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We investigate the dynamic effect of external conflict risk on environmental transition by considering the impacts of eco-innovation, economic growth, and energy consumption in a panel comprising 26 European countries from 2011 to 2020. Using a non-parametric model represented by the panel QARDL, we find that in the short run, a 1% increase in external conflict risk statistically leads to a 0.25% and 0.13% increase in the likelihood of environmental transition for the median and extreme upper quantiles (50th and 95th percentiles), respectively. However, the same increase holds little importance when considering the lower quantile (5th percentile). The indicated effect substantially decreases in the long run, reaching zero across the different quantiles. We also note discrepancies in the impact of energy across various quantile levels. For instance, the effect of population is significant from the 5th to the 90th quintiles. Overall, our findings suggest that enhancing eco-innovation helps reduce environmental transition risk. The results are relevant to the development of environmental policies and provide valuable insights for energy officials, technology stakeholders, and policymakers in their attempts to strengthen resilience during an environmental transition. [ABSTRACT FROM AUTHOR]

In Canada, greenhouse gas (GHG) emissions continue to remain high despite the federal government's commitment to reduce GHG emissions. Environmental policy across Canadian provinces has largely lacked consistency with some provinces implementing targeted policy such as carbon taxes while others have strongly resisted the federal government's attempts to encourage such policy. This study examines the impact of environmental policy on GHG gas emissions across Canadian provinces with policy uniquely measured by public and business sector spending on environmental protection as well as notable province-specific policies. An extended STIRPAT model is specified with the inclusion of proxies for environmental policy using panel data from Canada's ten provinces from 1995 to 2019. The cointegration and the error correction modelling approaches are employed to estimate the non-stationary panel data. A pooled mean group estimation is applied to provide short run and long run coefficients. The findings indicate that although per capita GDP is the main driver of GHG emissions in Canada, environmental policy has a significant mitigating effect, as shown by the negative association between emissions and private and public sector spending on environmental protection in the long run. Furthermore, provinces with targeted policies, such as Ontario's coal phase-out and British Columbia's carbon tax, experienced significant emissions reductions. The theoretical implication is the successful addition of policy variables to the STIRPAT model, providing the model a new application for future research. [Display omitted] • Assess the impact of environmental protection policies on per capita greenhouse gas emissions in Canada. • Utilize public and private expenditures on environmental protection, along with provincial policies. • Extend the STIRPAT model to incorporate environmental protection policies in an empirical model. • Demonstrate a significant negative relationship between environmental protection policies and GHG emissions. • Offer insights with implications for global environmental sustainability efforts. [ABSTRACT FROM AUTHOR]

The earth is experiencing unprecedented global warming and this has an adverse impact on the health of the planet, people and economies. A major contributor to the degradation of planetary health is CO2 emissions that are contributed by the transportation sector. The brunt of the environmental degradation is experienced by developing countries, where the transportation sector is dependent on cheaper fossil-fuels. This study examines the causal interface between transportation infrastructure development, economic growth, institutional quality, and CO2 emissions in 79 developing countries over the period 2005 to 2022. A quantile-on-Quintile regression (QQR) and vector error-correction model (VECM) are deployed to study the causal relationships between the above-mentioned variables. The empirical findings show strong endogenous relationships between the variables in the short-run and long-run. The concerning trend is that, while the transportation sector and improvement in the institutions contribute positively to the economic growth of these countries, CO2 emissions (from the transportation sector) have a detrimental, and perhaps larger, impact on economic growth. A key insight from these findings is that there is a need to reduce CO2 emissions by ensuring greater use of renewable energy to power the transportation sector. A more environmentally-friendly transportation sector will be critical in enabling these countries to transition towards sustainable economic growth trajectories. [Display omitted] • Exploring the interface between institutional quality, transportation, economic growth and CO2. • The sample comprises developing countries from 2005 to 2022. • The study uncovers uni- and bidirectional nexus between these variables. [ABSTRACT FROM AUTHOR]

The sustainability of the blue economy (BE) may be impeded by the adverse consequences of human activities, such as greenhouse gas (GHG) emissions, unsustainable economic expansion, and engagement in environmentally harmful trading practices. Therefore, this study aims to determine the impact of GHG emissions, trade, and economic growth on the BE. To achieve this, we used a panel dataset of 25 selected countries surrounding the Indian Ocean, covering the period 2002–2019. As a process of estimation, we employed the Westerlund error correction model to detect cointegration. To determine the long-term relationship among the variables, we adopted the cross-sectional autoregressive distributed lag (CS-ARDL) approach, which revealed a significant outcome in the long run but an insignificant outcome in the short run. In response to this divergence, the panel corrected standard error (PCSE) model was applied to correct the autocorrelation problem. Subsequently, a two-step generalized methods of moment (GMM) test was conducted to check robustness. Based on the results of PCSE and GMM, this study reveals that trade has a negative effect on the BE, while GHG emissions and economic growth have a positive ascendance. From a policy standpoint, all governments must integrate ocean-based solutions into their national climate pledges to fulfill the objectives outlined in the Sustainable Development Goals (SDGs), particularly SDG 14 (Life Below Water). [ABSTRACT FROM AUTHOR]

