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The aim of the paper is to analyze how regulatory design and its framework's topics, other than macroeconomic factors, might impact green innovation by taking into consideration a brand-new renewable source of energy that is becoming more and more important in recent years: hydrogen and fuel cell patenting activities. Such activities have been used as a proxy for green technological change in a panel data of 52 countries over a 6-year period. A series of sectorial, energy regulation, and macroeconomic variables were tested to assess their impact on that technological frontier of green energy transition policy. As might have been expected, the empirical analysis carried out with the model that was prefigured confirms significant evidence of lock-in effects on fossil fuel policies. The model confirms, however, another evidence: countries already investing in renewables might be willing to invest in hydrogen projects. A sort of reinforcement to the further development of green sustainable strategies seems to derive from having already concretely undertaken this direction. Future research should exploit different approaches to the research question and address the econometric criticalities mentioned in the paper, along with exploiting results of the paper with further investigations. [ABSTRACT FROM AUTHOR]

A growing number of countries worldwide have committed to achieving net zero emissions targets by around mid-century since the Paris Agreement. As the world's greatest carbon emitter and the largest developing economy, China has also set clear targets for carbon peaking by 2030 and carbon neutrality by 2060. Carbon-reduction AI applications promote the green economy. However, there is no comprehensive explanation of how AI affects carbon emissions. Based on panel data for 270 Chinese cities from 2011 to 2017, this study uses the Bartik method to quantify data on manufacturing firms and robots in China and demonstrates the effect of AI on carbon emissions. The results of the study indicate that (1) artificial intelligence has a significant inhibitory effect on carbon emission intensity; (2) the carbon emission reduction effect of AI is more significant in super- and megacities, large cities, and cities with better infrastructure and advanced technology, whereas it is not significant in small and medium cities, and cities with poor infrastructure and low technology level; (3) artificial intelligence reduces carbon emissions through optimizing industrial structure, enhancing information infrastructure, and improving green technology innovation. In order to achieve carbon peaking and carbon neutrality as quickly as possible during economic development, China should make greater efforts to apply AI in production and life, infrastructure construction, energy conservation, and emission reduction, particularly in developed cities. [ABSTRACT FROM AUTHOR]

In this paper, the panel data of 30 provinces in China from 2011 to 2019 are analyzed by the spatial measure model and the threshold regression model. The results show that the air quality level is positively correlated with green finance, but there is no spatial effect. The spatial effect of the three influencing factors, including the degree of openness, the level of infrastructure, and the level of education, is the crowding-out effect. At the same time, variables such as human resource level, air quality, and infrastructure construction level all have threshold effects in the relationship between green finance and economic development. The research conclusions suggested that local governments at all levels should formulate policies according to the actual situation to promote the development of provinces' intensive, intelligent, and green development, and build a regionally-linked green finance development model, thereby promoting the improvement of green finance. [ABSTRACT FROM AUTHOR]

In the short, medium, and long term, a sustainable bioeconomy can help address one of the main concerns of most countries concerning the food crisis, particularly in the Latin American and Caribbean contexts, where food security and the bioeconomy are crucial for the region's development and sustainability. However, to avoid negative impacts on the environment and food production, all sectors of the bioeconomy, especially those related to biofuel production, must be sustainable and environmentally conscious. This study analyses historical correlations between three dependent variables related to basic concepts of food security and independent variables framed by biofuel production through a panel data study in eight Latin American and Caribbean countries between 2007 and 2021. Of the three econometric models analyzed, two are statistically significant. The first shows a positive correlation between biofuel production and the food production index. The third shows a negative correlation between the percentage of undernourished people and biofuel production. In conclusion, according to the historical data evaluated in the countries studied, the impact of biofuel production on the food security variables analyzed is positive. This positive relationship can be interpreted as an opportunity for the region's countries to generate additional bio-economic income, taking advantage of the region's potential and providing new opportunities for producers, especially in rural areas. [ABSTRACT FROM AUTHOR]

