Does circularity mean environmental sustainability? Novel evidence from European countries.

The objective of this research is to evaluate the effects of green economy initiatives (GEI) on environmental sustainability (ES) through empirical means. The degree of green economy efforts is measured using six different metrics: the percentage of circular material consumption (GEI_MA), municipal trash generation per person (GEI_MW), recycling waste performance (GEI_RW), and recycling and secondary raw materials-related patents (GEI_PA). The latter particularly comprises the biowaste (GEI_RB) and e-waste (GEI_RE) recycling shares. Our analysis, which included information gathered from 19 European nations from 2012 to 2019, shows that GEI_MW significantly improves EPI and ECO. On the other hand, there is no meaningful connection between ecological sustainability and GEI_PA. EPI is strongly positively impacted by GEI_MA and EPI and ECO are positively impacted by GEI_RW. Additionally, GEI_RB has a beneficial impact on EPI, HLT, and ECO, but GEI_RE has a considerable favorable impact on both HLT and ECO. These findings highlight how crucial it is for the government to fund R&D for green economy projects in order to achieve ecological sustainability.

Employment of the DCC-GARCH Copula Model to explore a link between robotics and artificial intelligence and green crypto investments.

The pursuit of the Sustainable Development Goals (SDGs) requires considerable new green crypto investments. To attract the flow of this investment, it is necessary to develop and apply robotic artificial intelligence (AI) as it has the potential to encourage the adoption of environmental innovation and increase individuals' environmental awareness. Our research employs the DCC-GARCH Copula Model to examine time-varying spillovers and prove interlinkages between the development of AI and green cryptocurrencies in the period from January 1, 2018, to September 8, 2023. Comparing the optimum hedge ratios with the optimal portfolio weights, we demonstrate that the optimal hedge strategy for BOTZ is the most successful one. However, the success of hedging depends on the portfolio's risk profile. Based on our analysis of the cumulative profit profile of different approaches, we continue to believe that the best portfolio weighting strategy is the one that produces positive returns in the middle of 2020 and the first part of 2022 and 2023. This demonstrates that the most profitable diversification approach is not always the most successful one. Our results have important policy implications for investors and governments.

Achieving a blue economy through the circular initiatives: a path towards sustainable marine living resources.

This paper empirically examines the role of circularity performance on the performance of marine living resources to prove its role in promoting a sustainable blue economy. We use five different metrics to quantify the marine living resources of nations in the European regions, including the value added at the factor costs of small-scale capture fisheries, shellfish aquaculture, freshwater aquaculture, marine aquaculture, and large-scale capture fisheries. By using various econometric techniques, we provide evidence of the importance of circularity performance in improving the sustainability of the blue economy in the European region during the 2009-2020 period. However, it is more likely that this effect is only positive in the long term. In the long run, circularity performance affects many marine living resource components in a statistically meaningful way.

A wavelet analysis of dynamic connectedness between geopolitical risk and renewable energy volatility during the COVID-19 pandemic and Ukraine-Russia conflicts.

The study explores inter-relations between the geopolitical risk index and renewable energy volatility index at frequency dimensions from April 4, 2019, to June 13, 2022, using novel multivariate wavelet analysis approaches, such as partial wavelet coherency and partial wavelet gain. Our method allows us to study these interlinkages at various time frequencies. We also consider the influences of uncertain events like the COVID-19 pandemic and Ukraine-Russia conflicts on their interconnectedness. The multiple coherencies between the geopolitical risk index and the green energy sector suggest four cycles in the low-frequency range (50-130 days) from March 2020 to October 2021 and from February 2022 to June 2022. The partial coherency between the geopolitical risk index and renewable energy volatility index suggests connectedness between renewable energy dynamics and geopolitical risks during the COVID-19 duration and the Russia-Ukraine conflict. The partial wavelet coherency of the volatility of green bonds and geopolitical risks suggests that alterations in green bonds caused alterations in geopolitical risks, and the association is negative from February 2021 to April 2021. Both indicators are in-phase with geopolitical risks pushing from February 2020 to April 2020 and from October 2021 to the end of the sample. The partial coherence between clean energy and geopolitical risk suggests geopolitical risks pushing anti-phase connectedness from September 2020 to September 2022. Our findings help policymakers design the most effective policies to lessen the vulnerabilities of these indicators and reduce the spread of risk or uncertainty across them by having insightful knowledge about the primary antecedents of the contagions among these indicators.