Renewable energy plays an important role in reducing global carbon (CO 2) emission. This paper builds a RER (renewable energy consumption rate) index to represent the energy structure of a country and proposes a U-shaped RKC (renewable energy Kuznets Curve) hypothesis between RER and economic growth. We also examine the dynamic relationship between RER and the Environmental Kuznets Curve (EKC) hypothesis using two panel data sets of 17 major developing and developed countries as well as six geo-economic regions of the world during 1990–2014. Panel co-integration tests indicate that a long-run relationship exists among economic growth, RER and carbon emission. We employ the fully modified ordinary least squares (FMOLS) and the dynamic ordinary least squares (DOLS) techniques to estimate the co-integration coefficients of the panels and individual countries/regions respectively. The results verify both the EKC and RKC hypotheses, indicating that a 10% rise in RER would to a 1.6% carbon emission reduction. It is also found that the RKC turning points of individual countries and the entire samples in general take place before the turning points of the respective EKCs. It suggests that promoting renewable energy consumption to make RKC cross its turning point earlier can accelerate EKC to reach its turning point more quickly. This finding has important policy implications with respect to the development and utilization of renewable energy and environmental protection. The dynamic relationship between EKC and RKC. Image 1 • We examined the relationship between renewable energy and GDP. • A U-shaped curve exists between GDP and renewable energy consumption. • The turning points of RKCs take place earlier than that of the EKCs. • Promoting RKC arrive its turning point in advance can accelerate EKC to reach its turning point more quickly. [ABSTRACT FROM AUTHOR]

China's progress in energy efficiency has contributed significantly to the reduction in global energy intensity (EI), but the descending speed of per unit GDP energy consumption in China has been decreasing during recent years. The present study aims to investigate the core driving forces of EI from 2005 to 2016 in 289 Chinese cities based on Granger Casualty Test and regression analysis. For this purpose, the study employs panel data analysis with both fixed coefficient and time-varying coefficient which are suitable for examining the effects of influence factors on EI and their change trend. The Granger Casualty Test investigates that there supposed to be a bidirectional causality between air-pollutant emission and energy consumption in China. However, due to China's weak environmental regulations, the negative effect of emission on EI is not significant. Further, regression analysis shows that a percentage increase in electricity price decreases EI by 0.722% in long-term, but this adjustment takes time. Furthermore, analysis of short-term relationship reveals that optimizing energy structure may be the best way for China to reduce EI in short run. Finally, the time-varying coefficients of panel data model indicate that inhibitory effect of promoting electricity consumption on EI will keep improving with expansion of electricity use. Image 1095 • How direct and indirect influencing factors affect energy intensity is analyzed. • Rising energy price can reduce energy intensity of China only in the long run. • The inhibitory effect of promoting electricity consumption is constantly increasing. • China's environmental regulations are too weak to reduce energy intensity. [ABSTRACT FROM AUTHOR]

Previous studies have discussed theoretically the role of green finance in energy security, but empirical studies have yet to explore their relationship. In order to make up for this deficiency, we first measured the development level of green finance and the comprehensive score of energy security in China from 2000 to 2020. Then, we constructed a vector error correction model based on the cointegration relationship. The results show a stable cointegration relationship between the long-term variables, and the improvement of the development level of green finance is conducive to ensuring China's energy security. However, from the results of the short-term dynamic adjustment effect, the change in green finance development level has no significant impact on the change in energy security level because the role of green finance has a specific time lag. Further, through impulse response analysis, it is found that when the development level of green finance has a unit positive impact, energy security will produce a first negative and then positive response. The variance decomposition results show that the contribution of green finance to energy security first weakens and then gradually increases. To sum up, the long-term development of green finance will help stabilize China's energy security. Therefore, this study proposes strengthening supervision over green finance, developing "new energy + green finance", achieving positive interaction between green finance and transformational finance, and enabling green finance with digital technology. • Construct China's green finance evaluation index system. • Construct China's comprehensive energy security evaluation index system. • Measure the contribution of green finance to energy security. [ABSTRACT FROM AUTHOR]