The overcoming of the issues on energy crisis and inequality have become the priorities as far developing as developed countries are concerned. Moreover, energy inequality has increased due to the shortage of natural gas and rising energy prices in retaliation to the economic recovery affected by the COVID-19 pandemic. This study aims to verify the linkage between the growth of renewable energy consumption and the country's economic advancement. In this context, this paper determines the main driving forces of renewable energy consumption in European countries during 2000–2018. The annual data for panel regression analysis are retrieved from the OECD. Stat and World Bank Open Data. This empirical analysis employed a set of estimation procedures such as the panel unit root test (Levin, Lin & Chu; Im, Pesaran, Shin W-Stat; ADF-Fisher Chi-square; and PP-Fisher Chi-square methods), the Pearson correlation, fixed- and random-effects models, generalized method of moments (GMM), Hausman and the robustness tests. The results from the Hausman test ratified that the fixed-effects regression model is more suitable for involved panel balanced data. The results of fixed-effects regression and GMM identified the statistically significant and positive relationship between the share of renewable energy consumption of total final energy consumption, GDP per capita, and CO2 emissions per capita for the overall sample. In turn, the total labor force, the gross capital formation, and production-based CO2 intensity are inversely related to renewable energy consumption. The identified effects could provide some insights for policymakers to improve the renewable energy sector towards gaining sustainable economic development. [ABSTRACT FROM AUTHOR]

Global warming has emerged as a serious threat to humans and sustainable development. China is under increasing pressure to curb its carbon emissions as the world's largest emitter of carbon dioxide. By combining the Tapio decoupling model and the environmental Kuznets curve (EKC) framework, this paper explores the relationship between China's carbon emissions and economic growth. Based on panel data of 29 provinces from 2007 to 2016, this paper quantitatively estimates the nexus of carbon emissions and economic development for the whole nation and the decoupling status of individual provinces. There is empirical evidence for the conventional EKC hypothesis, showing that the relationship between carbon emissions and per capita gross domestic product (GDP) is an inverted U shape and that the inflection point will not be attained soon. Moreover, following the estimation results of the Tapio decoupling model, there were significant differences between individual provinces in decoupling status. As a result, differentiated and targeted environmental regulations and policies regarding energy consumption and carbon emissions should be reasonably formulated for different provinces and regions based on the corresponding level of economic development and decoupling status. [ABSTRACT FROM AUTHOR]

Indepth research on the impact of energy endowment on provincial green development provides a new perspective for achieving high-quality provincial economic development. Based on 30 provinces' panel data in China from 2009 to 2020, this study first constructs an index system to analyze energy endowment and provincial green development; then it explores the mechanism by which energy endowment affects provincial green development, including the moderating role of environmental regulation and the mediating role of energy efficiency. The results show that energy endowment can significantly curb provincial green development when environmental regulations are not taken into account. Moreover, environmental regulation has moderated the process of energy endowment affecting provincial green development. Energy efficiency has mediated the process of energy endowment affecting provincial green development. From a geographical viewpoint, the moderating effect of environmental regulation has regional heterogeneity but the mediating effect of energy efficiency does not. The conclusions of this research may supply applicable recommendations for provincial green development in China. [ABSTRACT FROM AUTHOR]

This study examines the dynamic connection between green energy, employment, fossil fuel energy, and human development index including additional variables such as education, life expectancy, and poverty in panel data of 30 developing countries from 1990–2017. Previous studies analyzed the total energy consumption on the human development index, whereas the differential effect of green and fossil fuel energy with employment and human development index has not been examined. The empirical exercise is based on the panel co-integration test, panel fully modified ordinary least squares, dynamic ordinary least squares, and vector error correction estimation approaches. The results reveal that all variables are co-integrated. The results of regression analysis indicate that green energy, education, life expectancy, and employment increase the human development index, but fossil fuel energy and poverty decrease the human development index by −0.016 and 0.023%. In addition, the vector error correction model designates that there is bidirectional causality between green energy consumption and the human development index. Therefore, for developing countries, the development and utilization of green energy sources (wind, solar, geothermal, etc.) are needed. Moreover, these countries should rely less on fossil fuel energy because it causes a decrease in the HDI. [ABSTRACT FROM AUTHOR]

