Role of alternative and nuclear energy in stimulating environmental sustainability: impact of government expenditures

The impact of Chinese investment on access to clean and sustainable energy in Africa

The objective of this study is to examine the relationship between Chinese investment and access to clean and sustainable energy in African countries. We are motivated by the increasing engagement between China and Africa and the priority of sustainable energy for both partners. We employ robust econometric modelling, including fixed effects and the two-step Generalized Method of Moments, on a panel sample of 43 African countries over 19 years. The results show that Chinese energy investment in Africa is significantly associated with increased access to sustainable electricity. This effect is more pronounced in resource-rich countries, suggesting that China is more attracted to these countries due to the opportunities for resource trade in the form of partnerships. The policy implication of this finding is that it highlights the importance of African governments developing favourable strategies and policies to attract more Chinese investments in the energy sector.

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.

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.

Assessing the environmental sustainability gap in G20 economies: The roles of economic growth, energy mix, foreign direct investment, and population

There is serious debate among researchers regarding the sustainability implications of economic prosperity and energy dependence. Energy consumption has a critical linkage with economic growth, but it also degrades environmental quality. Therefore, it is important to investigate the relationship between economic growth, the energy mix, and environmental sustainability. However, empirical literature utilizes narrow variables to capture environmental sustainability. Because of this, this research introduces a new environmental sustainability variable using entropy weighting and combining deforestation, household carbon emissions, and life expectancy. This study examines the relationship between environmental sustainability, economic growth, and other selected variables using data from 2002 to 2019 for the G20 and its high-, upper-, and low-middle-income member countries. Since shocks in one G20 country can affect another, this study uses the Augmented Mean Group (AMG) technique for empirical analysis. The results of this study indicate that Gross Domestic Product (EG) and its square term did not support the Environmental Kuznets Curve (EKC) theory. The energy mix has a positive impact on the environmental sustainability gap across all the samples except for the upper-middle-income group. Foreign direct investment positively affects this gap, while population growth has no significant impact. These findings demonstrate that policymakers should support environmentally friendly and clean energy sources to foster long-term economic growth and sustainability.

Evaluation of food waste treatment techniques using the complex q-rung orthopair fuzzy generalized TODIM method with weighted power geometric operator

Food waste has received wide attention due to its hazardous environmental effects, such as soil, water, and air pollution. Evaluating food waste treatment techniques is imperative to realize environmental sustainability. This study proposes an integrated framework, the complex q-rung orthopair fuzzy-generalized TODIM (an acronym in Portuguese for interactive and multi-criteria decision-making) method with weighted power geometric operator, to assess the appropriate technique for food waste. The assessment of food waste treatment techniques can be divided into three phases: information processing, information fusion, and ranking alternatives. Firstly, the complex q-rung orthopair fuzzy set flexibly describes the information with periodic characteristics in the processing process with various parameters q. Then, the weighted power geometric operator is employed to calculate the weight of the expert and form the group evaluation matrix, in which the weight of each input rating depends upon the other input ratings. It can simulate the mutual support, multiplicative preferences, and interrelationship of experts. Next, the generalized TODIM method is employed to rank the food waste treatment techniques, considering experts' psychological characteristics and bounded behavior. Subsequently, a real-world application case examines the practicability of the proposed framework. Furthermore, the sensitivity analysis verifies the validity and stability of the presented framework. The comparative study highlights the effectiveness of this framework using the existing frameworks. According to the result, Anaerobic digestion (0.0043) has the highest priority among the considered alternatives, while Incineration (-0.0009) has the lowest.