Renewable energy development is one of the cleaner production paths for China's transformation of urbanization and economic development. Recognizing the nexus among them may help China to formulate a targeted policy for efficient and clean energy utilization, as well as for carbon reduction. Based on the panel data of 30 provinces and seven geographical regions over the period of 1997–2015, we apply a bootstrap panel causality test to explore the cause and effect of renewable energy consumption on urbanization and economic growth in China after a cross-sectional dependence test and a slope homogeneity test. We find that China's renewable energy consumption, urbanization and economic growth in one region might be influenced by the others. However, no causality is found in 80% of provinces and 71% of geographical regions for the nexus of renewable energy consumption and urbanization, and no causality is found in 53% of provinces and 43% of geographical regions for the nexus of renewable energy consumption and economic growth. Besides, significant geographical differences are found for the nexus. Therefore, the Chinese government should not only strengthen a unified renewable energy management system to advocate regional cooperation, but also give full play to the weak joint linkages and adopt differentiated renewable energy policies according to local conditions. The interactive mechanism and a virtuous cycle among the three indicators should be established in the medium and long term to help China's energy use towards a cleaner transition. Image 105 • Cause and effect of renewable energy consumption on urbanization and economic growth across Chinese provinces and regions are explored. • Significant differences are found by bootstrap panel Granger causality test. • No causality are found in most Chinese provinces and geographical regions. • Some differentiated development policies across China are recommended. [ABSTRACT FROM AUTHOR]

China has the largest electricity system in the world, which is undergoing a critical market reform. Based on the panel data in 2000 to 2016 of China, this paper tries to explain theinconsistency between electricity consumption and economic growth. For example, in 2015, GDP growth rate was close to 6.9% but with only 2.9% growth in electricity consumption. However, in 2018, a 6.6% growth in GDP required an 8.5% electricity growth. The results explain the reasons for inconsistency and identify the key factors. We find that the increase in inventory, fixed capital and industrial electricity consumption will narrow the gap when economy grows faster than electricity consumption, and widen the gap on the contrary. Heterogeneity exists among regions, the model and variables seem most convincing in explaining the situation in the western region, which is most similar to the full sample of China. Feedback effect is also observed between electricity consumption and economic growth in most parts of China by Granger test. The findings provides suggestions for the policy makers in making power planning, in an effort to avoid large power shortage or surplus. • Inventory, fixed capital and industrial electricity consumption will impact the deviation. • Impacts on deviation in western region are most similar to the full sample, and eastern region goes opposite. • Feedback effect is observed between electricity consumption and economic growth in most parts of China. [ABSTRACT FROM AUTHOR]

This study determines the dynamic linkages between globalization, financial development and carbon emissions in Asia Pacific Economic Cooperation (APEC) countries in the presence of energy intensity and economic growth under the framework of Environment Kuznets Curve (EKC). This study employs the panel data from 1990 to 2016, Westerlund cointegration technique to find long-run cointegration, and Continuously Updated Bias-Corrected (CUP-BC) and Continuously Updated Fully Modified (CUP-FM) methods to check the long-run elasticities between the variables. Empirical results indicate that globalization and financial development significantly reduce carbon emissions, but economic growth and energy intensity increase them. These results support the EKC hypothesis for APEC countries. The Dumitrescu and Hurlin causality analysis shows that globalization Granger causes CO 2 emissions. Globalization also causes financial development and energy intensity. A feedback effect exists between financial development and CO 2 emissions. Furthermore, financial development causes economic growth but similar is not true from opposite-side in Granger sense. Finally, this study presents important policy implications with respect to APEC countries. Image 1 • This study examines the effects of globalization and financial development on CO 2 emissions. • The data of APEC countries has been used. • Westerlund Cointegration approach used to find panel cointegration while CUP-FM and CUP-BC used to find long run relationships. • Globalization and financial development reduce the CO2 emissions both in long run and short run. • Policies to increase green energy and improved technology are recommended, among others. [ABSTRACT FROM AUTHOR]