An investigation of the nexus between green innovation and environmental sustainability in Vietnam: new evidence from the wavelet analysis.

The research investigates the interactions between ecological sustainability and green technologies in Vietnam at different time and frequency dimensions from 1992 to 2019. This study investigates these correlations and their frequency domains by employing innovative multivariate wavelet analysis techniques. The multiple coherencies between green technologies and ecological sustainability suggest one cycle was placed at low frequencies (periodicity of approximately 5-14 years) and spanned from 1996 to 1998. Two significant coexisted cycles at low frequencies were from 2001 to 2004 and 2001 to 2009. The three additional cycles were situated at high frequencies (periodicity of approximately 1-5 years). These cycles ran from 2004 to 2006, 2014 to 2016, and another cycle from 2017 to 2019. The partial wavelet coherency of green technology growth and CO2 emissions suggests that green technology causes alterations in CO2 emissions, and the association is negative from 1996 to 2003 and from 2012 and 2015; both indications are in sync. CO2 emissions pushed from 2004 to 2010, and CO2 emissions pushed anti-phase connectedness from 2016 to 2019. The inconsistency between green technologies and renewable energy use shows that changes in renewable energy consumption are caused by green technology. The relationship is negative from 1996 to 2003, while renewable energy utilization is in step with green technologies pushing from 2011 to 2019. Novel findings in Vietnam in this paper is vital for policymakers to design policies to promote the use of green technologies toward environmental sustainability.

Welfare influences of green energy volatility in Vietnam: new evidence from an extended TVP-VAR approach.

We present a study utilizing TVP-VAR - a time-varying parameter vector autoregression combined with an extended joint connectedness approach to examine the interrelationships between welfare and green energy volatility in the system of variables, including economic growth measured by gross domestic product (GDP), rural income, urban income, and renewable energy consumption. We characterize the connectedness of these variables from 19954 to 2019 in Vietnam. Net total directional connectedness of renewable energy consumption and GDP, rural-urban income suggests that both GDP and rural income have constantly been recipients of net contagion shocks, and urban income is a net critical receiver in the period 2001-2010. Renewable energy consumption consistently behaves as an important transmitter of shocks. Pairwise connectedness reveals that renewable energy consumption demonstrates a consistent shock-transmitting behavior for other variables. Renewable energy consumption could be either a transmitter or a receiver of shock from GDP, depending on the period. Our findings are critical since they will help policymakers formulate appropriate policies for reducing the vulnerabilities of these variables and minimizing the spread of risk and uncertainty among them, then improving the individuals' welfare and obtaining ecological sustainability in the case of developing countries.

Scrutinizing the nexus between green innovations and the sustainability of environmental system: novel insights from European database.

A study is presented in this paper that examines the effect of environmental innovation (EI) on environmental performance (EP). Six measures are used to reflect environmental innovation, including the percentage of enterprises that invest in environmental innovation, the percentage of enterprises implementing environmental innovation activities, the number of ISO 14001 certificates, patents related to environmental innovation, the total R&D personnel and researchers, and the amount of green early-stage investments. The estimation results show that EI positively impacts EP in 21 European countries using different econometric techniques during the 2011-2019 period. By using various econometric techniques (namely a panel-corrected standard errors (PCSE) model, a feasible generalized least square estimates (FGLS) model, and the two-step general method of moment (the two-step GMM), our research demonstrates how environmental innovation impacts on environmental quality. The short- and long-term effects of autoregressive distributed lag (ARDL) methods were also investigated using pooled mean groups (PMGs) to distinguish the short-run and long-run influences of EI. The relationship between EI and EP is explored by demonstrating how EI affects EP short- and long-term and comparing its influence on EP across many component measures of EI: air quality, sanitation, drinking water, heavy metals, waste management, biodiversity, habitat, ecosystem services, water resources, and agriculture. Notably, we find that the influences of EI become more pronounced in a country characterized by a well-developed institutional system. Our findings suggest policy implications to help countries invest in research and development with concerns about environmental damage mitigations more effectively. These findings are critical to suggest a way to help countries pursue ecological sustainability.

