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The interactive behaviors, such as competition and learning between local and neighboring cities, can lead to spatial spillover effects in policy implementation. Estimating the direct, indirect, and total effects of the carbon emission trading scheme (CETS) on green innovation is crucial to clarify its role and mechanisms. This paper applies the spatial difference-in-differences model to estimate these effects using data from 278 cities in China from 2009 to 2019. The results demonstrate that the CETS implementation catalyzes green innovation in pilot cities, which supports the Porter hypothesis. However, it has a negative impact on green innovation in neighboring cities of pilot cities, with this negative impact diminishing as distance increases. Notably, the total effect of the CETS is significantly negative, indicating that the CETS's average impact on green innovation in all cities is negative. Mechanism analysis reveals that the direct and indirect effects of the CETS on green innovation are strengthened in cities with higher levels of financial development, lower financial pressure, and easier economic growth targets. Notably, in cities with high-level industrial structures, the CETS not only enhances its contribution to green innovation but also mitigates its negative impact on neighboring cities. Furthermore, this paper explores the heterogeneous effects of the CETS from the perspective of its implementation measures. [ABSTRACT FROM AUTHOR]

The transportation industry (TRAI) is an important source of carbon emissions for China to achieve its peak carbon and carbon neutrality targets. This study analyzes the coupled integration of TRAI economic growth and carbon emissions in 30 Chinese provinces from 2005 to 2020 using a Tapio decoupling elasticity model and an environmental Kuznets curve (EKC) model. Then, a long-term energy alternative planning (LEAP) system model was constructed to predict and simulate the development of TRAI in China. The results of the study are as follows. (1) TRAI shows an inverted U-shaped decoupling in most provinces across the country, and most of the decoupling is usually more volatile in provinces with higher levels of economic development. In addition, COVID-19 positively contributes to the development of TRAI nationwide and in three regions. (2) The Tapio-EKC coupling curves of TRAI and eastern TRAI (ETRAI) nationwide have an inverted N-shape, and central TRAI (CTRAI) and western TRAI (WTRAI) have an inverted U-shape. Twenty-seven provinces crossed the decoupling elasticity inflection point nationwide, all provinces of ETRAI crossed the EKC inflection point, while all provinces of CTRAI and WTRAI did not cross the EKC inflection point; (3) The carbon reduction rates after scenario simulation ranged from 5.07 to 54.94%, with aircraft, ships, private vehicles, and their fuels (aviation kerosene, diesel, and gasoline) being the focus of energy saving and emission reduction. The coupled Tapio-EKC analysis model of this study is universal and can be extended to other provinces, cities, or industries. [ABSTRACT FROM AUTHOR]

Raising economic growth is the primary concern of most of countries especially the developing and emerging economies in order to enhance the living standard of people. However, increase in economic activities increases energy demand which rise carbon dioxide emissions and leads to environmental degradation. Technological innovations might be the remedy to overcome the issue of increased carbon dioxide emission by reducing energy use, raise energy efficiency and also push economic growth activities efficiently. In this regard, this study explores the interrelationship of technological innovation, carbon dioxide emissions, and economic growth from 1985 to 2019 in 35 Belt and Road countries. The study uses ordinary least squares, two-step system generalized method of moments, two-step difference generalized method of moments, seemingly unrelated regression, and three-stage least square models for analysis. The results indicate that technological innovations increase economic growth and enhance environmental quality. Foreign direct investment also increases economic growth while degrading environmental quality. Economic growth increases technological innovation while exerting harmful effects on the quality of the environment. The impact of trade on economic growth is positive, while financial development reduces economic growth. School enrollment has a significant and positive effect and increases technological innovation, while foreign direct investment and research and development reduce it. The results also confirm that research and development expenditures significantly reduce carbon emissions and enhance environmental quality. The findings of this study have considerable policy implications for the sample countries with respect to economic growth, technological innovations, and environmental quality. [ABSTRACT FROM AUTHOR]

Health and the environment are complex components of the countries, influenced by several factors, especially transport, and economics. Thus, this paper assesses the role of transportation and economic complexity in the environment and public health for the Organization for Economic Co-operation Development (OECD) countries from 2001 to 2020. This study also focuses on the relationship between transport and economic complexity with environmental and healthcare expenditures. Precisely, transport and economic activities stimulate healthcare expenditures through multiple channels. The current study employs the STIRPAT model to investigate the association with transportation, economic complexity, transport–carbon intensity, and healthcare expenditure. Besides, the current research confirms the plausible cross-sectional dependency across countries, and it adopts a second-generation technique. Analytical findings suggest that transportation-carbon intensity is positively and significantly associated with healthcare expenditures. Healthcare and transport–household expenditures increase transport–carbon intensity (TCI) by 75% and 45%, respectively, in the long run. In the contrast, TCI and transport–household expenditures have also a remarkable impact on healthcare expenditures and are estimated approximately 95% in the long run. Moreover, economic growth also upsurges TCI and healthcare expenditures through multiple economic activities. Besides, transport–household expenditures (THE) drastically impact transport–carbon intensity and healthcare expenditures (HEX) through passenger traffic (PTF). Diagnostic upshots unveil that the joint effect of THE and PTF increases TCI and HEX by 4 and 3%, respectively. Finally, findings recommend some policy implications and future research directions for the countries based on empirical outcomes. Countries should regulate economic activities to reduce transport carbon emissions. [ABSTRACT FROM AUTHOR]

There are worldwide growing concerns about environmental issues such as global warming and climate change. Moreover, it is expected that there will be regional differences in environmental issues. Therefore, this study focuses on a tri-regional comparison: America, Europe, and Asia-Pacific. Previous literature has paid less attention to exploring regional comparisons while considering regional heterogeneity. Against this backdrop, this study delves into the dynamic relationship between fossil fuel utilization, economic growth, globalization, urbanization, and CO2 emissions to understand the environmental implications of these interconnected factors. The study period spans from 1990 to 2021. Additionally, it employed rigorous tests to confirm cross-sectional dependence and data heterogeneity, following methodologies proposed by Pesaran (2004, 2015) and Pesaran (2007), utilizing the CS-ARDL panel cointegration methodology by Chudik and Pesaran (2015). The results confirm long-term significant relationships among OC, NGC, FDI, and UR variables in both combined panels, with and without regional dummies. However, GDP and COC become insignificant in the long run in the dummy variables regression. Furthermore, the regional dummies were found to be negative but remain insignificant, possibly due to heterogeneous effects or unobserved factors influencing each region independently. Analysis by region reveals predominant coal consumption in Asia, higher oil consumption in America, and greater gas consumption in Europe. Economic growth and CO2 emissions are positive in Asia and America but negative in Europe, aligning with theories prioritizing growth over environmental concerns in Asia and America, and advocating for renewable energy adoption in Europe. Urbanization increases energy demand and emissions, supporting the environmental revolution theory, while FDI holds the potential to reduce CO2 emissions, as per the endogenous growth theory. [ABSTRACT FROM AUTHOR]