This paper estimates the linkages among total Sulphur dioxide (SO 2) emissions, total GDP and energy efficiency using China's provincial panel data from 2002 to 2015. We investigate total emissions rather than per capita emissions or ambient concentrations since it is total emissions that the environment cares about. Energy efficiency is estimated using stochastic frontier analysis and decomposed into both persistent and transient efficiency. We then investigate the long-run dynamics among SO 2 emissions, economic growth, and energy efficiency by employing the panel-based error correction model and taking the effects of cyclical variations into account. Our analysis shows that GDP has a positive impact on total SO 2 emissions in the short run and gains in energy efficiency have a significant negative effect on emissions in the long run. By controlling the effects of the business cycle, the effects of GDP on emissions remain positive in both the short and long run. The cross-sectional analysis provides similar insights. We argue that economic growth itself is an emission generator. Therefore, the government needs to establish a long-run strategy to curb emissions by improving energy efficiency. Image 1029 • We estimate the linkages among sulphur dioxide emissions, GDP and energy efficiency. • Energy efficiency is estimated by SFA and decomposed into persistent and transient efficiency. • We employ the panel-based error correction model with cyclical variations and structural break. • GDP has a positive impact on emissions in both the short and long run. • Gains in energy efficiency affects emissions negatively in the long run. [ABSTRACT FROM AUTHOR]

Balancing economic growth and a sustainable environment has been a concern for governments. However, it has been observed that sustainable development is related to economic factors, the institutional environment, and the effectiveness of environmental regulatory policies. This study empirically investigates the relationship between financial development, strict environmental regulations, corruption, foreign direct investment, trade openness, renewable energy consumption, and ecological footprint. We used annual panel data of Asia-Pacific Economic Cooperation countries from 1994 to 2018 to fill the research gap. The present study follows a perspective that produces reliable and robust results using Fully Modified Ordinary Least Squares and panel fisher causality analysis. The long-run flexibility estimates calculated with the Fully Modified Ordinary Least Squares approach explain the inverted U relationship between financial development and ecological footprint. Long-run elasticity estimates suggest that strict environmental policies, renewable energy consumption, financial development and corruption, and the interaction of financial development and strict environmental policies reduce the ecological footprint. In addition, foreign direct investment and trade openness are found to increase the ecological footprint. This confirms the pollution haven hypothesis in Asia-Pacific Economic Cooperation countries. According to the causality test results, bidirectional causality relationships were discovered between ecological footprint and financial development, strict environmental policies, corruption, renewable energy sources, foreign direct investment and trade openness. We suggest that institutional financial framework and financial development for APEC countries will reduce environmental degradation in the long run, and sustainable development can be achieved through the institutional environment and the effectiveness of environmental regulatory policies. [Display omitted] • Empirical evidence of a U-inverted behaviour between financial development and the ecological footprint in APEC countries. • On panel data sets of the APEC countries from 1994 to 2018. • Strict environmental policies and renewable energy consumption reduce the ecological footprint. • The damper effect between corruption and strict environmental policies on financial development reduces ecological footprint. • Used second-generation panel estimation methods. [ABSTRACT FROM AUTHOR]

Information and Communication Technology (ICT), especially internet-use and technological innovation are argued to have brought significant structural changes that drive economic growth. The current study verifies this argument using data for 16 emerging economies from 2000 to 2018. In this analysis, we have investigated the effects of ICT, innovation, electricity-consumption and renewable power generation, on the economic growth of the emerging economies. Using Instrumental-Variable GMM and fixed-effects regression with Driscoll-Kraay standard-errors, it is found that, ICT not only increases economic growth monotonically, but also increases the effectiveness of financial development on growth. However, ICT is also found to accentuate the negative effects of trade on economic growth. In order to account for the heterogeneities among these economies, both conditional and unconditional panel quantile estimators have been used for an income-level analysis. This shows that internet-use increases growth significantly in the lower and middle-income quantiles; innovation is found to have significant negative effects on growth, except for the highest income-quantile, while the positive growth-effects of electricity-consumption are confirmed across all quantiles. These findings suggest that the emerging economies should increase internet-connectivity to induce network-effect and to improve their capital markets, while also augmenting renewable electricity generation for environmentally-sustainable economic growth. • Internet-use increases economic growth monotonically for the overall sample of emerging economies. • Internet-use increases growth significantly in the lower and middle-income quantiles. • Innovation is found to have significant negative effects on economic growth, except for the highest income-quantile. • Electricity consumption significantly increases growth, but renewable power generation have insignificant effects. • The interaction of internet-use with trade and financial development are significantly negative and positive respectively. [ABSTRACT FROM AUTHOR]

