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In this paper, continuous wavelet decompositions regarding the notions of coherence and phase are used to analyze the time-frequency dynamics of the existing relationships between energy supply and economic growth for a group of European countries. The objective is to identify both the intensity and the direction of the relationship over time and a...
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Citations
... This strategy has mainly demonstrated effectiveness in instances where private debt is scarce [34,35]. For instance, government green bonds have become a prevalent tool for supporting green infrastructure, representing how government debt can straightforwardly support decarbonization [36,37]. ...
The existing literature on government debt has predominantly focused on its influence on economic growth, with relatively limited attention paid to its ecological implications. Government debt, as an important financial tool, plays an essential role in improving the quality of economic development, yet its impact on sustainable governance remains underexplored. Against this backdrop, this paper investigates the relationship between government debt and carbon reduction using a sample of Chinese listed companies from 2010 to 2023. After excluding missing and financial firm data, our final sample includes 26,535 observations. We obtained these data from the China Security Market Accounting Research (CSMAR) database and the Wind database. This study utilizes ordinary least squares (OLS) as the baseline regression and identifies a significant positive impact of government debt on carbon emissions. Further, the moderating analysis suggests that the positive impact of government debt on carbon reduction is particularly stronger in state-owned (SOEs) and heavily polluting enterprises. To ensure the robustness of these findings, we also use fixed-effects models and the generalized method of moments (GMM), validating the consistency of the findings. This research provides critical practical and theoretical insights for regulators and adds to the prevailing body of literature on emissions reduction.
... From the mid-20th century to the present, the global energy market underwent significant transformations that deeply impacted international political and economic interactions. The literature analyzes the drivers of political and economic changes in the energy sector from multiple dimensions, including technological innovation [24], environmental sustainability [25], market supply and demand dynamics [26], and new energy industry policies [27][28][29]. It also examines the influence of geopolitics on the energy market [30] and the importance of environmental sustainability in addressing global concerns such as energy security and climate change [30]. ...
This study analyzes the impact of global geopolitical changes on new/renewable energy (NRE) policies and their roles in enhancing national energy security, elevating international stature, and influencing the global energy market. Using game theory, it reveals how NRE policies promote technological innovation, diversify energy supply, and strengthen international collaboration, thus advancing the global energy system towards a low-carbon transition and improving international energy governance. NRE policies significantly enhance national energy security by reducing dependency on single energy sources, facilitate the global shift to low-carbon energy, and intensify international cooperation. The effectiveness of these policies in driving energy transformation is notable, and they are expected to remain crucial for global energy security and sustainable transition. Recommendations include strengthening the stability and security of energy supply chains through enhanced oversight, increasing investment in R&D and innovation to reduce costs, fostering international cooperation for better policy coordination, and implementing diversified energy policies to encourage the adoption of NRE. These measures will address challenges from global geopolitical dynamics and drive the global energy system towards sustainability and efficiency.
... Researchers have investigated the effects of Sustainable Finance in numerous fields by building on these assessment approaches [27]. Several studies have looked at the impacts of Sustainable Finance on pollution and carbon emissions because it intends to encourage ecologically friendly projects and enterprises. ...
Introducing sustainable credit protection by companies depends on eco-friendly funding that accelerate businesses' technical development and transformation. This study investigates the sustainable financing roles through green credit legislation which impacted state owned enterprises and non state owned enterprises. We have investigated our hypothesis using the Propensity Score Matching Difference-in-Differences (PSM-DID) model. For this purpose we collected data of businesses listed on the Shanghai and Shenzhen stock exchanges that are country's most polluting publicly listed enterprises between 2009 and 2021. The results of the study reveals that liquid Finance and industrial Credit experienced a meteoric rise while the use of illiquid debt financing has dropped significantly among highly polluting organizations. This pattern has intensified after China introduced its “sustainable credit guidelines.” Additionally, businesses in areas with lower sustainable development indices are more likely to feel the consequences of sustainable credit programs. However, there is still a need for prudent capital flow allocation in response to the personalized financing preferences resulting from the sustainable credit policy at the business level, even if China's sustainable credit rules have unquestionably reduced the use of illiquid debt financing by severely polluting enterprises. Policy implications include improving the direction signalled to these businesses via sustainable funding.
... The inclusion of S is essential because, without it, the coherency would be consistently equal to one across all scales and times. The phase difference between the two chronicles serves as a complementary indicator that enables us to determine the direction of the relationship, as well as the mutual influences between the variables, with the concept of a Leader (Awada and Mestre, 2023). The phase difference between {X} and {Y} is depicted in Eq. (5): ...