From industrialization to dehumanization: understanding the deriving forces of environment and implications for sustainable development

Environment has detrimental effects on economic activity and human survival. Climate change is increasingly conducive to natural disasters, epidemics, social conflicts, food security, financial shocks, economic hardships, and life subsistence. In pursuit of this issue, this study empirically investigates the effects in outcome variable CO2 provoked by independent variables governance, technological innovation, renewable energy, economic growth, and economic policy uncertainty in APEC economies. The APEC region accounts for 60% of global emissions, 62% of world GDP, 48% of global trade and contribute 8.7% renewable energy annually. A dynamic panel PMG-ARDL model is applied under the assumption of maximum likelihood estimation with DH causality and CS-ARDL for the period of 1996-2020. Our empirical results confirm that governance, technology innovation, and transitional energy have significant and positive effect to mitigate CO2 emissions. The region needs to design policy mechanisms supportive to promote institutional quality, enhances transparency, ensure political stability and rule of law. It develops the infrastructure that ensures the adaptation of technology innovations, promotes green growth, improves energy efficiency, and implements carbon pricing mechanism. Economic policy uncertainty has insignificant and positive effects on environmental degradation. The findings show that governance, technological development, and transitional energy have an essential role to mitigate CO2 emissions and achieve sustainable development. Moreover, this study will be helpful in understanding the implications of SDGs and achieving specific targets such as (SDG-7: Clean energy sources) and (SDG-8: Sustainable development goal) based on the largest set of emitters APEC.

Understanding the Role of Technology in Asian Economies: The Environmental Impact of Remittances and Economic Complexity

In recent years, scholars have determined various determinants of environmental degradation using the panel and time-series studies. However, technological innovations (TI) and remittances, among the financial system's essential components, are relatively ignored. In addition, nations' economic progress and environmental performance also depend upon the nature of their economic structure. This empirical research investigates the effects of TI, remittances and economic complexity (EC) on CO2 controlling economic growth and trade openness (TR) in the selected 15 Asian nations. The study collected panel data of 15 Asian countries from 1990 to 2019 and employed the panel quantile regression and augmented mean group methods to unveil the impacts of variables on CO2 emissions. The empirical findings established that remittances are negatively linked with CO2 emissions. Similarly, EC reduces CO2 emissions in the context of Asian countries. In addition, EC and remittances Granger cause CO2 emissions. These findings indicate that remittances and EC positively contribute to environmental quality in Asian countries. Conversely, TI, economic growth, and TR intensify CO2 emissions in Asian countries. Finally, the study recommended policies to enhance remittances and EC in Asian countries to curb environmental degradation.

Enhancing industrial environmental performance: interplay among environmental sustainability, green HRM, and green competitive advantage

This study highlights the importance of green human resource management (HRM) practices, which investigates the connection between environmental sustainability and green competitive advantage. Using the CGM model and the generalized method of moments (GMM), this research investigates how green HRM may foster environmental sustainability by creating a competitive advantage for businesses. Research shows that green HRM may achieve green competitive advantage practices, crucial for environmental sustainability. By "green HRM practices," we mean incorporating environmental concerns into traditional HRM processes, including hiring, training, evaluating, and compensating employees. However, the importance of green HRM practices cannot be overstated due to their efficiency in creating a competitive advantage and advancing environmental sustainability. Specifically, the research shows that businesses that have adopted "green HRM practices" outperform their competitors in terms of environmental sustainability. The last section emphasizes the importance of green HRM as a key facilitator of environmental sustainability. Implications for businesses that want to improve their environmental performance are also provided.

The impact of energy efficiency in reducing environmental degradation: does renewable energy and forest resources matter?

The vast utilisation of energy sources in promoting economic growth has been identified as the major cause of environmental degradation (through carbon emission). Therefore, the efficient utilisation of energy ensuring the minimisation of any wastages is vital in reducing environmental degradation. The current research aims to investigate the importance of energy efficiency, forest resources, and renewable energy in reducing environmental degradation. The major novelty of the research is that it seeks to investigate the impact of forest resources and energy efficiency on carbon emissions. Literature shows that there is still a dearth on the association of forest resources and energy efficiency, with carbon emissions. We employ data of the European Union countries for the time frame ranging from 1990 to 2020. The CS-ARDL technique depicts that raising GDP by 1% raises carbon emissions by 5.62% in the short run and 2.93% in the long run, raising renewable energy by 1 unit reduces carbon emissions by 0.098 and 0.03 units in the short and long run, respectively, whilst raising energy efficiency by 1% reduces carbon emissions by 6.29% and 3.29% in the short and long run, respectively. The Fixed Effect and Random Effect tools support the outcomes of the CS-ARDL tool on the negative effect of renewable energy and energy efficiency, and the positive effect of GDP on carbon emissions, and also depict that raising non-renewable energy by a single unit raises carbon emissions by 0.07 and 0.08 units, respectively. Forest resources, in this present research, do not significantly impact the emissions of carbon amongst the European nations.