The paper investigates how climate changes and socioeconomic transformations affected grassland productivity from 2000 to 2017 in counties in Inner Mongolia of China. The grassland productivity and climatic change variables included 162 readings (9 periods in the growing season × 18 years), while ten socioeconomic variables contained 18 yearly readings. The mismatch between the environmental observations and socioeconomic data compounds quantitative analysis of causal relations between them. We applied several time-series processing methods to generate five datasets. We fit them with conventional, dependent-lagged, and dynamic-lagged panel regression models to investigate which combinations augment causal relationships between grassland productivity, climate, and socioeconomic changes. The results confirmed that the conventional model with the original data failed to reveal causal relationships between these factors. The panel regression models with the original data tended to intensify the causal effects of climate factors on grassland productivity. The models with the transformed datasets disclosed more socioeconomic variables showing causal relationships with grassland productivity. The dependent-lagged model with the empirical mode decomposition transformed data produced the highest R-squared value and lowest prediction error. GDP, state fixed asset investment, highway construction, grain plantation, and livestock density were primary factors affecting grassland productivity. In brief, the integration of time-series data mining and time-lagged panel analysis effectively unveiled the causes of grassland deterioration under climate and socioeconomic changes. [Display omitted] • Augment causality hidden in env-socio-economic systems with data assimilation. • Assimilate temporal environmental and socioeconomic data into compatible time-series. • Experiment with four groups of computational data mining methods on data assimilation. • Compare combinations of data assimilation methods and lagged panel regression models. [ABSTRACT FROM AUTHOR]

The carbon intensity of human well-being (CIWB) is an effective indicator for measuring the progress of the UN Sustainable Development Goals. Compared with production-based accounting, consumption-based CIWB is more useful for the dual tasks of improving cost-effectiveness and increasing equity. Therefore, this study for the first time estimated consumption-based CIWB in 176 countries from 1990 to 2015 by a multi-region input-output model and explored its spatiotemporal patterns. A panel regression technique was adopted to test the impact of the potential socio-economic determinants, with consideration given to the income levels of global countries. We found that global consumption-based CIWB improved annually between 1990 and 2015, and the gap between countries has also gradually decreased since 1995. Apparent differences in consumption-based CIWB and its changes were observed in the four income groups. The lower the income, the more pronounced the trend of consumption-based CIWB reductions was. Economic growth, energy intensity, and exports of goods and services all have a negative impact on the consumption-based CIWB, i.e., elevated CIWB values, while population density, urbanization, renewable energy consumption, and imports of goods and services all lower CIWB values. The effect of socioeconomic factors on consumption-based CIWB also presented different changes depending on income levels. The results of the study provide an important reference for improving the environment while enhancing human well-being. • A multi-region input-output model was used to calculate consumption-based CIWB. • The global consumption-based CIWB decreased from 1990 to 2015, and the differences between countries have narrowed. • Significant differences in consumption-based CIWB values and their changes were observed concerning four income groups. • We explored the heterogeneity of the effects of socioeconomic factors on consumption-based CIWB at different income levels. [ABSTRACT FROM AUTHOR]

It has been proven that mankind has achieved economic prosperity at a huge environmental cost. However, if the ecological footprint cannot be controlled at the same time, economic growth will not be maintained. This work takes 166 countries (divided into high-income countries, upper-middle-income countries, lower-middle-income countries, and low-income countries) as examples to analyze the nexus between renewable energy consumption, population aging, and decoupling economic growth from ecological footprint. This study uses the second-generation econometric methodological framework of panel data to effectively solve the problems of transnational heterogeneity and cross-sectional dependence. The results indicate that the decoupling between economic growth and ecological footprint showed an improvement trend from 1990 to 2015, and finally maintained a weak decoupling. Among them, upper-middle income countries improved the earliest (2003), and low-income countries improved the latest (2009). The evidence of the inverted U-shaped nexus between economic growth and ecological footprint shows the validity of the Ecological Kuznets Curve globally. However, this nexus is not significant in low-income countries. Importantly, renewable energy consumption can reduce the ecological footprint globally in the long run. Furthermore, this reduce effect is stronger in low income and lower-middle income countries than in high-income and upper-middle-income countries. Population aging, financial development and trade openness all contribute to the reduction of the ecological footprint. Among them, the effect of population aging is more significant than financial development and trade openness. Based on the results, comprehensive policy implications were put forward so that these countries can achieve the decoupling economic growth from ecological footprint. [Display omitted] • Cross-sectional dependence was considered using second-generation econometric techniques. • The decoupling of economic growth from the ecological footprint is ultimately maintained at weak decoupling. • Renewable energy consumption has a heterogeneous driving effect on decoupling economic growth from ecological footprint in different income groups. • The inhibitory effect of aging on the ecological footprint is greatest in the high-income group. [ABSTRACT FROM AUTHOR]