In today's highly advanced industrialised and modernised world, China's economy is still growing, and its demand for energy is increasing daily. It is crucial to examine the connection between energy consumption, carbon emissions, and economic growth in order to promote economic growth based on energy conservation and emission reduction. Using Dezhou City in Shandong Province as an example, the study builds a VAR model of carbon emission, energy consumption, and economic growth in Dezhou City based on simplified macroeconomic sub-models, energy sub-models, and environmental sub-models. It then determines the correlation and influence mechanism between the three using tests like ADF unit root and Granger causality. The pertinent elements affecting Dezhou's carbon emissions were then investigated using grey correlation analysis. Finally, based on the study's findings, policy suggestions are made regarding energy use, carbon emissions, and economic expansion. It is necessary not only to restrain high-energy consumption industries and fundamentally optimize the energy consumption structure, but also to find new economic growth points and improve economic growth channels, so as to optimize the industrial structure. In this process, increasing the proportion of the tertiary industry is a key measure. In addition, the government needs to advocate the citizens to adopt a low-carbon lifestyle, and the concept of low-carbon environmental protection will be deeply rooted in the hearts of the people. This study will provide suggestions and theoretical guidance for China's energy consumption and carbon emissions, and help achieve high-quality growth of China and even the world economy. [ABSTRACT FROM AUTHOR]

Bangladesh, being the fastest growing economy in the South Asian region, necessitates a comprehensive study to evaluate the influence of various socio-economic factors. The primary objective of this study is to get a comprehensive understanding of the concept of sustainable development and its relationship to carbon emissions. This analysis will specifically consider the current status of economic and anthropogenic activities within the context of Bangladesh. This research examines the aforementioned matter by utilizing the latest accessible yearly data spanning from 1990 to 2020, as well as employing advanced econometric models including the dynamic autoregressive distributed lag approach and frequency domain causality test. The analysis of empirical data reveals that the economic growth experienced in Bangladesh has yielded a discernible and favorable influence on the degradation of the environment, in both the immediate and extended periods. Nevertheless, it is crucial to acknowledge that the observed impact holds no statistical significance. Furthermore, it is apparent that energy consumption has a substantial impact on the escalation of carbon emissions, in both the immediate and prolonged periods. Additionally, the processes of industrialization and foreign direct investment have also exerted adverse effects on short-term carbon emissions. A frequency domain causality test is used in this work to do a robustness analysis and confirm that there are causal links between economic growth, energy use, development, and carbon emissions over a range of time frames, such as the short, middle, and long terms. The above studies have given us a lot of useful information about how economic growth, energy use, industrialization, and environmental sustainability all affect each other in Bangladesh. Bangladesh should prioritize the formulation of policies and regulations that are centered around specific goals. These objectives include: (a) enhancing government engagement in activities related to environmental innovation, (b) integrating ecologically sustainable development targets by adopting renewable energy sources, and (c) devising strategies and initiatives to attract foreign direct investment, facilitate knowledge exchange, and promote energy-efficient manufacturing to stimulate economic growth. [ABSTRACT FROM AUTHOR]

Renewable energy is essential for boosting economic expansion and lowering carbon dioxide emission (CO2) to achieve carbon neutrality. This study's objective is to investigate the relationship between the use of renewable energy, economic growth, and CO2 for South Caucasus Countries. For analysis purposes, time series methods were applied on the panel data. Second-generation unit root and cointegration tests were used to test the cross-sectional dependence. Afterward, panel causality and panel VAR techniques were performed to examine the relationship between the variables. Based on feedback hypothesis, results of our causality analysis revealed a bidirectional causality relationship between growth and renewable energy consumption. Moreover, we revealed unidirectional causality from CO2 to renewable energy and from growth to CO2 emission. We also found that the effect of a shock in renewable energy on growth is increasing, and on CO2, it is decreasing implying that renewable energy consumption will trigger growth and have a reducing effect on CO2 emissions. We portrayed significant workable implications for policymakers, regulation bodies, companies, stakeholders, and managers. Results from this study should be extrapolated with caution since their applicability is limited to the South Caucasus Countries. In addition, the research heavily depends on summaries, which may obscure regional differences. In the future, researchers may want to dig deeper into the data and examine the subtle effect of renewable energy policy nationally. Moreover, including socio-economic aspects and technical improvements in the research might give a more thorough picture of the dynamics at play. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa (SSA) is seeing exceptional urbanization and economic expansion rates. Therefore, the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) parameters and the spatial econometric framework are used in this work to examine the influence of economic growth and urbanization on SSA's CO2 emissions. Likewise, to determine the spatial effect and understand how factors influence the spatial dependence of carbon emissions, the study builds a spatial Durbin model (SDM). In line with the findings, the spatial correlation test revealed the spatial correlations across various countries. This indicates that the changes in sub-Saharan African country's CO2 emissions impacted nearby countries and the countries themselves. Additionally, the findings reveal that, in the SSA's countries, urbanization, economic growth, industrial structure, trade, and population, excluding energy intensity, which failed the significant test, all positively influence CO2 outflows, in line with the spatial econometric model's findings. Thus, energy intensity shares an adverse impact on carbon emissions. As an outcome, energy intensity reduces carbon dioxide emissions in nearby nations and the entire region. Thus, the study recommends that policymakers account for the effects of spatial spillover when establishing low-carbon policies, encouraging a low-carbon lifestyle, promoting environmentally friendly technologies, and improving regional collaboration. [ABSTRACT FROM AUTHOR]

Air pollution is a danger to economies throughout the European Union. Industry, population expansion, a building boom owing to housing and infrastructure development, increasing vehicle traffic, crowded streets, a lack of availability of clean fuel, and ineffective control programs are the primary causes. Toxic air is a double-edged sword for a country's health since it affects just a tiny fraction of Europe's population. The financial burden and healthcare expenses for people rise when health expenditures rise. The present research looks at how dangerous air levels, healthcare costs, and the expansion of the European Union's economy are all connected. The findings are based on data collected over 29 years and account for the abovementioned variables. The results of the unit root test have the significant probability values of all variables: health expenditures (HE), gross domestic product (GDP), nitrous oxides (NOX), and carbon dioxides (CO2) emissions at both level and first difference. We used the Johansen, Kao, and Pedroni cointegration tests to test the null hypothesis of no cointegration to see that sample variables had a long-term association. The PMG-ARDL test was used to get these findings. The results confirmed the significant probability values of dependent variables in long- and short-run results that GDP has a positive and significant effect on health expenditure, while NOX and CO2 emissions have a negative and significant impact on (HE), in the European Union. To verify the results, we applied the robustness test, fully modified OLS (FMOLD), and dynamic OLS (DOLS); the robustness test results validated the PMG-ARDL test results. Environmental pollution (CO2, NOX) has a significant and negative impact on healthcare expenditures and a significant effect on GDP (HE) in the EU region. The findings of this research have implications for a wide range of parties, including those who would examine the link between factors in a study meant to improve air quality, distribute health resources, or develop strategies for economic development. [ABSTRACT FROM AUTHOR]

In recent years, there has been a persistent intensification of the global greenhouse effect. Balancing carbon emission reduction with economic growth poses an unprecedented global challenge. To better comprehend the relationship between economic growth and carbon emissions, this study first utilized the Tapio decoupling index to compare the decoupling relationship (the USA, Japan, and Germany) and three developing countries (China, India, and Russia) from 2000–2020. Additionally, the logarithmic mean Divisia index (LMDI) method was employed to investigate the factors influencing changes in carbon emissions. Our findings indicate that (1) the USA and Germany basically achieved strong decoupling; China, India, and Russia mainly showed weak decoupling; and Japan showed recessive decoupling. (2) Economic growth predominantly contributed to increased carbon emissions, with a lesser impact from population growth. A significant reduction in energy intensity restrained carbon emissions growth, as did energy structure replacement in most countries, excluding Japan. Based on this, a decoupling effort index was formulated. It has shown that the decoupling efforts made by developing countries are weaker than those of developed countries, primarily attributed to a lesser degree of decoupling between energy intensity and structure. This paper offers valuable insights for developing countries undergoing a low-carbon economic transformation. They should counterbalance carbon emission escalation resulting from economic growth through technological and energy structure improvements. [ABSTRACT FROM AUTHOR]