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.

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 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.

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.

The moderating effect of liquidity on the relationship between sustainability and firms' specifics: Empirical evidence from indian manufacturing sector

The current study attempts to examine the moderating effect of liquidity on the relationship between firms' specific and sustainability expenses. The study is based on secondary data over a period from 2015 to 2021. The results are estimated using panel data with fixed-effect models. The results indicate that liquidity enhances and strengthens the ability of a company to spend more on environmental, social, and employee compensation sustainability expenses. In the same context, the results reveal that there is an insignificant moderation effect of liquidity with the financial performance of a company, indicating that the liquidity of companies with higher financial performance does not enhance and strength their ability to spend more on sustainability expenses. Further, the extent of liquidity in larger companies affects positively and significantly the level of employee compensation but not environmental and social spending. Finally, the findings show that greater leverage with less liquidity negatively affects the levels of sustainability spending. This study provides a unique contribution to the existing literature by introducing the moderating effect of liquidity on the relationship between firms' specific and sustainability expenditures. It highlights the direct effect of firms' specific determinants and the moderating effect of liquidity on three categories of sustainability expenses which are environmental expenses, social expenses, and employee compensations. Therefore, this research has valuable implications for company managers, financial analysts, policymakers, and other stakeholders.

Estimation of ecological footprint based on tourism development indicators using neural networks and multivariate regression

The ecological footprint has attracted a lot of attention in the top tourism destination countries, and this issue may be worrying. This study aims to estimate the ecological footprint, using such indicators as economic growth, natural resources, human capital, and the number of tourists in top tourism destination countries. For this purpose, artificial neural network models and multivariate regression were used for a period of 24 years (1995-2019). The results of the study showed a significant positive correlation between economic growth and ecological footprint. Multivariate regression estimation (R = 0.75) is weaker than neural network models (R = 96.3). Regarding predicting the ecological footprint, neural network models have better performance in comparison with the multivariate regression statistical methods. Accordingly, one can say that for planning ecological footprint, deeper look at neural networks can be more effective in predicting top tourism destination countries.

The role of economic growth, information technologies, and globalization in achieving environmental quality: a novel framework for selected Asian countries

This study examines the impact of information and communication technologies (ICT), GDP growth, population, and globalization on the environmental quality of 31 Asian economies (i.e., categorized as lower middle-income, upper middle-income, and high-income groups Asian economies). This analysis employed the time series data from 1990 to 2018. The robust second-generation econometric technologies are used in this analysis. This study applied the Environmental Kuznets curve (EKC) premises under the extended "STIRPAT model" to add population and GDP (per capita) and information technologies (ICTs) by employing ecological footprint. To estimate, the estimators of this study used the CS-ARDL estimates, and for robustness check, this study used the augmented mean group (AMG) test. The co-integration test found the long-run association between ecological footprint and its main determinants. The results of CS-ARDL have confirmed the imperative role of information technologies in mitigating the ecological footprint in the higher, upper-middle, and lower-middle-income economies of Asian economies. The statistical findings of this study are robust to diagnostic tests and alternative estimation proxies and techniques. Moreover, policymakers need to identify the direction of the information technology-ecological footprint nexus through cooperation in combating climate change with financial assistance in the ICT sector.