In China, one of the most pressing issues that have to be addressed is how to best manage the link between energy consumption and sustainable development. Given this context, the goal of the current article is to investigate the effect of renewable energy consumption on sustainable development. Using provincial panel data from 2005 to 2020 and the province and year fixed effects model for an empirical study, we discover that renewable energy consumption has a favorable impact on sustainable development. Similarly, the findings suggest the influence of non-renewable energy consumption on sustainable development is weaker than that of renewable energy consumption. Moreover, the heterogeneity of the influence of renewable energy consumption and nonrenewable energy consumption on sustainable development in eastern, central, and western China has been demonstrated as well. Notably, the two-stage least squares approach and generalized system method of moments are utilized to examine the robustness of this issue, and the reliability and robustness of the conclusions presented in this study are also confirmed. To sum up, the results in this article provide more evidence that the use of energy is an important contributor to achieving sustainable development in China and realizing the target set for sustainable development in 2030. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The future of opencast mining and energy production based on conventional resources is one of the most important issues being discussed in international forums. The whole discussion is becoming increasingly heated and takes on a special significance with the drastic increase in energy commodity prices that has occurred with the outbreak of war in Ukraine. Especially in a country like Poland, these issues are accompanied by heated discussions between miners, the government and citizens. It should be emphasised that Polish lignite mining currently produces about 35% of the cheapest electricity in Poland and also creates many jobs. The aim of this study is to assess the possibility of continuing opencast mining and its impact on rural development—both from an environmental and socio-economic point of view. The study was conducted for two municipalities in Poland where opencast lignite mining plays an important role, namely Kleszczów and Kleczew. As a result, it was found that in the case of the studied municipalities, the presence of opencast mining has contributed to their development, and the application of modern environmental protection technologies and recultivation have reduced the difficulties associated with mining. On the other hand, the decision to start mining should be the result of a comparison between the potential environmental and social benefits and damages. In some cases, mining is beneficial for community development and leads to new opportunities for agriculture and tourism after reclamation. The study is a combination of different methods, i.e., case studies, GIS remote sensing analysis (based on Landsat data) and econometric analysis for selected socio-economic data. [ABSTRACT FROM AUTHOR]

Mitigating haze pollution is of practical significance to the green economy, and the development of digital finance may help achieve this goal. However, the effect of digital finance on haze pollution has not been systematically explained. Based on Chinese prefectural panel data for the 2011–2016 period, this study on haze concentration, technological innovation, and digital inclusive finance index as the dependent variable, mediating variable, and the core independent variable, respectively, investigated whether digital finance has improved haze pollution control in China using fixed effect (FE) and random effect (RE) models, a mediating effect model, a threshold panel model, and a dynamic spatial Durbin model (SDM). Four key results were obtained. (1) Digital finance significantly decreased haze pollution. After accounting for potential endogeneity, this conclusion was still valid. (2) The analysis of the influencing mechanism showed that digital finance was conducive to haze reduction by promoting regional innovation capabilities. (3) There was a nonlinear relationship between the influence of digital finance and haze pollution. Specifically, the impact of digital finance on haze pollution has gradually increased with the improvement of regional innovation capabilities. (4) Haze pollution displayed a significant positive spatial agglomeration in China. Digital finance can alleviate local haze pollution but will aggravate haze pollution in adjacent areas. Based on the results of this study, some pertinent policy suggestions were proposed. [ABSTRACT FROM AUTHOR]

Standardization in energy-saving and emission-reduction measures has become increasingly important. The impact of standardization on carbon-emission efficiency in China was explored by using panel data from 2002 to 2017. The results showed that standardization significantly improved China's carbon-emission efficiency, which remained robust after a series of tests. Furthermore, the development of industry standards had a greater effect on the improvement of carbon-emission efficiency in the economically developed coastal areas, while the development of national standards significantly promoted the improvement of carbon-emission efficiency in the inland areas. An assessment of the impact mechanism demonstrated that standardization affects carbon-emission efficiency through technological progress, industrial modernization, and economies of scale. We compared our findings with the existing literature regarding the governance of a low-carbon economy; we also considered the subsequent policy implications of our findings in terms of sustainable economic development. [ABSTRACT FROM AUTHOR]