Economic agglomeration has played a key function in China's economic transformation. Meanwhile, structural adjustment and external pressure to reduce carbon emission necessitate a deeper investigation into its relationship with carbon productivity. This paper measures economic agglomeration and carbon productivity of 281 cities in China in 2003–2017. With the purpose of exploring the spatial effect of economic agglomeration on carbon productivity, a spatial Durbin model is constructed. In addition, the mediation effect model is also adopted for examining the transmission mechanism of economic scale and technological progress on economic agglomeration as well as carbon productivity. A heterogeneity test is also carried out to uncover the varying effects of economic agglomeration on carbon productivity. The empirical results suggest that economic agglomeration raises carbon productivity not only in the local cities but also in the neighbouring ones. The impact of economic agglomeration on carbon productivity becomes more potent as the level of economic agglomeration increases. For cities with low level of economic agglomeration, the effect is mainly achieved through the expansion of economic scale, but for cities with high level of economic agglomeration, the effect is mainly achieved through technological progress. Therefore, we suggest encouraging carbon productivity improvement through technology effect in cities with high economic agglomeration level, while enhancing carbon productivity through scale effect in cities with low economic agglomeration level. [ABSTRACT FROM AUTHOR]

R&D spending upsurges technological advancement and innovation which results in lowering energy consumption and environmental degradation. The current study investigates the asymmetrical impact of R&D spending on CO2 emissions in China via employing annual data from 1980 to 2021 and the NARDL model for empirical analysis. The estimated results of the NARDL model confirmed that there are asymmetries in positive and negative coefficients of R&D spending in China. The results depict that the positive shock in R&D spending exerts a negative and statistically significant impact on CO2 emissions in both runs implying that an increase in R&D spending lowers CO2 emissions. However, the negative coefficient of R&D spending yields a positive and statistically significant impact on CO2 emissions revealing the fact that a negative shock in R&D spending results in the upsurge of CO2 emissions in China. According to these findings, the impact of positive and negative shocks in R&D spending on CO2 emissions is asymmetric. The findings also show that the impact of a negative shock in R&D spending is greater than the impact of a positive shock on CO2 emissions. In addition to the negative shock in R&D spending, increases in energy consumption, economic growth, and FDI inflows also contribute to an upsurge in CO2 emissions in China. The robustness of the estimated results is assessed using standard fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models. The FMOLS and DOLS results have been confirmed to be sound and consistent with the results of the NARDL model. The study suggests that the economic strategies should aim at investing in R&D spending to foster environment-friendly technological innovations and to lower environmental degradation in China. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei region is not only an important economic center in China, but also one of the major regions contributing to China's carbon emissions. Revealing the spatial distribution between carbon emissions and economic growth is essential for the formulation of low-carbon development policies. Following the principle from macro to micro, this paper investigates the spatial evolution trend and distribution characteristics between carbon emissions and economic growth in the Beijing-Tianjin-Hebei region from 2005 to 2020 by applying imbalance index model, the rank-scale rule, and decoupling index model. The results show that the imbalance index of carbon emissions decreased between 0.0601 and 0.0533 in a fluctuating way, indicating that the imbalance of spatial distribution of carbon emissions decreases. The imbalance index of economic growth increased between 0.0738 and 0.0851, indicating that economic growth has become more disequilibrated, and the spatial evolution of carbon emissions is not coordinated with economic growth. The Zipf dimension of carbon emissions declined from 1.1806 in 2005 to 0.9594 in 2020, and carbon emissions declined in big cities and increased in cities of the middle order. The Zipf dimension of economic growth increased from 1.1384 in 2005 to 1.2388 in 2020, and the economic growth monopoly in big cities increased. The decoupling coefficient of carbon emissions to economic growth declined, and the driving effect of economic growth on carbon emissions diminished. It is recommended that the Beijing-Tianjin-Hebei region should coordinate the allocation of factors and coordinate industrial adjustment. Hebei should accelerate industrial upgrading and establish a diversified industrial system. [ABSTRACT FROM AUTHOR]

Large-scale internal migration and unprecedented urbanization have dramatically promoted economic growth in China, resulting in a rapid surge in carbon emissions in urban areas. However, few studies have investigated the causal effect of mass internal migration on carbon emissions or examined the effects of autonomous mitigation mechanisms, such as population agglomeration and technological innovation. This study identifies the causal effect of internal migration on prefectural-level cities' carbon emissions in China by employing an instrumental variable and further investigates the buffering effect of population agglomeration and technological innovation using mediating effect models. The results show that mass internal migration has a substantial impact on increasing carbon emissions in prefectural-level cities. If the proportion of inflowed migrants rises by 1% point, prefectural-level cities' carbon emissions per capita will increase by 1.9%. A series of robustness tests confirms the result. Population migration also promotes population agglomeration and technological innovation in urban areas. Two autonomous mechanisms buffer 11.9% and 5.4% of prefectural-level cities' incremental carbon emissions per capita caused by population migration, respectively. This study highlights the crucial role of population agglomeration and technological innovation in mitigating carbon emissions in cities experiencing significant migrant inflows and provides several implications for formulating relevant policies. [ABSTRACT FROM AUTHOR]

This study examines the environmental Kuznets curve (EKC) theory and its possible relevance in the context of China and the complex and one-of-a-kind interaction between financial innovation, environmental deterioration, and China. China's fast industrialization and consequent economic expansion have been accompanied by significant environmental difficulties, despite the country's status as the world's second largest economy. The research takes a secondary data approach to its investigation of this topic, drawing on a large dataset that spans many decades to ensure a thorough examination of the dynamic interaction between financial innovation and numerous environmental variables. The primary objective of this research is to determine whether or not recent developments in financial technology have contributed to the current trends of environmental degradation in China. In keeping with the central tenet of the EKC hypothesis, this study uses cutting-edge econometric techniques to investigate the existence of nonlinear correlations and inflection points. In addition, the research analyzes how policy interventions and regulatory measures have shaped the tendencies spotted. In elucidating the usefulness of financial innovation as a tool for promoting environmental betterment, this study's findings substantially contribute to the current discussion around sustainable development and economic policy. This research also carefully assesses the applicability of the EKC theory in China, providing insights that may be used to inform future environmental policy decisions. Ultimately, the success of measures to promote sustained economic growth and the preservation of the environment in China depends on an in-depth understanding of these delicate relationships. In addition, the lessons learned from this study have the potential to serve as a guide for economies facing similar difficulties. [ABSTRACT FROM AUTHOR]

The carbon emissions trading system (CETS) is a helpful policy instrument for separating carbon emissions from economic expansion, and it significantly impacts energy efficiency (EE). This study uses 30 Chinese provinces from 2007 to 2020 as its research samples, and classifies energy efficiency into single-factor energy efficiency (SFE) and total-factor energy efficiency (TFE), using the difference-in-differences model to examine the effect and mechanism of the CETS on EE. As an additional tool to assess the efficacy of the CETS, the corresponding evolution of the rebound effect of energy-related carbon emissions (RECE) is also calculated. This study shows that the CETS can significantly improve EE in China's pilot provinces. The influence mechanism indicates that the effect of the CETS on EE is influenced by the level of government governance, green innovation, and industrial structure optimization. Further study finds that after the CETS was carried out, the RECE in pilot provinces was higher than that in non-pilot provinces, and 31.4% of carbon emissions reduced by EE improvement rebounded. Therefore, the CETS has yet to realize its full carbon reduction potential. The study offers specific policy proposals for the enhancement of China's CETS in light of the aforementioned findings. [ABSTRACT FROM AUTHOR]