This paper examines the nexus between renewable energy consumption (REC) and Gross Domestic Product (GDP) in G7 countries. To this end, we analyse data from 1980 to 2020 employing Toda and Yamamoto (1995) time causality test, Lemmens et al. (2008) frequency causality test and Hatemi-J's (2012) asymmetric causality approach. The findings differ across countries and are as follows. The conservative hypothesis is validated for the US and Canada. Specifically, we find significant and positive causal effect from GDP to REC in the long-term horizons (periods greater than 15 years for the US and 7 years for Canada). The growth hypothesis is confirmed for Germany. Precisely, significant and positive causal impact is shown from REC to GDP in the long-run horizons (periods longer than 7 years). The neutrality hypothesis is supported for France, the UK, Italy and Japan as there is no significant causal link at any time horizon. This is likely because the clean energy consumption does not reach a threshold beyond which it will start to have considerable interaction with economic growth. This study provides policymakers a better understanding of the REC-economic growth nexus to formulate appropriate policies. • We examine the nexus between renewable energy consumption and economic growth in G7 countries. • We use Toda and Yamamoto (1995) and Lemmens et al. (2008) tests and Hatemi-J's (2012) asymmetric causality approach. • For the US and Canada, significant and positive causal effect is shown from GDP to REC in the long-term horizons. • For Germany, significant and positive causal impact is displayed from REC to GDP in the long-run horizons. • For France, the UK, Italy and Japan, no significant causal link is found between REC and economic growth. [ABSTRACT FROM AUTHOR]

This paper aims to examine the causal relations between economic growth, electricity consumption, and urbanization indicators. Heterogeneous panel data techniques are performed to help shed light on the importance of the heterogeneity among three economic regions within China from 2000 to 2017. Our results show that the three indicators are all stationary and cointegrated after the first difference. Heterogeneity of the Granger causality is found between these three variables varies across the eastern, central, and western economic regions in China. In the long run, the eastern region presents a similar trend as the national level that long-run Granger causality of the three variables is found. Conversely, there is a unidirectional long-run causal relationship from economic growth to electricity consumption in the central region, while there is a bi-directional long-run causal relationship between economic growth and electricity consumption in the western region in China. Our empirical findings highlight the "urbanization ladder" effect which implies that as development, urbanization factor in the eastern region may play a promotion role in the tri-variate system when the urbanization reaches a higher level, while it may lack the influence in the central and western regions of China. From a regional perspective, it is further indicated that the improvement of urbanization can be practical measures in the central and western parts of China in the long run. • Economic growth, electricity consumption, and urbanization are cointegrated in eastern, central, and western China. • Granger causalities between the three variables vary across the three economic regions in China. • Urbanization does not have a causal effect on economic growth & electricity consumption in central-western China. • It is essential to accelerate the urbanization process in the central-western areas in China in the long run. [ABSTRACT FROM AUTHOR]

Economic growth, energy consumption, and urbanization are mutually influenced, therefore, forecasting economic growth, energy consumption and urbanization in China has always been important as it could help government to improve energy policies and plans. To this end, two novel grey multivariable models, SRMGM(1, M) and BRMGM(1, m), are designed in this paper. Compared with the MGM(1, M) model, the SRMGM(1, M) model can optimize the background of the traditional model according to the Simpson formula, and the BRMGM(1, m) model optimizes the background value according to a Boolean formula. The reconstruction of background value can reduce the prediction error of MGM(1, M) model. Furthermore, rolling prediction is added to these two new models based on the priority principle of new information. In order to validate their efficacy and accuracy, the two proposed models are employed to reproduce and predict economic growth, energy consumption, and urbanization compared with MGM(1, m) model and three linear regression models. FDs of our models, in both fitted and predicted stages are all over 97%, and the ADFs are all below 5%. The results show that our new models achieves higher fitted and predicted accuracy than MGM(1,m) model and the non-grey models. Eventually, the new models will be used to forecast economic growth, energy consumption, and urbanization from 2020 to 2025, and the forecast results provide a solid basis for economic growth policies and energy consumption plans. [Display omitted] • Two novel grey models are designed and theirs the validity are proved in the paper. • The background value is improved by Simpson formula and Boolean formula. • Two novel models perform best than the non-grey models. • The results improve economic growth policies and energy consumption plans. [ABSTRACT FROM AUTHOR]