Based on the background of China's "carbon neutral" policy and the booming digitalization, how does environmental regulation affect green economy performance? The existing literature has studied the impact of energy consumption on green economic performance. However, the literature has ignored the impact of carbon dioxide emissions on China's green economy performance. In this regard, this research uses the non-radial distance function (NDDF) to calculate the green economic performance of China's prefecture-level cities, and uses the dynamic panel threshold model and the systematic GMM method to study the nonlinear impacts and mechanisms of environmental regulation, digital development, technological innovation, and industrial structure upgrade on green economic performance. The panel data set contains 228 Chinese cities from 2003 to 2019. The following findings are established: first, after adding carbon dioxide emissions to China's green economy performance, the environmental performance was reduced, and the green economy performance was also reduced. Second, the impact of environmental regulations on green economic performance has a double-threshold effect, with threshold values of −0.267 and 3.602, and this double-threshold effect has temporal and regional heterogeneity. Third, environmental regulations of different intensities have a single-threshold effect between digital development, technological innovation, and industrial structure upgrade, with threshold values of 2.955, 3.957, and 2.249, respectively. Fourth, digital development, technological innovation, and industrial structure upgrade promote green economic performance. Fifth, environmental regulation acts on green economic performance through the transmission of digitalization, technological innovation, and industrial structure upgrade. Based on these empirical findings, this research suggests that Chinese local governments should appropriately increase the intensity of environmental regulations, strengthen the digital application and technological innovation, and promote the upgrading of industrial structure to achieve the improvement of urban green economic performance. [ABSTRACT FROM AUTHOR]

This study investigated the contributions of human capital and physical capital to economies at different stages by measuring the economic development with the traditional GDP and green GDP. The traditional GDP stood for the quantity of economic growth, and the green GDP, taking both the energy consumption and environmental pollution into account, was employed to represent the sustainability of economic development. We used a panel data of 143 countries and regions during the period from 1990 to 2014, and results showed that the elasticities of output with respect to human capital were greater compared to physical capital, while green GDP was significantly more sensitive to changes in human capital than the traditional GDP. In particular, considering the unbalanced distribution of economic growth among countries and regions, we employed the quantile regression model to explore the heterogeneous roles of physical and human capital in different stages of economic development, which evidenced not only the significance but also the stability of human capital. As national economic levels grew, countries became less dependent on physical capital, yet human capital maintained its outstanding role at different stages of economic development, particularly for the building of more sustainable economies. [ABSTRACT FROM AUTHOR]

Attaining sustainable development and cleaner production is a major challenge both for developed and developing economies; income, institutional regulations, institutional quality and international trade are the key determinants of environmental externalities. The current work attempts to study the role of environmental taxes and regulations on renewable energy generation for developed economies. For that, the authors have used the annual dataset for the period 1994 to 2018. More specifically, the study investigates the impacts of environmental taxes, environment-related technologies and the environmental policy stringency index on renewable electricity generation in 29 developed countries. Given the short available data of these countries, the authors have developed panel cointegration and panel regressions models (fully modified ordinary least square (FMOLS), quantile regressions). The heterogeneous panel empirics stated that environmental regulations and income level support renewable electricity generation. The conclusions further mention that bureaucratic qualities such as decision making and trade openness tend to reduce renewable energy generation. The empirical findings allowed us to draw new narrative and implications. Overall, the conclusions argue that innovative regulations and policies can be useful for attaining specific sustainable development goals (e.g., SDG-7: cleaner and cheap energy). [ABSTRACT FROM AUTHOR]

Several studies have examined the relationship between environmental performance and economic development. However, most of them did not take sustainable development and financial development into account. The study argues that sustainable financial and economic development contributes to reducing greenhouse gas emissions. We use the panel data regression model to capture the relationship between greenhouse gas emission and sustainable economic and financial development. The panel data refers to the period of 2007–2017. The EU 25 countries were analysed. The results show that the relationship between sustainable financial development and environmental degradation is more relevant for converging economies than developed countries. We found that the variable "energy productivity" has the strongest impact on greenhouse gas emissions for both country groups (converging and developed); however, it increases for developed countries and it decreases the greenhouse gas emissions for converging economies. We also found that environmental taxes are an efficient instrument that mitigates greenhouse gas emissions, especially in developed countries group. [ABSTRACT FROM AUTHOR]