Do the climate-related financial policies promote green innovation? Insights from global sample.

This paper is an attempt to empirically examine the influences of climate-related financial policies (CRFP) on green innovation (GI). By applying diverse econometric techniques, namely a panel-corrected standard error model (PCSE), feasible generalized least square (FGLS), and two-step general method of moment (the two-step GMMs), to a global sample of 23 European countries in the period from 2012 to 2019, the estimation results demonstrate that the CRFP has a favorable impact and is statistically significant on all four aspects of green innovation implementation. We find robust results by utilizing various econometric techniques and adding more explanatory variables. To shed light on the relationship between CRFP and GI, we demonstrate the short-run and long-run effects of CRFP on GI. The results suggest that climate-related financial policies only significantly negatively affect investments in environmental activities in the short run. Notably, our findings imply that climate-related financial policies are more likely to have long-term impacts than short-term ones. Our findings are critical to suggest policy implications to employ climate policies more effectively to promote the use of green innovation.

Fat tails, serial dependence, and interlinkages of the geopolitical risk and food market during the COVID-19 pandemic and war crisis: an application of Bayesian vector heterogeneous autoregressions.

We investigate fat tails and network interconnections of geopolitical risk index and food prices, including the price of corn, rice, and wheat, using seven Bayesian vector heterogeneous autoregression fashions. This paper differentiates dynamically between network interlinkages between these variables during the short, medium, and long runs. We found some noteworthy results in our study. In the first place, network interlinkages exhibit remarkable differences over time. Interlinkages between variables in our designed networks are increased in the short, medium, and long term due to transient events occurring in markets during the studied period. During the Russia-Ukraine conflict, the long-term ties within the system are more significantly impacted. Additionally, based on net-directional linkages, each market's role shifts (from sending to receiving shock and vice versa) during the pre- and post-Ukraine-Russia conflict, whereas these roles persist during the COVID-19 pandemic. Observations of short- and medium-term trends reveal that the geopolitical risk index is shock receivers transmitted to these markets by the rice and corn markets. The results indicate that the geopolitical risk index persists as shock receivers in terms of long-horizon measures.

Dynamic interrelations between environmental innovations, human capital, and energy security in Vietnam: new evidence from an extended TVP-VAR approach.

This study employs an extended joint connectedness approach, as well as a time-varying parameter vector autoregression technique (ETVP-VAR), to characterize the interrelationships among six factors, namely, renewable energy, environmental innovations (EI), gross domestic product (GDP), human capital, energy consumption, and energy productivity (EP), from 1995 to 2019 in Vietnam. Taking a holistic view, it appears that both energy consumption and GDP are net recipients of contagion shocks. In addition, renewable energy, as well as environmental innovations, is critical net transmitters during our studied period. From 1995 to 2003, human capital constantly acted as a crucial net shock absorber before switching to a crucial net transmitter after that year. With a significant exception around 1997, this variable is mostly a shock transmitter when it comes to energy production. Pairwise connectedness reveals that renewable energy consistently appears as a shock transmitter to GDP, human capital, energy consumption, and energy productivity. That being said, environmental innovations consistently contribute to renewable and green energy volatility by transmitting shocks from other markets.

Dynamic connectedness between FinTech innovation and energy volatility during the war in time of pandemic.