The rising GHG emissions and climate change have resulted in number of catastrophes such as floods, droughts and heat waves. Accordingly, researchers are interested in exploring the nexus between GHG emissions and economic growth. This research study is motivated to explore the moderation of transportation competitiveness for economic growth and carbon emissions of transport sector in global perspective. The annual time series data for study variables are used for time period from 2008 to 2018 for 121 countries. The panel quantile regression (PQR) estimation technique is used for analysis of results. The study results validated inverted U-shaped environmental Kuznets curve (EKC) for quantile group-1 and 2, while U-shaped EKC was validated for quantile group-3 and 4. The moderation of transport competitiveness significantly tends to achieve environmental sustainability for economic growth and carbon emissions of transport sector for quantile group-1 and 2. However, the moderation of transport competitiveness increases carbon emissions of transport sector in quantile group-4. The study results implicated that process of economic growth resulted in expansion of transport sector in quantile group-3 and 4 beyond sustainable level. The various policy recommendations are advocated to improve the quality of transport sector to mitigate carbon emissions. [ABSTRACT FROM AUTHOR]

Exploring the relationship between economic development and carbon emissions is a hot issue of concern to academia. Taking Chinese cities as the research object, this study constructed an allometric growth model of economic scale and carbon emissions to analyze the spatial–temporal evolution of their allometric growth from 2000 to 2017. Additionally, the geographical detector model was used to reveal the driving mechanism of allometric growth. The findings were as follows. (1) The spatial–temporal patterns of economic scale and carbon emissions were dominated by hot spots. Additionally, their size distribution was in an equilibrium stage. (2) The gap between the economic growth rate of Chinese cities and the growth rate of carbon emissions grew, reflecting the remarkable achievements in carbon emission reduction in Chinese cities as a whole. The scaling exponent declined from east to the west during 2000–2008, but showed the opposite trend during 2009–2017. The proportion of cities with negative allometric growth in the sample cities increased from 76.49 to 97.86%. (3) The influence of city investment intensity, energy utilization efficiency, technological development level, social consumption level, fiscal investment level and economic development level on allometric growth gradually decreases. These factors were also the main factors affecting the spatial–temporal heterogeneity of allometric growth. (4) The impact of various factors had a synergetic enhancement effect. These factors can be classified as economic factors, environmental factors and a combination of them. Under the nonlinear coupling of multiple factors, a spatially differentiated pattern of allometric growth was formed. [ABSTRACT FROM AUTHOR]

Financial development is a multidimensional process that contributes to economic growth but sometimes it has a devastating effect on climate change. No country can achieve sustainable development goals without caring the environmental quality. The present study investigates the moderating role of globalization (KOF) in determining the financial development (FD) on environmental degradation in the SAARC countries from 1990 to 2020. The long-run coefficients are estimated using the panel quantile regression (PQR) approach at lower, middle and upper quantile groups. The study shows the U-shaped relationship across three quantile groups based on financial development and carbon emissions. The moderator globalization (KOF) brings up the change in the turning point and flattens before the maturity of the U-shaped curve at the middle quantile while flattens after the maturity of the U-shaped curve at the upper quantile. The study recommends that by using energy-efficient technologies, better financial sector interaction with globalization enhances the environmental quality in SAARC countries. [ABSTRACT FROM AUTHOR]

The study examines the relationship between green finance development, carbon emission intensity, and economic development in China's 30 provinces. The entropy approach is used to calculate the green finance development index, and a panel vector autoregressive model is established using this index along with economic development and carbon emission intensity. The study finds that green finance can promote economic growth and help achieve emission reduction objectives, while increasing carbon emissions can also promote economic growth. The study also highlights regional differences, with the economic growth of the eastern and central regions negatively correlated with carbon emissions after surpassing the inflection point of the environmental Kuznets curve. Additionally, the study suggests that there is still room for growth in green finance in the western region. The findings have important policy implications for China in developing targeted development strategies. [ABSTRACT FROM AUTHOR]

Growth target management drives China's economic expansion, leading to potential carbon emission externalities. This study examines the impact of economic growth target setting on carbon emission performance in 257 Chinese localities from 2004 to 2020. Using cluster standard error regression, 2SLS instrumental variable regression, and the spatial Durbin model, the results show that moderate growth targets improve urban carbon emission performance. Conversely, aggressive targets do not enhance regional carbon emission performance. Moderate growth targets foster innovation in green technology, while aggressive ones encourage investment in fixed assets and new city growth, impeding performance. Cities in the eastern and western regions, with larger populations and less reliance on natural resources, benefit more from effective economic development targets. The establishment of local targets negatively affects neighboring regions' carbon emissions performance, particularly at a spatial scale of 100 to 200 km. This paper contributes to understanding the environmental consequences of growth target setting and offers insights for balancing economic growth with carbon emission governance in emerging market countries. [ABSTRACT FROM AUTHOR]

The problem of climate change, which causes various negativities in the global sense, is one of the important research topics. It is necessary to determine the factors affecting carbon dioxide (CO2) emissions, which are the main determinants of climate change, and to take measures for this. In this study, based on the hypothesis that economic growth, energy usage, trade openness, and foreign direct investment affect CO2 emissions, it was aimed to examine the effects of economic growth, energy usage, trade openness, and foreign direct investment on CO2 emissions for G8 countries using annual data for the period 1990–2018. For this purpose, first, a literature review was done in the study. Then, cross-section dependency and heterogeneity tests were performed as empirical analyses. Afterward, unit root tests, cointegration analyses, and causality analyses were performed in the study. Finally, in the study, short-term parameters and long-term parameters were estimated to capture possible dynamic relationships between variables. The Westerlund Error Correction Model (ECM) panel test for cointegration showed that there is a cointegration relationship between these variables for both the entire panel and the cross-section units. The results of the Augmented Mean Group (AMG) estimator method showed that (i) economic growth has no effect on CO2 emissions in 7 of 8 countries, (ii) energy usage increases CO2 emissions in 4 of the countries studied but decreases it in one of them, and (iii) foreign direct investments and trade openness do not affect CO2 emissions in 4 countries but positively affects in 2 countries and negatively in 2 countries. According to the results obtained from the Pooled Mean Group (PMG) analysis, while economic growth, energy usage, and trade openness affect CO2 emissions in the long run, economic growth, energy use, and trade openness affect CO2 emissions in the short run too. According to Dumitrescu-Hurlin panel causality results, it was seen that there is no causal relationship between CO2 emissions, economic growth, and energy use. While there is a unidirectional causality from CO2 emissions to foreign direct investments, it was determined that there is a bidirectional causality between trade openness and CO2 emissions. When the results were examined in general, it was understood that the variables of economic growth, trade openness, foreign direct investment, and energy usage are effective on CO2 emissions in the G8 countries. It would be beneficial for countries to include the objectives of making production with clean production technologies, ensuring efficient use of energy, and expanding the use of renewable energies among their main targets. [ABSTRACT FROM AUTHOR]