China is the first major economy to show a recovery after a slowdown induced by the COVID-19 pandemic. This work aims to explore what the China's economic recovery after the COVID-19 pandemic means for the economic growth and energy consumption of the other countries using the global VAR quarterly data. In the long term, spillover effects of China's economic growth have the most obvious impact on upper-middle-income countries' economic growth (0.17%), followed by the economic growth of lower-middle-income countries (0.16%) and high-income countries (0.15%). However, the spillover effect of China's economic growth has the most significant impact on energy consumption in high-income countries (0.11%–0.45%), followed by energy consumption in upper-middle-income countries (0.08%–0.33%) and in lower-middle-income countries (−0.02%–0.05%). Our results indicate upper-middle-income countries will benefit the most from China's economic recovery post-COVID-19, followed by lower-middle-income countries and high-income countries. The spillover effect of China's economic recovery post-COVID-19 brings the most obvious impact on the increase in energy consumption in high-income countries, followed by middle-income countries. It also should be noted that the spillover effect of China's economic growth does not necessarily lead to an increase in energy consumption lower-middle-income countries. Generally, the spillover effect of China's economic recovery on other countries' economic growth is much more than other countries' energy consumption. [Display omitted] • China is the first major economy to show a recovery after the COVID-19 pandemic. • Investigating China's economic spillover effects on other countries' economy &energy. • China's economic recovery lead to all other countries' economic growth. • China's economic recovery does not lead to all other countries' energy consumption. • Spillover effect of China economy on economic growth is far greater on energy consumption. [ABSTRACT FROM AUTHOR]

Decoupling the trends of energy-related carbon emissions from economic growth is an essential precondition and condition for cost-effective climate stabilization. Using an extended Kaya identity and the Tapio decoupling definitions, this study explored the role and magnitude of drivers associated with carbon emissions and economic growth decoupling across 134 countries. The retrospective (1995–2015) decomposition analysis was complemented by exploring the future decoupling projections using assumptions of the Shared Socio-economic Pathways (SSP) framework. The results indicate that less mature developing economies are carbonizing their energy systems at faster rates (about 1–4%/year) compared to developed economies. While emerging developing economies are progressively transitioning towards weak decoupling. Overall the deterioration of structural and intensity technology drivers, including conversion efficiency, emission factor, and fossil fuel mix, are the major pinch points to achieving absolute decoupling among developing economies. The prospective analysis of the SSP assumptions also indicate that - developing economies exhibit very minimal signs of decoupling and decarbonization relative to developed economies. The study provides instructive insights about the urgency of addressing global decarbonization, especially among developing economies. • Compared the technology and scale driver of CO 2 -GDP decoupling across income class. • Downscaled the projection of CO 2 -GDP decoupling using assumptions of mitigation. • Developing economies exhibit minimal evidence of strong decoupling. • Structural energy drivers inhibit strong decoupling among developing economies. [ABSTRACT FROM AUTHOR]

We employ a non-parametric modelling technique to examine the time-varying impact of renewable and non-renewable energy consumption on economic growth. The specific nonparametric method that we employ is the local linear dummy variable estimation (LLDVE) method, which we apply to OECD and non-OECD panels for the period 1990 to 2015. While previous studies employing parametric models have recognised the existence of non-linearities and instability in the relationship between renewable (and non-renewable) energy consumption and economic growth, the LLDVE method has the advantage that it does not make any assumptions about functional form and, hence, is better able to approximate the non-linear relationship. Our estimates suggest that non-renewable energy consumption exerts a positive and significant impact on economic growth across OECD nations with the coefficient function exhibiting an upward trajectory over time. The impact of renewable energy consumption on economic growth, however, is statistically indistinguishable from zero in these countries for most of the study period. Both renewable and non-renewable energy consumption promote economic growth in non-OECD countries, suggesting that developing countries may play an important role in the transition process to renewables despite constraints in technical progress. [ABSTRACT FROM AUTHOR]

Threats posed by global climate change have heightened the urgency for economies to transition to sustainability. However, quantitative metrics that measure sustainability status remain under development, hampered in part by the difficulty of identifying clear relationships between economic growth and sustainability. The Environmental Kuznets Curve hypothesis provides a framework for describing sustainability status relative to socioeconomic development. In this study, the Environmental Kuznets Curve hypothesis was adopted to investigate statistical relationships between the carbon intensity of human well-being (as an indicator of sustainability) and economic development in eight economic zones of China during 1997–2015. The results provide new evidence that seven of eight Chinese economic zones began advances to sustainability (defined here as downward turning points marked by inverted "N" shapes in the Environmental Kuznets Curve) between 2012 and 2015. The lone exception was the Northwestern economic zone, in which an approach to sustainability had not yet occurred by 2015. This study thus supports the contention that environmental policies and technologies have contributed to improving sustainability in terms of carbon intensity. The results suggest two strategic options for further increasing sustainability in China: 1) "first help the weakest"; and 2) "first help the latest to sustainability". • Advance to sustainability defined in terms of carbon intensity of human well-being. • Almost all economic zones in China began advances to sustainability around 2013. • Only the Northwestern economic zone had yet to reach a turning point by 2015. • Assessment shows progress toward international obligations and national objectives. • Both environmental policies and technological advances have contributed. [ABSTRACT FROM AUTHOR]