We use an extended joint connectedness technique and the time-varying parameter vector autoregression (ETVP-VAR) method to examine connections between the ARK FinTech Innovation ETF (ARKF), Global X FinTech ETF (FINX), and energy volatility by connectedness as a quality of eight indicators from April 1, 2019, to September 26, 2022. Our results demonstrate that the pattern of ARKF and FINX is picked up as a crucial net shock transmitter that nearly permeates our analyzed sample. Since the COVID-19 epidemic, more people are adopting FinTech partly because of their concern about the disease spreading through social contact and cash handling. Moreover, green bonds are net shock recipients over the long term. Furthermore, during the COVID-19 duration and the Russo-Ukrainian War, shocks transmitted to green bonds soared sharply. By contrast, keeping with the clean energy and crude oil trend, these indicators transmit a network of shocks during the period under study. When considering wind power, it becomes clear that this signal first acts as a net shock transmitter before changing into a net receiver of shocks from mid-2021 onwards. We recognize that the system is a net shock receiver regarding clean power. The dynamics invariably lead the series to change to a net shock transmitter in mid-2021. By mid-2021, the developments always cause the series to transform into a net shock transmitter.

An application of QVAR dynamic connectedness between geopolitical risk and renewable energy volatility during the COVID-19 pandemic and Russia-Ukraine conflicts.

The article is the first to employ a quantile vector autoregression (QVAR) to identify the connectedness between geopolitical risks and energy volatility from January 1, 2015, to April 03, 2023. This paper is also the first to examine the mediating roles of uncertain events like the COVID-19 pandemic and the Russia-Ukraine conflict on this interlinkage. Dynamic connectedness is 29% in the short term and approximately 6% in the long term. Dynamic net total directional connectedness over a quantile also indicates that connectedness is very intense for both highly positive changes (above the 80% quantile) and negative changes (below the 20% quantile). In the short term, the geopolitical risks remained net receivers of shock, but they turned into net shock transmitters during 2020 in the long term. Clean energy, in the short term, transmits shocks to other markets, and it plays the same role in the long term. Crude oil was a net receiver of shocks during COVID-19 and turned into a net transmitter of shocks in early 2022. Dynamic net pairwise directional connectedness over a quantile suggests that uncertain events like the COVID-19 epidemic or the Russia-Ukraine conflict influence the dynamic interlinkages between geopolitical risks and renewable energy volatility and change their roles in the designed system. These findings are critical since they help authorities develop effective policies to lessen the vulnerabilities of these indicators and minimize how widely the renewable and non-renewable energy market is exposed to risk or uncertainty.

Dynamic connectedness between green energy and carbon risk during Russia-Ukraine conflict: new evidence from a wavelet analysis.

The study explores the inter-relations between green and renewable energy and carbon risk. Key market participants with varying time horizons include traders, authorities, and other financial entities. This research examines these relationships and frequency dimensions from February 7, 2017, to June 13, 2022, using novel multivariate wavelet analysis approaches, such as partial wavelet coherency and partial wavelet gain. The multiple coherencies between green bond, clean energy, and carbon emission futures imply that these regions were situated at low frequencies (relating to approximately 124-day frequency) and run from the beginning of 2017 to the beginning of 2018, in the first half of 2020, and from the beginning of 2022 to the end of the sample. The relationship between the solar energy index, envitec biogas, biofuels, geothermal energy, and carbon emission futures, is significant in the low-frequency band starting from early 2020 to middle 2022 and in the high-frequency band starting from early 2022 to middle 2022. Our research demonstrates the partial coherencies between these indicators during the Russia-Ukraine conflict. The partial coherency between the S&P green bond index and carbon risk suggests that carbon risk pushes anti-phase connectedness. The partial phase difference S&P global clean energy index and carbon emission futures (from early April 2022 to the end of April 2022) recommend that indicators are in-phase with carbon risk pushing and the phase (from early May 2022 to middle June 2022), suggesting that carbon emission futures are in-phase with S&P global clean energy index pushing.

Scrutinizing interlinkages between digitalization, economic complexity, green technologies, green energy consumption and CO2 emission by quantile spillovers in Vietnam.