The relationship between economic growth and environmental pollution continues to attract significant research interest for researchers, practitioners, and policymakers all over the globe. Theoretically, the environmental benefit of economic growth should be greater than its negative externality with higher level of development. However, from the African perspective, countries with higher economic performances often face several environmental challenges, which raises the doubt whether economic growth helps or constrains environmental quality improvement. Under the environmental Kuznets curve (EKC) hypothesis, this study re-examined the effect of economic growth on CO2 emissions conditional on the dynamics of urbanization, renewable energy, and good governance across 47 African countries using panel data from 1996 to 2019. We employ panel cointegration tests to establish whether there is a long-run equilibrium relationship among our variables. We also apply pooled mean group ARDL (PMG-ARDL) techniques and the Dumitrescu-Hurlin causality test to determine the long- and short-run effects of economic growth, urbanization, renewable energy consumption, and good governance on CO2 emissions. The results from the PMG estimator validate the EKC hypothesis since a 1% surge in GDP per capita increases emissions by 0.61% in the long run, while a 1% increase in its square decreases emissions by 0.03%. In the short-run, economic growth does not exercise any significant effect on emissions. Furthermore, results indicate a significantly negative and positive long-run effect of renewable energy and governance, respectively. Finally, our causality test shows bidirectional relationship between CO2 emissions and all the explanatory variables. Henceforth, we provided policy implications based on the study's results. [ABSTRACT FROM AUTHOR]

Carbon emissions have risen in line with China's economic expansion. The key to sustainable development is finding a way to strike a balance between economic expansion and environmental protection, so improving carbon emission efficiency is vital. This paper uses provincial data from 2010 to 2020 to account for total carbon emissions using the emission factor method and obtains carbon emission efficiency data on this basis. A dynamic spatial Durbin model is then used to empirically test the possible influencing factors. The results show that, firstly, the growth rate of total carbon emissions is generally in line with the growth rate of GDP, indicating that there is no 'decoupling' in the economic system. Second, regional carbon emissions and carbon emission efficiency are not necessarily related. Thirdly, there is a clear spatial effect on carbon emission efficiency. The eastern region has the highest carbon emission efficiency, the western region has the lowest, and the northeastern and central regions have little difference in carbon emission efficiency. Further spatial and temporal migration analysis reveals that five provinces have made the migration between 2010 and 2020. Fourthly, in the short term, the direct and indirect effects of the factors affecting carbon emission efficiency are insignificant, but in the long term, most of the factors have significant direct and indirect effects on carbon emission efficiency. Finally, based on the above research findings, this paper makes policy recommendations. [ABSTRACT FROM AUTHOR]

Excessive carbon emissions are the major challenge to global sustainable development. In the context of the coronavirus pandemic, pressure on global economic growth is gradually rising, threatening established carbon reduction targets. However, the relationship between economic growth pressures and carbon emission intensity has yet to be clearly discussed. Thus, this study quantitatively discusses the impacts of economic growth pressures from central (EGPN) and provincial (EGPP) governments on city carbon intensity. The study is based on data from China's city panels from 2005 to 2019. This study finds that (1) there is a U-shaped correlation between economic growth pressure and a city's carbon emission intensity, whether the economic growth pressure comes from the central government or the provincial government; (2) carbon emission intensity is more sensitive to economic growth pressure from the provincial government than it is to economic growth pressure from the central government. The findings of this study will help enhance the understanding of the relationship between economic growth pressure and carbon emission intensity, and can also provide a reference for global sustainable development that balances economic growth and environmental protection. [ABSTRACT FROM AUTHOR]

China is the world's largest energy consumer and CO2 emitter, facing a great challenge of CO2 emission mitigation. In order to identify driving factors for prefecture-level carbon emissions in western China, a case study of Haixi was performed. Time series analysis was undertaken in this study to provide a holistic picture of the historical trend of energy-related CO2 emissions. The relationship between CO2 emissions and economic growth was also explored based on decoupling analysis. Subsequently, logarithmic mean Divisia index was adopted to identify key factors driving CO2 emissions. Results showed that the energy-related CO2 emissions generated by Haixi increased to 18.18 million tons in 2016 from 7.26 million tons in 2007. Results also indicated that Haixi had not achieved decoupling of economic growth from CO2 emissions. Economic activity was the dominant positive driver in changes of CO2 emissions, while industrial structure was the dominant negative driver over the entire period. Suggestions based on empirical findings and local realities were proposed, which may provide reference for stakeholders regarding the reduction of CO2 emissions. [ABSTRACT FROM AUTHOR]

The Chinese government has established carbon emissions trading schemes (CETS) to cope with climate change and reduce carbon emissions. This paper uses the multi-period difference in difference (DID) model to explore the impact of CETS on cities' GDP and GDP growth rates in China based on data from 285 prefecture-level cities from 2008–2019. We find that CETS increase the level of GDP by 3.4% and the GDP growth rate by 0.004. The mechanism of increasing GDP includes promoting investment and innovation, and the mechanism of increasing the GDP growth rate includes only promoting the investment growth rate. Thus, CETS satisfy both the weak and strong versions of the Porter Hypothesis from the GDP and growth rate perspectives. In the heterogeneity analysis, we find that the impacts of CETS on cities' GDP and GDP growth rates decrease with the increase of the corresponding dependent variable. In the spatial spillover analysis, we find that the establishment of CETS has a positive spillover effect on the GDP of cities around 50 km and 150 km, and a negative spillover effect on the GDP of cities around 200 km, but there is no spatial spillover effect on the GDP growth rate. [ABSTRACT FROM AUTHOR]

This study seeks to address pertinent economic and environmental issues associated with natural gas flaring, especially for the world's leading natural gas flaring economies (i.e. Russia, Iraq, Iran, the United States, Algeria, Venezuela, and Nigeria). By applying relevant empirical panel and country-specific approaches, the study found that fuel energy export positively impacts economic growth with elasticity of ~ 0.22 to ~ 0.24 for the panel examination. It is further revealed that environmental quality in the panel is hampered by increase in economic growth, gas flaring, fuel energy export, and urbanization. Moreover, for the country-wise inference, government quality desirably moderates economic and environmental aspects of gas flaring in Venezuela and Nigeria, and in Russia and Iran respectively. However, government quality moderates gas flaring to cause economic downturn in the USA. Additionally, economic growth increased with increase in urbanisation (in Iraq and the USA), gas flaring (in Iran and the USA), government quality (only in the USA), and fuel energy export (only in Algeria) while economic growth downturn is due to increase urbanisation in Russia and the USA, increase in fuel energy export in the USA, and increase in government quality in Russia. Meanwhile, environmental quality is worsened through intense carbon dioxide emission from increased urbanisation activity (in Iraq, Iran, Algeria, and Nigeria), increased fuel energy export (in Nigeria), increased natural gas flaring (in Algeria and Nigeria), increased GDP (in Russia, Iran, USA, Algeria, and Venezuela), and high government quality (in Iran). Interestingly, the result revealed that increase in GDP (in Nigeria), increase in urbanisation (in the USA), and increase in gas flaring (in Algeria and Nigeria) dampens environmental quality. Importantly, this study offers policy insight into sustainable approaches in natural gas production, government effectiveness, and regulatory quality. [ABSTRACT FROM AUTHOR]

This research aims to examine the validity of the Environmental Kuznets Curve (EKC) hypothesis in 37 Organization for Economic Co-operation and Development (OECD) countries over the period from 1960 to 2019. Panel Quantile Regressions (QR) show that for the lower quartile, economic growth does not impact emissions; for the central quartile a U-shaped curve emerges; while for the upper quartile, an N-shaped curve is found. In addition, cointegrating regressions highlight that economic growth, fossil fuel consumption, and population exert a detrimental effect on the environment, while renewable energy consumption reduces carbon dioxide (CO2) emissions. These results are confirmed by panel causality tests since a feedback mechanism is found between CO2 emissions and the remaining series. Furthermore, single-country estimates provide evidence of great variability in the sample. [ABSTRACT FROM AUTHOR]

