 emissions. Again, institutional quality showed a positive effect (DOLS and FMOLS) and a negative effect (OLS) on CO2 emissions. The study believes the DOLS model exhibited the most robust explanatory power, with the highest explanatory power of 99.9%. These results provide greater insights and the comprehensive policies outlined can help policymakers formulate working policies to bolster green innovation, improve green energy development, and strengthen institutional frameworks toward achieving overall SDGs.

Environmental policies and green technologies: Impacts on energy sustainability in the African continental free trade area

The nexus between greenhouse gas emission, electricity production, renewable energy and agriculture in Pakistan

The environmental challenges that have arisen as a result of rapid economic growth have become a hindrance to social progress. This article examines the effects of energy consumption, urbanization, industrialization, economic development, and technological innovations on South Korea's greenhouse gas (GHG) emissions. Using data from 1990 to 2021 and the autoregressive distributed lag (ARDL) method for empirical investigations, the findings indicate that fossil fuel energy consumption, urbanization, industrialization, and economic expansion all pose a threat to environmental sustainability due to their positive impact on GHG emissions. In contrast, the results suggest that renewable energy usage and technological innovations improve environmental sustainability by reducing GHG emissions in both the short and long term. In addition, the findings were validated using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR) techniques. The most significant contribution is that the findings of this study provide various policy recommendations for achieving environmental sustainability and net zero emissions in South Korea.