We use quantile vector autoregression (QVAR) to identify the connection between six variables related to digitalization (proxied by a number of Internet users and mobile cellular subscriptions), green technology development, green energy consumption, carbon dioxide emissions, and economic complexity index from 1996 to 2019 in Vietnam. The dynamic connectedness of the system is 62% and 14% in the short and long term, respectively. Their connectedness is intense for highly positive and negative quantiles (over 80% quantile). In contrast, economic complexity transmits shocks in the short term and manifests itself even more in the long term. Green technology development is the central receiver of short- and long-term shocks. Besides, digitalization captured by a number of Internet users has switched from shock transmitters to shock receivers in the short term. Other metrics like mobile cellular subscriptions, green energy consumption, and CO2 emissions are mainly shock-receiver-driven. In the short term, there was volatility, especially from 2009 to 2013, due to unprecedented events like destructive changes in political, economic, and financial issues in the globe. Our findings are critical for economists and policymakers in promoting a country's digitalization, green technology performance, and green energy on the path toward sustainable development.

An application of Bayesian vector heterogeneous autoregressions to study network interlinkages of the crude oil and gold, stock, and cryptocurrency markets during the COVID-19 outbreak.

We investigate fat tails and network interconnections of crude oil, gold, stock, and cryptocurrency using seven Bayesian vector heterogeneous autoregression fashions. In this paper, we incorporate parameter uncertainty by using Bayesian VAR models for estimation. To make rational investment decisions, we decompose a network of financial assets and commodity prices into various time horizons to obtain essential insight and knowledge. During the short, medium, and long run, this paper differentiates dynamically between network interlinkages between these markets. We found some noteworthy results in our study. In the first place, network interlinkages exhibit remarkable differences over time. Interlinkages between networks are increased in the short term, medium term, and long term due to transient events occurring in markets during the study period. As a result of the ongoing COVID-19 epidemic, the long-term ties within the system are significantly impacted. Additionally, based on net directional linkages, each market's role shifts (from sending to receiving shock and vice versa) before the pre-COVID-19 pandemic course, whereas they remain persistent during COVID-19. Observations of short- and medium-term trends reveal that three markets, namely, crude oil, gold, and stock, receive shocks, which are transmitted to these markets by the cryptocurrency market. In terms of long-horizon measures, the results indicate that the gold and cryptocurrency markets persist as shock transmitters. Our findings are critical since policymakers can also design appropriate policies to reduce the vulnerabilities of such markets and prevent risk spread and instability.

What are the impacts of economic complexity and product proximity on nations' circularity? An empirical approach using statistical analysis.

The topic of whether economic complexity or close proximity to a product produces favorable conditions to aid nations in transitioning to the circular economy is addressed in this article. Six distinct indicators are used to assess the performance of circularity. The amount of municipal garbage, the amount of circular materials utilized, the number of circularity patents, the rate of recycling waste, the rate of recycling biowaste, and the rate of recycling electronic waste are some examples of these metrics. By using various econometric techniques (namely, a panel-corrected standard error (PCSE) model, a feasible generalized least square estimate (FGLS) model, and the two-step general method of moment (the two-step GMM), our research demonstrates how economic complexity and close proximity to a product have varied nonlinear impacts on circularity. We do, however, offer empirical proof that, particularly over the long term, a country's closeness to its products may significantly improve its performance in terms of circularity. Although economic complexity is a crucial enabler of circularity, it may also become too complicated, which could impede the process.

Decomposed and partial connectedness between economic globalization, non-renewable and renewable energy consumption in Vietnam.