Population aging, economic globalization, and economic growth simultaneously cause changes in environmental quality, but so far no studies have integrated these key factors into the same environmental policy framework. Thus, this study uses the more robust Westerlund cointegration test and the augmented mean group (AMG) estimator (robust to cross-sectional dependence (CD), heterogeneity, and endogeneity) to estimate the long-term relationship between population aging, economic globalization, economic growth, and per capita carbon emissions in East Asian countries during the period 1975–2018. The analysis results reflect that population aging significantly reduces the long-term per capita carbon emissions of specific East Asian countries. However, energy generation and economic globalization make significant contributions to long-run per capita carbon emissions. Moreover, the impact of economic growth on long-term per capita carbon emissions is significantly positive, while the impact of square of economic growth on long-run per capita carbon emissions is significantly negative, thus validating the inverted U-shaped environmental Kuznets curve (EKC) hypothesis for specific East Asian countries. The results of the causality test indicated a two-way causality between energy generation and per capita carbon dioxide emission, supporting the feedback hypothesis. There is also a two-way causal relationship between aging population and per capita carbon dioxide emission. Policy recommendations are discussed in response to the empirical findings of this study. [ABSTRACT FROM AUTHOR]

In Europe, there has been a significant shift in the movement of people and things. Nonetheless, despite the fact that transportation is an important component of the supply chain, its environmental consequences pose a severe threat to the ecosystem as a whole. As a result, we intend to explore the relationship between transportation, economy, and CO2 emissions. We used the Static method with Pooled OLS, then tested the Granger causality to validate the use of dynamic approach via the GMM system. The major findings revealed that GDP and trade openness had a considerable impact on CO2 emissions. Although the three modes of transportation have different effects on CO2 emissions, road density has a positive and considerable impact on CO2 emissions. The railway network is inversely connected to CO2 emissions. While the quantity of flight passengers has no substantial effect on emissions. In terms of the impulse response function, there is an initial shock in period 2 for the response of air passengers carried to CO2 emissions, followed by convergence back to zero in period 6, whereas road density has a slight decrease in period 2 with a post shock peak in period 4, followed by convergence back to zero in period 5. The variance decomposition results reveal a little increase until the fifth period for road density, air passengers, and trade openness with coefficients equal to 0.0893, 0.636, and 1.573, respectively, after which these three variables offer decreasing coefficients. [ABSTRACT FROM AUTHOR]

This research investigates the resource curse hypothesis and environmental sustainability by integrating China's natural resources, renewable energy, and urbanization. However, the EKC N shape describes the complete picture of the EKC hypothesis for the growth-pollution relationship. The findings of FMOLS and DOLS show that economic expansion positively drives carbon dioxide emissions in the beginning, then negatively so after the target level of growth is reached. Continuing economic expansion in China does not maintain the intended level and again has a beneficial impact on the country's carbon dioxide emissions. However, the EKC U, inverted U, and N shapes persist in the growth-pollution connection over the long term. Although adopting renewable energy and urbanization help reduce carbon dioxide emissions, the formation of fixed capital worsens environmental conditions. Natural resource rents are a major cause of environmental degradation and the resource curse that has plagued China. Economic growth, as well as its square and cube, has a causal effect on CO2 emissions, as shown by the frequency domain causation. Carbon dioxide emissions at frequencies of 0.05, 1.50, and 2.50 are momentarily predicted by the use of renewable energy and urbanization. The investigation recommends switching to renewable energy sources owing to low cost and the potential to limit the overuse of non-renewables. To balance the overdo of natural resources and ensure continued long-term growth-environment sustainability, technological advancement is recommended as a countermeasure as a mitigating mechanism. [ABSTRACT FROM AUTHOR]

Financial inclusion is critical element of economic growth as it makes financial services available to all facets of society and hence has an influence on environmental quality. Using data from 2004 to 2019, this research evaluates the asymmetric nexus between financial inclusion and environmental quality in the top-10 polluted nations (China, India, Russia, USA, Japan, Iran, Germany, Saudi Arabia, South Korea, and Indonesia). Previous research used panel data approaches, which resulted in usual findings of the connection between financial inclusion and environmental quality, even with the reality that numerous nations did not show such a linkage individually. This research, conversely, utilizes an exclusive method 'Quantile-on-Quantile (QQ)', which permits us to probe each nation distinctly to provide multilateral yet country-specific information about the relation between the variables. The estimations demonstrate that financial inclusion degrades environmental quality in 7 out of the 10 economies at many quantiles of data distribution. Additionally, the outcomes reveal that the degree of asymmetry between financial inclusion and carbon emissions differs by nation, stressing the need of governments giving particular attention while implementing policies related to financial inclusion and a sustainable environment. [ABSTRACT FROM AUTHOR]

As the world's largest carbon dioxide emitter, China is curbing coal consumption and increasing natural gas and renewable energy consumption to curb the increase in carbon emissions. At the same time, China is still the largest developing country in the world. Therefore, it is very important to investigate the links between different types of energy consumption, economic growth, and carbon emissions. In this paper, impulse response functions and Granger causality test based on time-varying parameters vector autoregressive model are used to explore the time-varying relationship among CO2 emissions, economic growth, and heterogeneous energy consumption (coal, gas, oil, and renewable energy) in China over the period 1980–2019. The results show that reducing coal and oil consumption and increasing natural gas and renewable energy consumption will not significantly hinder economic growth. In addition, in the long run, reducing coal and oil consumption and increasing renewable energy consumption can significantly reduce carbon emissions. However, after 1998, increasing natural gas consumption will significantly increase carbon emissions. This study reveals the time-varying relationship between heterogeneous energy consumption, economic growth, and carbon emissions, and provides suggestions for China to achieve low-carbon economic growth. [ABSTRACT FROM AUTHOR]

The present paper investigates the influence of renewable energy consumption (REC), economic growth (GDP), financial development index (FDI), z-score (ZS) and control of corruption (CC) on carbon dioxide (CO2) emissions, for eighteen different APEC economies over the period 2000–2019 using the Pooled Mean Group-Autoregressive Distributed Lags (PMG-ARDL) approach and Granger causality tests. The outcomes of the empirical study confirm that the variables are cointegration using Pedroni tests. The long-run estimates revealed that economic growth and renewable energy contribute to the huge of carbon emissions, while financial development, ZS and CC lead to decrease carbon emissions. Granger causality shows that, in the long-run, there is bidirectional causality between CO2 emissions, economic growth, and financial development. In the short-run and for basic variables, Granger shows a unidirectional causality from CO2 emissions and economic growth to REC and; unidirectional causality from financial development, ZC and CC to CO2 emissions. A comprehensive approach is needed in APEC countries to effectively reduce CO2 emissions and promote sustainable development, including encouraging green financial products, reinforcing financial regulations, transitioning to a low-carbon economy, enhancing renewable energy usage, and improving governance and institutional quality, while considering the distinctive characteristics of each country. [ABSTRACT FROM AUTHOR]