This study examines the complex and time-varying relationship between residential energy demand (including electricity, geothermal, and solar energy) and climate change using wavelet analyses with monthly USA data from January 1990 to March 2023. The results show that residential energy demand and climate change indicators exhibit a time-varying interrelationship with cyclical and lag effects. Specifically, before 2021, a positive correlation between residential electricity demand and carbon dioxide (CO2) emissions in short-term frequencies was found, but the relationship reversed thereafter, with an increase in CO2 levels influencing and decreasing residential electricity demand. In the long run frequencies, the link between residential power consumption and CO2 emissions shifted over time, exhibiting inconsistent co-movement. The co-movements between residential geothermal and CO2 show predominantly positive correlations, with CO2 leading the relationship in the short run, while geothermal leads the co-movements in the long run. In both short and long-term frequencies, the dependency and co-movement between residential solar and CO2 are mixed, with residential solar leading to positive correlations and CO2 leading to negative correlations. Therefore, improved insulation, energy-efficient windows, and high-efficiency heating systems can all assist in reducing heat loss and the total energy demand for domestic heating and subsequently low CO2 emissions.
... recognition from stakeholders, while high-environmental-risk enterprises face more environmental regulatory pressure, transformation difficulties, and pollution control costs. This requires greater investment in green transformation than for lowenvironmental-risk industries [58]. To meet various environmental regulatory requirements, some innovative resources may be occupied by environmental risk factors such as pollution control, resulting in a reduction in the improvement of ESG ratings on green innovation and GTFP. ...
Against the backdrop of frequent extreme climates and international consensus on green and low-carbon development, Environmental, Social, and Governance (ESG) has progressively drawn increasing attention. Integrating the perspectives of stakeholder theory and signaling theory, this study employed the Malmquist-Luenberger productivity index, fixed-effects regression model, mediating effect model, propensity matching score difference-in-differences model, and a two-stage least squares method. Using the research sample of Chinese A-share listed companies between 2011 and 2021, the mechanisms linking ESG ratings and each component (the individual scores of E, S, and G) with the green innovation and green total factor productivity (GTFP) of enterprises were investigated. This study conducted heterogeneity analysis integrating regional, industry, and enterprise dimensions, fully considered the potential endogeneity issues, and conducted multiple robustness tests by exploring alternative approaches, replacing the measures of indicators, and reducing the research sample. The results demonstrated that higher ESG ratings significantly improved the green innovation and GTFP of enterprises. This improvement was achieved through the stakeholders and signaling mechanisms, and was more prominent in economically underdeveloped regions, patent-intensive industries, and industries with lower environmental risk. In addition, the impact varied among enterprises with different property rights. The findings elucidate the pathways through which soft regulation influences micro-level corporate decision-making, making significant contributions to the literature. Furthermore, this study provides a theoretical foundation and policy reference for constructing a positive feedback loop mechanism for ESG ratings and promoting the green transformation and upgrading of enterprises.
... 2.1.1. Effects of IPR protection on enterprise green innovation Justification of the exclusiveness of an intellectual property right involves more than one theory, and typical theories involved include the theory of incentives for creation and the theory of compensation for public opening [26][27][28][29][30]. Therefore, strengthening judicial protection of intellectual property is a fundamental guarantee for the promotion of the vitality and driving force of enterprise innovation. ...
In the context of high-quality economic development in China, it is important to promote green innovation development by protecting intellectual property rights (IPR). Taking the pilot policy of the intellectual property courts in Beijing, Shanghai, and Guangzhou for example in a quasi-natural experiment, this article examines the effect of IPR protection on the development of corporate green innovation and its mechanisms by using a difference-in-differences model and a mediating effect model based on Chinese enterprise data from 2011 to 2019. The study found that first, IPR protection promotes enterprise green technological innovation; second, IPR protection affects green innovation through enterprise financing constraints and R&D investment; that is, increasing enterprise R&D investment and alleviating enterprise financing constraints are two important channels through which IPR protection promotes enterprise green technological innovation.
... Fossil fuels, despite being pivotal for industrial and economic growth (Awada and Mestre, 2023), present significant environmental challenges. Consequently, enterprises' GI performance, encompassing sustainable technological, product or service advancements, is gaining focus (Liu and Wang, 2023;Cheng et al., 2021;Ma et al., 2021;Vasileiou et al., 2022). ...