Most industrialised countries have peaked carbon dioxide emissions during economic crises through strengthened structural change

As the climate targets tighten and countries are impacted by several crises, understanding how and under which conditions carbon dioxide emissions peak and start declining is gaining importance. We assess the timing of emissions peaks in all major emitters (1965-2019) and the extent to which past economic crises have impacted structural drivers of emissions contributing to emission peaks. We show that in 26 of 28 countries that have peaked emissions, the peak occurred just before or during a recession through the combined effect of lower economic growth (1.5 median percentage points per year) and decreasing energy and/or carbon intensity (0.7) during and after the crisis. In peak-and-decline countries, crises have typically magnified pre-existing improvements in structural change. In non-peaking countries, economic growth was less affected, and structural change effects were weaker or increased emissions. Crises do not automatically trigger peaks but may strengthen ongoing decarbonisation trends through several mechanisms.

Energy transition determinants in the European Union: threshold effects

The World Economic Forum (2018) has introduced a comprehensive proxy for the Energy Transition Index (ETI), which includes two main sub-indices; the energy System Performance Index (SPI) and Transition Readiness (TRI). The first sub-index measures the current state of the energy system, and the latter indicates future transition(s). Any factor that can move these two levers in a positive direction will eventually lead to improved energy transitions. Various factors affect the energy transition. Since the ETI is a comprehensive index that includes socio-economic, governance structures, and political dimensions of the energy transition, it is expected to be impacted by globalization and economic complexity. The present study seeks to answer whether the impact of globalization and economic complexity on both energy transition sub-indicators is in the same direction. Also, do the effects of these two variables vary at different levels of energy transition and its sub-indices? For this purpose, we implement a fixed-effect panel threshold model for data from the European Union. The results demonstrate that (overall) globalization significantly influences the ETI and its sub-indices at all levels. The economic complexity in all three regimes reduces TRI (at 90% or 95% confidence intervals). Nevertheless, it harms the SPI and ETI if they exceed the threshold.

Income inequality, carbon emissions, and green development efficiency

Income inequality affects not only social well-being, health, and carbon emissions but also the strategy for green development in China. Based on the panel data of 205 cities in China from 2010 to 2020, a panel model with partial linear functional coefficient is used to analyze and test the relationship between income inequality, carbon emissions, and green development efficiency under different regional economic development levels. The empirical results show that the impact of income inequality on carbon emissions and green development efficiency is significant. The worsening of income inequality could aggravate carbon emissions, but the effect of income inequality on carbon emissions shows an increase-decrease-flattening with the continuous improvement of regional economic development. In terms of affecting the green development efficiency, the effect of income inequality on the efficiency of green development presents an inverted U shape. However, the number of cities where income inequality has an inhibitory effect on carbon emissions and green development efficiency has increased over time, and the impact of income inequality in a few cities on green development efficiency is not significant. These findings provide new insights into the understanding of shared prosperity and the strategy of carbon peaking and carbon neutralization in China.

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.

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.

Alternative energy and natural resources in determining environmental sustainability: a look at the role of government final consumption expenditures in France

The global community is concerned about several environmental changes. Climate change, desertification, destruction of tropical rainforests, erosion of coastal ecosystems, soil resource loss, overfishing, species extinction, and loss of biodiversity are all contributing factors. Many commentators contend that these issues make up a cumulative, sustained human impact on the environment that has profoundly changed the surface of the Earth. We explore the effects of alternative energy sources, natural resources, and government consumption expenditures on French environmental sustainability from 1990 through 2018 under the environmental Kuznets curve (EKC) framework. We apply advanced econometric methodologies for empirical analysis. Our long-run estimates indicate that alternative and nuclear energy, natural resources, and government final consumption expenditures are negatively associated with CO₂ emissions, while economic growth is positively related to CO₂ emissions. CO₂ emissions are negatively correlated with the square root of economic growth (EKC), thereby supporting EKC. As economic growth increases, environmental sustainability deteriorates. Eventually, EKC will make a positive contribution to environmental improvement. Future research directions, research limitations, and policy implications are discussed.