This study assesses the role of government spending on environmental sustainability based on a framework that combines the environmental Kuznets curve (EKC) hypothesis with the Armey curve hypothesis. Specifically, the inverted U-shaped relationships between carbon (CO2) emissions and economic growth (EKC hypothesis) and between government spending and economic growth (Armey curve hypothesis) are analyzed using a composite EKC model tested for cross-sectional dependence and heterogeneity, panel unit root, panel co-integration, and the augmented mean group estimation. In so doing, this study pursues a potential transmission mechanism leading from government spending to CO2 emissions through the growth channel and presents a novel way to develop a better understanding of how economic growth policy and energy policy can be synchronized. Empirical results show that economic growth acts as a transmitter between government spending and CO2 emissions in the USA, UK, and Canada. However, the composite EKC hypotehesis is confirmed only for the USA and Canada, where the optimal level of government spending that maximizes CO2 emissions is 29.87% and 29.22% of GDP, respectively. In contrast, the optimal level of government spending equivalent to 28.30% of GDP minimizes CO2 emissions in the UK. The key policy implication is that governments can achieve sustainable economic growth by setting standards for their spending levels. [ABSTRACT FROM AUTHOR]

In recent years, environmental issues have become controversial, and policymakers are discovering new predictors of carbon emissions. Some economists/researchers have advocated for fiscal decentralization to improve the quality of the environment by offering more financial authority to provincial/local and sub-national governments. Therefore, this work aims to inspect the effect of fiscal decentralization on economic growth and environmental quality in India by taking data from 1996 to 2021. This work applies both ARDL and NARDL econometric models for empirical examination. The findings of this study suggest that expenditure decentralization has asymmetric long-term and short-term consequences on economic growth, and carbon emission in India. The result of the asymmetric ARDL model also indicates that positive and negative shock in expenditure decentralization contrarily affects economic growth and carbon emission. Moreover, the positive and negative shock in revenue decentralization helps in reducing carbon emissions both in the long run and short run in India. These outcomes are useful for policy analysis from the Indian economic policy perspective. The study also laid out potential outcomes that may benefit India's local governments and central government in resolving the issues of economic growth and environmental degradation. [ABSTRACT FROM AUTHOR]

Based on the environmental Kuznets curve (EKC) hypothesis and using Chinese provincial panel data from 2002 to 2019, this study examines how different types of healthcare expenditure and levels of economic development and energy consumption contribute to carbon emissions regionally. Considering the wide regional differences in the development levels of China, this paper uses quantile regressions and draws the following robust conclusions: (1) The EKC hypothesis was validated by all methods in eastern China. (2) The carbon emission reduction of government, private, and social health expenditure is confirmed. Furthermore, the impact of health expenditure on carbon reduction decreases from East to West. (3) Government, private, and social health expenditure all cause reductions in CO2 emissions, with private health expenditure having the largest negative effect on CO2 emissions, followed by government health expenditure and finally social health expenditure. Overall, the limited empirical work available on the impact of different kinds of health expenditure on carbon emission in the existing literature, this study greatly assists policy makers and researchers to understand the importance of health expenditure in improving environmental performance. [ABSTRACT FROM AUTHOR]

The main objective of this manuscript was to investigate the relationships among economic development, tourism, the use of natural resources, technical advancement, and carbon dioxide emissions in the BRICS group of nations. Data from the panel was gathered from 1995 to 2018. Modern methodology tools including the CS-ARDL tests, Westerlund cointegration tests, and panel data unit root tests have been used in this study. Results of the models show that all the variables were transformed to the first difference to make it stationary. The Westerlund model test results suggest that dependent and independent variables have robust cointegration. Results of the CS-ARDL models reveal that all the variables signed, and significance are aligned with the economic theory. It indicates that except for tourism, the rest of the variables like technical innovation, natural resources, and economic growth have positive and significant effects on carbon dioxide emissions both in the short and long runs. Additionally, a 1% rise in economic growth, technical innovation, and natural resources over the long term would raise carbon dioxide emissions in the BRICS economies by 1.79%, 0.15%, and 0.10%, respectively. However, a 1% increase in tourism would result in a 0.39% decrease in carbon dioxide emissions among the nations in the panel data set. Therefore, the promotion of sustainable tourism and advancement in technological innovation is highly important in these countries, so the high impact of environmental degradation pressure may reduce to some extent. An in-addition comprehensive set of policies should be made on encouraging low-carbon transportation, promoting sustainable tourism certification, boosting local produce, reducing waste management, and provide education and awareness campaigns to tourists. [ABSTRACT FROM AUTHOR]

A growing body of literature has highlighted the importance of green innovation and institutional quality in sustainability transitions. However, there is little empirical research knowledge about green innovation and institutional quality as significant factors for sustainable development, particularly in Africa. In this context, the study examines the relationship between green innovation, institutional quality, economic growth, export, energy consumption, urbanization, and CO2 emissions in three (3) African countries over the period 1990 to 2016 at a panel and individual country level. Westerlund–Edgerton panel cointegration test together with the Cross-sectional Augmented Dickey-Fulller (CADF) test and Cross-sectional Im, Pesaran and Shin (CIPS) test correspondingly confirmed the variables employed are co-integrated and as well stationary. Major findings from the augmented mean group (AMG) estimator unveiled that: (i) green innovation mitigates CO2 emissions, whereas institutional quality increases CO2 emissions at the panel level and in South Africa; (ii) energy consumption increases CO2 emissions at the panel level and in all the individual countries; (iii) urbanization increases CO2 emissions at the panel and in Egypt and South Africa; (iv) an inverted U-shaped is evidenced to exist among economic growth and CO2 emissions in Egypt and South Africa. Finally, Dumitrescu-Hurlin panel causality test revealed a unidirectional causal link from CO2 emissions to green innovation and institutional quality correspondingly. Policy implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

This research analyzed the effect of tourism market diversification on Singapore's CO2 emissions by measuring the level of concentration of source countries in a foreign tourist basket of Singapore using a Herfindahl–Hirschman index. Our results indicated that the index fell over the period 1978–2020, which means the diversification of source countries of Singapore's foreign tourists increased. By applying the recent bootstrap and quantile ARDL models, we found that tourism market diversification and inward FDI act as stumbling blocks to CO2 emissions. In contrast, economic growth and primary energy consumption increase CO2 emissions. Policy implications are presented and discussed. [ABSTRACT FROM AUTHOR]

Oil and natural consumption are non-renewable energy sources that are the main drivers of economic growth, but these energy sources are also the main causes of environmental degradation in Northeast Asian countries. The main objective of this study is to examine the impact of renewable energy consumption, non-renewable energy consumption on CO2 emissions, and economic growth in seven selected Northeast Asian countries during the period 1970–2020. First, the cross-sectional dependence test recommended by Pesaran, Ullah, and Yamagata (2008) concludes that there is no cross-sectional dependence in the panel data model, so it is feasible to use the first-generation panel data methods. Later, cointegration tests proposed by Pedroni (Oxford Bull Econ Stat 61:653–670, 1999, Economet Theor 20:597–625, 2004), Kao (J Econom 90:1–44, 1999), and Westerlund (2007) were adopted, revealing long-term cointegration relationships among model panel variables. Long-term variable coefficient elasticities were detected using the estimation techniques of panel fully modified ordinary least squares (FMOLS) and panel dynamic ordinary least squares (DOLS). Two-way causality of variables was detected using the Dumitrescue-Hurlin (Econ Model 29:1450–1460, 2012) panel causality test. The results of the analysis highlight the significant progressive effects of renewable energy consumption, nonrenewable energy consumption, employed labor force, and capital formation on long-run economic growth. The study also concluded that renewable energy consumption significantly reduced long-term CO2 emissions, while non-renewable energy consumption significantly contributed to long-term CO2 emissions. Estimates from the FMOLS technique reflect a significant progressive effect of GDP and GDP3 on CO2 emissions, while GDP2 has a significant adverse effect on CO2 emissions, thus validating the N-shaped EKC assumption in selected group of countries. Furthermore, the feedback hypothesis is supported based on the two-way causality between renewable energy consumption and economic growth. Strategically, this evidence-based empirical study demonstrates that renewable energy is a valuable process that can protect the environment and contribute to future economic growth in selected countries by addressing energy security and reducing carbon emissions. [ABSTRACT FROM AUTHOR]