... The inclusion of S is essential because, without it, the coherency would be consistently equal to one across all scales and times. The phase difference between the two chronicles serves as a complementary indicator that enables us to determine the direction of the relationship, as well as the mutual influences between the variables, with the concept of a Leader (Awada and Mestre, 2023). The phase difference between {X} and {Y} is depicted in Eq. (5): ...
This study examines the complex and time-varying relationship between residential energy demand (including electricity, geothermal, and solar energy) and climate change using wavelet analyses with monthly USA data from January 1990 to March 2023. The results show that residential energy demand and climate change indicators exhibit a time-varying interrelationship with cyclical and lag effects. Specifically, before 2021, a positive correlation between residential electricity demand and carbon dioxide (CO 2) emissions in short-term frequencies was found, but the relationship reversed thereafter, with an increase in CO 2 levels influencing and decreasing residential electricity demand. In the long run frequencies, the link between residential power consumption and CO 2 emissions shifted over time, exhibiting inconsistent co-movement. The co-movements between residential geothermal and CO 2 show predominantly positive correlations, with CO 2 leading the relationship in the short run, while geothermal leads the co-movements in the long run. In both short and long-term frequencies, the dependency and co-movement between residential solar and CO 2 are mixed, with residential solar leading to positive correlations and CO 2 leading to negative correlations. Therefore, improved insulation, energy-efficient windows, and high-efficiency heating systems can all assist in reducing heat loss and the total energy demand for domestic heating and subsequently low CO 2 emissions.
... The inclusion of S is essential because, without it, the coherency would be consistently equal to one across all scales and times. The phase difference between the two chronicles serves as a complementary indicator that enables us to determine the direction of the relationship, as well as the mutual influences between the variables, with the concept of a Leader (Awada and Mestre, 2023). The phase difference between {X} and {Y} is depicted in Eq. (5): ...
This study examines the complex and time-varying relationship between residential energy demand (including electricity, geothermal, and solar energy) and climate change using wavelet analyses with monthly USA data from January 1990 to March 2023. The results show that residential energy demand and climate change indicators exhibit a time-varying interrelationship with cyclical and lag effects. Specifically, before 2021, a positive correlation between residential electricity demand and carbon dioxide (CO 2) emissions in short-term frequencies was found, but the relationship reversed thereafter, with an increase in CO 2 levels influencing and decreasing residential electricity demand. In the long run frequencies, the link between residential power consumption and CO 2 emissions shifted over time, exhibiting inconsistent co-movement. The co-movements between residential geothermal and CO 2 show predominantly positive correlations, with CO 2 leading the relationship in the short run, while geothermal leads the co-movements in the long run. In both short and long-term frequencies, the dependency and co-movement between residential solar and CO 2 are mixed, with residential solar leading to positive correlations and CO 2 leading to negative correlations. Therefore, improved insulation, energy-efficient windows, and high-efficiency heating systems can all assist in reducing heat loss and the total energy demand for domestic heating and subsequently low CO 2 emissions.
... In more developed OECD countries, causality from energy to GDP is more significant than in the less developed countries. Research results that are evidence of this pattern have significant practical implications: Reducing energy consumption will have more effect on GDP in developed countries than in less developed ones [13,14]. ...
As the fourth industrial revolution drives innovation and economic growth, the energy sector is increasingly recognized for its significant economic contribution. This research aims to investigate the relationship between economic growth and renewable and non-renewable energy consumption in nine southeastern European countries using panel estimation techniques and causal inference. This research employs a unique approach to modeling the energy–growth nexus, incorporating interaction terms to better understand the impact of renewable energy on real GDP growth. The findings are a valuable addendum to the current body of research on the effects of renewable energy consumption on economic growth, and the results contribute to narrowing the empirical research gap in the econometrical field of panel data estimation and endogeneity. This study uses the fully modified OLS (FMOLS) technique for heterogeneous panels to estimate coefficients, while the error correction model (ECM) is used to estimate the cointegration vector between energy variables and GDP. The non-causality test by Dumitrescu and Hurlin (2012) evaluates the causation between energy variables and economic output. Empirical findings indicate that both renewable and non-renewable energy consumption positively affect economic growth. The outcomes of this study hold significant policy ramifications in terms of prioritizing reformation and investment towards specific sectors to foster capital infusion into renewable energy and energy efficiency projects and initiatives, consequently advancing sustainable economic growth.