Does income inequality increase the ecological footprint in the US: evidence from FARDL test?

In recent years, there has been a great interest in identifying determinants of environmental degradation. Although the effects of many economic, social, and political factors on the environment have been studied, the evidence of the relationship between income distribution and the environment is still quite scant. Looking at previous studies, the effect of income distribution on carbon emissions has generally been examined. In the last two years, a new line of research has emerged that investigates the links between income distribution and ecological footprint. Therefore, we investigate the effect of income inequality on the ecological footprint also considering its components. In this study, Fourier ARDL and Fourier ADL (new econometric techniques) are utilized to determine the ecological footprint-income inequality nexus in the US covering the period 1965-2017. We included economic growth and energy consumption as explanatory variables in the model. In this context, the study is a pioneering study examining the impact of income inequality on the ecological footprint as an environmental indicator in the US. The empirical results of Fourier ARDL and Fourier ADL denote that income inequality, economic growth, energy consumption, ecological footprint, and its components (cropland, fishing ground, and carbon) are cointegrated. Besides, it is found that income inequality has a positive effect on ecological footprint and cropland. Results denoted that economic growth and energy consumption have a positive and significant effect on ecological footprint and cropland, fishing ground, and carbon footprint components.

Nexus between environmental disclosures and top management team characteristics: a systematic review

Voluntary nature of sustainability disclosures in most of the countries shifts focus of academicians towards discretion of top executives as a major determining force for firms to make their operations environmentally and socially sustainable. Based on two decade literature on the topic available at Scopus database this study aims to present a comprehensive knowledge map of intellectual structure on the relationship of top management characteristics on sustainability spending and disclosures. A bibliometric systematic review of 164 articles from 2002 to 2022 has been conducted with the help of VOSviewer and identified most influential journals, articles, and the countries whose corresponding authors have contributed in the field and influential research clusters in the literature. These research clusters are first, red cluster with 94 articles has discussed the upper echelon's personal and professional characteristics in relation to sustainability disclosures. Second, green cluster with 60 articles has discussed particularly the gender diversity in top executives and board of directors in relationship with sustainability disclosures. Third, blue cluster with 10 articles has elaborated the influence of independent directors on sustainability disclosures of corporate sector. The findings of this study will particularly help the regulators to make regulations regarding critical mass of female on boards and top management, family-owned firms, and politically connected directors. Moreover it will also help consultants, analysts, and investment bankers to differentiate firms with pressure-resistant and pressure-sensitive institutional investors. From this review shareholders can be very much clear in the selection of their representatives and ultimately the appointment of top management team. This study also provides an insight for future direction so that unexplored dimension of this field may further be discovered by upcoming researchers.

Green effects of research and development on industrial waste reduction during the production phase: Evidence from China and policy implications

Maintaining public health requires a clean environment; however, some industrial wastes can damage the water, atmosphere, and living environment seriously. To promote green development, policy makers in China have developed and implemented strict environmental regulations to limit the pollutant emissions and improve the environmental quality. Industrial producers implement research and development (R&D) activities to gain more profits in competitive markets. A comprehensive understanding of the green effects of R&D on different industrial wastes could provide important policy recommendations, especially regarding the coordination of innovative and green developments. In this study, the author empirically analyzed the influence of R&D input, including the intramural expenditure on R&D and full-time equivalent of R&D personnel, on industrial wastes, including the discharge of chemical oxygen demand (COD) and ammonia nitrogen, emission of sulfur dioxide, nitrogen oxides, and particulate matter, and generation of common industrial solid and hazardous wastes, based on the data from Chinese industrial sectors for 2016-2020. The main findings of empirical analyses were robust and indicated that R&D activities significantly reduced the emissions of all three industrial waste gases and decreased the discharge of COD; however, in the case of China, the partial effects on the discharge of ammonia nitrogen and the industrial solid wastes were not statistically significant. The green effects of R&D on different industrial wastes may vary and generally depend on environmental regulations, with various limitations. The most viable policy recommendations indicate that by expanding and initiating the green effect of R&D on different industrial wastes, innovative and green developments are more likely to be achieved in a coordinated manner. Additionally, this can also support special R&D activities, with the added benefit of actively developing cleaner technology to treat pollutant emissions. Development, while maintaining a clean environment to ensure public health, could be more sustainable if innovative activities reduce the production of industrial wastes. This study analyzes the green effects of R&D on industrial waste and can serve as a viable framework for future studies on sustainable development.