In this study, we use a time-varying parameter vector autoregression (TVP-VAR) in conjunction with the extended joint connectedness approach to examine the influences of the economic globalization measured by foreign direct investment (FDI) as well as trade openness (TO), on renewable and non-renewable energy consumption, by characterizing the connectedness of these variables, from 1987 to 2020 in Vietnam. Our results demonstrate that abolishing the state monopoly in foreign trade influences the system-wide dynamic connectedness of trade openness, which peaked in 1989. Net total directional connectedness of FDI and energy consumption suggests that both the consumption of renewable and non-renewable energy consistently act as net contagion shock receivers, and FDI is a critical net transmitter the whole time. Trade openness behaves consistently as a critical net shock transmitter in 1989 but turned into an essential net receiver from 1990 to 2020. In a system with trade openness, the consumption of non-renewable energy consistently acts as a net contagion shock receiver, and renewable energy consumption is a critical net transmitter in the whole sample. Pairwise connectedness reveals that FDI consistently appears as a shock transmitter to renewable and non-renewable energy consumption. Trade openness could be either a transmitter or a receiver of shock from non-renewable energy, depending on the period, and is a net receiver of shocks from renewable energy consumption during our sample. The findings of this paper are critical for Vietnam's government to make a greater contribution to the expansion of global commerce and a sustainable environment.

Is environmental tax an enabler of circularity: new insights from the unique database.

This paper provides answers to the question that the environmental tax enables the circular economy. By employing six diverse measures to reflect circularity (namely the amount of municipal waste, the number of circularity patents, the amount of circular material used, the rate of recycling waste, the rate of recycling biowaste, and the rate of recycling e-waste) and four measures of environmental tax (namely total environmental tax revenue, energy tax revenue, pollution and resource tax revenue, and transportation tax revenue) of European countries, our article provided a comprehensive analysis of the nexus between environmental tax and circularity performance. A panel-corrected standard errors (PCSE) model and a feasible generalized least square estimates (FGLS) model are employed to study this association, while the dynamic fixed effects (DFE) estimator is applied to the autoregressive distributed lag (ARDL) method to measure both the short-run and long-run effects. Our study reveals the heterogeneous effects of an environmental tax on circularity. Taxing on the energy sector, the polluted sector, and transportation stimulate the process of circularity. Notably, our estimation results reveal that environmental tax can enable European countries to transit to a circular economy, especially in the long term. Our findings are critical for economists and policymakers in using the tax as an effective tool to promote a country's circularity performance.

The role of financialization in stimulating environmental innovation implementation in the European region.

This paper empirically examines the influences of financial development on environmental innovation implementation. Our research is based on four measures designed to assess the effectiveness of environmental innovations in 24 European countries, including the percentage of enterprises implementing environmental innovation investment (% of surveyed firms); the percentage of enterprises implementing environmental innovation activities (e.g., implementation of resource efficiency actions, sustainable products, or ISO 14001 certificates) measured, a number of enterprises having new ISO 14001 registration and a number of environmental innovation-related patents. Based on our analysis and estimates, we reveal that the better quality of the financial system improved the environmental innovation performance in the European region during the 2011-2019 period. To shed light on the link between financialization and environmental innovations, we dig deeper into financial markets and financial institutions' depth, access, and efficiency. Our results highlight financial institutions and financial markets' depth and efficiency in enhancing EI activities. However, EI-related patents do not show any significant improvements under the changes in the financial system.

Dynamic interlinkages between the crude oil and gold and stock during Russia-Ukraine War: evidence from an extended TVP-VAR analysis.

The Russia-Ukraine significantly influences the oil market. We employ a time-varying parameter vector autoregression (TVP-VAR) in combination with an extended joint connectedness approach to identify the sources of the oil market's volatility by studying interlinkages between the crude oil and gold and stock market by characterizing the connectedness of four markets starting from January 1, 2018 to April 8, 2022. Our attention is mostly paid to the period marked by the event that Russia invaded Ukraine on 24 February, 2022. Our results demonstrate that the war shocks appear to influence the system-wide dynamic connectedness, which signifies the interlinkages among the considered markets. Net total directional connectedness suggests that the oil and gold markets appear to be the net transmitter of spillover shocks in the system. However, there are shifts in the roles of these two markets during the time of the Russia-Ukraine war shock. Pairwise connectedness highlights the significance of the oil market in transmitting the adverse influences of shocks to other markets, especially during the Russia-Ukraine war.