The significance of the sports economy to the national economy is growing as the country develops rapidly. The term "sports economy" is used to describe the economic activities that are directly or indirectly tied to sports. This work introduces a multi-objective optimization model for a green supply chain management system, intending to reduce the economic and environmental impact of storing and transporting potentially dangerous products. This research intends to examine the impact of the sports sector on green economic growth and competitiveness in the China region. An empirical analysis is conducted to determine the relationship between sports economics and green supply chain management by employing data on 25 provinces of the China region for 2000 and 2019. To fulfill this study's objective and determine the effect of carbon emission, this study will use renewable energy, sports economics, green supply chain management, information and communications technology, and waste recycling as explanatory variables. In order to obtain the desired objectives, the current study will use the short run and long run of the cross-sectionally augmented autoregressive distributed lag and pooled mean group tests. Besides, this study uses an augmented mean group, fully modified ordinary least square, and dynamic ordinary least square estimations for the robust check. In contrast, renewable energy, green supply chain management, sports economics, information and communications technology, and waste recycling decrease CO2 emissions and, therefore, facilitate the carbon-abatement agenda of the China region. [ABSTRACT FROM AUTHOR]

This paper investigates the association between CO2 emissions and a range of factors, including electricity consumption, economic growth, urbanization, and trade openness for six Gulf Cooperation Council (GCC) countries using data covering the 1965–2019 period. Namely, Oman, Saudi Arabia, the UAE, Kuwait, Bahrain, and Qatar. Contrasting with the standard literature, our empirical strategy uses the wavelet coherence approach on the frequency domain, thought to complement the time series econometric procedures reported earlier on this topic. Supplied at the country level, associated evidence presents far-reaching policy recommendations whose applications may directly benefit environmental planning and bring high information value for the sake of sustainable energies in the Gulf region. [ABSTRACT FROM AUTHOR]

Most of the developing and emerging countries are focusing to increase economic growth, enhance the living standard of the people, and reduce income inequality. Increasing economic growth through the factors such as agriculture, energy use for production, and other related activities can harm the environment. Considering this situation, this study utilizes data from the Belt and Road Initiative countries for the period of 1999 and 2018 to explore the nexus between income inequality, agricultural value added, and carbon dioxide using two-step system GMM model. The findings of the study indicate that income inequality, economic growth, energy consumption, and agriculture significantly contribute to an increase in carbon emissions and a decrease in environmental quality. On the other hand, the findings also indicate that manufacturing and service industries significantly contribute to an improvement in environmental quality by reducing carbon emissions. The findings lend even more credence to the environmental Kuznets curve, but the results do not indicate that there is a strong relationship between income inequality and economic growth. The outcomes of this study have crucial policy implications for the sample countries to build environmental regulations. [ABSTRACT FROM AUTHOR]

The study examined the impact of renewable energy, non-renewable energy, remittances, and economic growth on environmental degradation from the perspective of carbon dioxide emissions (CO2) and ecological footprint for the top 50 remittance-receiving countries for 1991–2018. This study simulates the environmental future for attaining the targets of Sustainable Development Goal 7 (SDG7) using the latest datasets. This study is one of the few that empirically explores how various explanatory variables affect CO2 and ecological footprint. The study employed the pool mean group autoregressive distributive lag (PMG-ARDL), fully modified ordinary least squares (FMOLS), and dynamic ordinary least squares (DOLS) techniques for the analysis. In the long-run, non-renewable energy and economic growth have a positive impact, whereas renewable energy and remittances have a negative impact on CO2 and ecological footprint. The impact of non-renewable energy on CO2 and ecological footprint is more significant than renewable energy in both the short- and long-run. Most of the variables have a bidirectional causality among each other. This highlights the need for a paradigm shift towards renewable energy in the top recipients specifically for developing countries. [ABSTRACT FROM AUTHOR]

This study seeks to ascertain whether there is an unbalanced link between CO2 emissions, foreign direct investment, and economic growth in Malaysia over a 40-year timeframe between 1980 and 2019. We investigated the asymmetric relationship , using non-linear autoregressive distributed lag (NARDL) technique. The findings showed a noteworthy asymmetry between FDI, CO2 emissions, and GDP in Malaysia. The long-term and short-term effects of negative FDI on GDP are both equivalent to 0.028 and 0.021, respectively. This suggests that, compared to short-term fluctuations, long-term negative FDI adjustments have a considerably more negative impact on economic growth. The coefficient of positive (CO2+) and negative (CO2−) changes in economic growth is equal to 0.086 and − 0.152, respectively. It indicates that positive changes in CO2 emissions have stronger effects in the long run than negative shocks. Considering an asymmetric association between these two variables in the short and long term, Malaysian policymakers must comprehend the dynamic relationship between FDI, CO2 emissions, and GDP to plan appropriate economic and environmental policies that will support sustainable economic development and ensure a safer environment. [ABSTRACT FROM AUTHOR]

In this study, the effects of financial inclusion (FI), agricultural innovation (AI), trade (TR), and forest rent (FR) on carbon dioxide emissions (CO2), economic growth (Y), and ecological footprint (EFP) for Pakistan from 1970 to 2017 are examined using symmetric and asymmetric cointegration approaches. These links are investigated using linear and non-linear autoregressive distributive lag (NARDL) techniques. In contrast to the asymmetry results, the symmetric results revealed no cointegration among the variables over the long run. Moreover, asymmetry results from the Y-model indicated that a positive shock in AI significantly affects Y over the long run while raising it over the short term. Furthermore, CO2 rises in the wake of positive shocks like AI, Y, and FR but falls in the wake of adverse shocks. A negative shock to FI raises CO2 temporarily, whereas a negative shock to FR causes CO2 emissions to fall over time. According to the EFP-model, long-term EFP is decreased by both positive shocks to AI and adverse shocks to FR with one-period lags. On the other hand, positive shocks to FI and FR cause the short-term EFP to rise. In addition to a bidirectional causal relationship between Y, EFP, and FI, we found a one-way causative relationship between Y, FR, AI, CO2, and EFP. The FMOLS estimator also supports NARDL estimations. The key recommendations to help Pakistan keep its environment and economy are to enhance green mechanization in agriculture, allocate adequate research and development funds, and initiate integrated environmental and economic growth policies by relevant institutions. [ABSTRACT FROM AUTHOR]

FDI inflows remain an important source of economic growth and technology transfer for developing countries. However, the proponents of the pollution haven hypothesis (PHH) argue that FDI inflows may result in the production of polluted goods in poor economies. The empirical testing of PHH reveals conflicting outcomes on the subject. This study argues that foreign firms' choice of specific technologies and hence the validity of PHH can be determined by host countries' level of education. For developing economies having low levels of schooling, FDI inflows will accompany polluted technologies. Nonetheless, when education levels exceed certain thresholds, FDI inflows may reduce CO2 emissions. For our empirical investigation, we rely upon a large panel of 108 developing countries during 2000–2016. Our estimated outcomes, based on the panel cointegration method and panel vector error correction methods (P-VECM), confirm these moderating effects of human capital in the FDI–CO2 emissions nexus. The empirical results also confirm the presence of the environmental Kuznets curve (EKC) for developing countries. These results have important policy implications for the sample economies. [ABSTRACT FROM AUTHOR]