The environmental aspects of renewable energy consumption and structural change in Sweden: A new perspective from wavelet-based granger causality approach

The current paper assessed the time-frequency analysis interrelationship between CO₂ emissions and financial development, economic growth, renewable energy use, structural change, and non-renewable energy use in Sweden. We utilized a quarterly dataset stretching from 1980-2019. In order to unlock these interrelationships, we leverage wavelet tools (wavelet-based Granger causality and wavelet coherence). The wavelet-based Granger causality (WGC) test accounts for the issue of multiple time scales in a time series analysis. Another uniqueness of the WGC lies in its resistance to distribution assumption and misspecification in a time series model. Additionally, the wavelet coherence estimator instantaneously evaluates correlation and causality among the interacting indicators in a model. The outcomes of the wavelet coherence exposed that renewable energy, financial development, economic growth, structural change, and trade openness enhance the environment's quality while non-renewable energy intensifies CO₂. Moreover, the WGC shows that all the variables can predict each other. Based on these findings, policymakers in Sweden should focus more on improving public understanding of renewable energy and environmental preservation. We believe that Sweden's shift to service-sector-led growth will help to safeguard the environment.

Sanitation, water, energy use, and traffic volume affect environmental quality: Go-for-green developmental policies

Carbon emissions are primarily the result of human activity in urban areas. Inadequate sanitary facilities, contaminated drinking water, nonrenewable energy, and high traffic congestion have all impacted the natural ecosystem. Using data from 1975 to 2019, the study assessed the impact of the aforementioned variables on Pakistan’s carbon emissions in light of this crucial fact. The ARDL cointegration method was used to estimate the short- and long-run parameter estimates. Urban sanitation challenges and energy consumption increase carbon emissions, which affects the natural environment by raising a country’s carbon intensity. Economic expansion confirmed the inverted U-shaped relationship between carbon emissions and economic growth to verify the Environmental Kuznets Curve (EKC) hypothesis in the long run. In contrast, the monotonically rising function of carbon emissions provides evidence of the nation’s economic development in the short run. Access to clean drinking water improves population health and encourages the purchase of eco-friendly products. The government must improve sanitation services and use renewable energy sources to enhance air quality.

Influence of Senior Executives Characteristics on Corporate Environmental Disclosures: A Bibliometric Analysis

This study aims to synthesize the literature on the top management team (TMT) characteristics influence on environmental disclosures of public organizations and identify recent trends, key themes, influential journals, and authors. Our study recruited 88 research articles on the relationship of TMT characteristics and environmental disclosures from 54 academic journals published from 2010 to 2021 for bibliometric analysis. Our study has identified three influential streams: (1) Role of Politically connections of TMT, good governance in environmental disclosures; (2) Significance of environmental disclosures and performance; and (3) institutional investors and environmental disclosures. Thematic map classifies the TMT characteristics and environmental disclosures relationship themes into four categories: Niche theme (e.g., financial expertise, CFO characteristics, CEO tenure, and board backgrounds); motor themes (e.g., environmental sustainability and climate change); emerging/declining themes (e.g., Environmental disclosure, managerial ownership, and CEO tenure); and basic/transversal themes (e.g., CEO characteristics, upper echelon theory, corporate governance). This study assists academicians, policymakers, managers, and consultants in the corporate sector to understand the role of different dimensions of TMT characteristics regarding environmental disclosures. Our study concludes with important practical implications and future research directions.