Environmental degradation as a consequence of military activities largely remains a neglected subject, especially in South Asia. To fill this gap, we have investigated the impact of armed conflicts and militarization on the environmental dilapidation of South Asian countries from 1984 to 2019. A second generational unit root test has been applied to check the problem of cross-sectional dependency. Westerlund panel cointegration method is used to analyze the cointegration between selected variables. Long-run and short-run estimates have been calculated using the panel autoregressive distributed lag (ARDL) method. Besides, the Granger Causality test is employed and results indicate the causality runs from armed conflict and militarization to ecological footprint. Empirical estimates also confirm that the military expenditures, internal conflict as well as external conflict have a positive impact on ecological footprint and these results are highly significant both in the long run and short run. Our study also confirms the presence of the Environmental Kuznets Curve in South Asia. South Asia is marred by the aggressive posturing bitterness as witnessed by the sour relationship that exists between Pakistan and India, the two strongest nations in the region. This animosity left them with consistent and incremental growth in defense expenditure. To achieve sustainable development in South Asia it is imperative to initiate peace talks and to impose necessary restrictions on hazardous military operations contaminating the environment. [ABSTRACT FROM AUTHOR]

A boom in renewable energy consumption as a percentage of final energy consumption (REC) has a significant impact on cleaner production and environmental sustainability. However, studies on REC as for an individual country-case and panel case approach for top emitters are rare. Against this backdrop, this study investigates the long-run drivers of REC by using a time series data from 1990 to 2015. The FMOLS-grouped results indicate that economic growth and trade openness increase REC whereas population growth has a negative but significant impact on REC. To check for causal links, the innovating accounting approach using variance decomposition analysis is applied. The results show that there is a unidirectional causality running from economic growth, trade openness, and population growth to REC. Further, the predictive accuracy of the FMOLS based econometric output and the bi-directional long short-term memory (Bi-LSTM) is analyzed. The Bi-LSTM formulated algorithm outperformed the econometric output. The Bi-LSTM is utilized to forecast REC to the year 2030. The output from the Bi-LSTM shows that China, the US, India, the Russian Federation's, and Japan's REC will hit ∼11.3395, ∼11.1245, ∼34.6969, ∼2.9097, and ∼7.4859, respectively. The US and Japan's REC levels will increase while that of China, India, and Russia Federation will decrease. As a policy implication, new policy directives for China, India, and the Russian Federation are required to boost REC levels. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze the relationship among iron and steel industries, air pollution and economic growth in China. Using monthly time series from 2000 to 2017, we adopt a Long Short Term Memory (LSTM) approach. The empirical results show that the relationship between economic growth and steel production is very strong in the first stage. Furthermore, in our model, we can see that the reduction of polluting emissions is linked to the principle of sustainable development. In particular, this phenomenon lies in the economic growth model responsible for the future generation. [ABSTRACT FROM AUTHOR]

Previous studies have considered the effect of financial development on carbon emissions; however, few studies have explored the role of green finance in carbon mitigation. To bridge this gap, the current study constructs a green finance development index based on four indicators: green credit, green securities, green insurance, and green investment. A vector error correction model is used to analyze relationships between the development level of green finance, non-fossil energy consumption, and carbon intensity using data from 2000 to 2018. We find that China's green finance industry developed rapidly, and improvements in the green finance development index, as well as the increasing use of non-fossil energy, contributed to a reduction in carbon intensity. Simultaneously, an increase in carbon intensity inhibited the expansion of non-fossil energy use, impeded the investment flow to green projects, and ultimately led to a deterioration of green finance development. In addition, non-fossil energy consumption in China was primarily influenced by green finance and carbon intensity, with clear policy-driven effects. However, the impacts of green finance policies continually fell short and lacked continuity. This study proposes ways in which to improve the effect of green finance policy implementation, expand the consumption of non-fossil energy, and develop a carbon trading market. • The green finance–new energy use–carbon intensity nexus is explored for China. • A vector error correction model is employed. • A green finance development index is constructed based on four green indicators. • Green finance and new energy use are found to reduce carbon intensity. • Carbon intensity increases are found to inhibit green finance and new energy use. [ABSTRACT FROM AUTHOR]

This study evaluates the potential impact of promoting non-fossil fuel energy on India's economic growth in a regime based non-linear asymmetric framework. The empirical outcomes affirm regime-shift and asymmetric cointegrating links of the non-fossil fuel energy usage represented by combustible renewables & waste (CREW) and alternative & nuclear energy (ANEN) with the gross domestic product (GDP). The study establishes the existence of threshold cointegration between CREW and GDP. The causal links between CREW and GDP are regime variant and asymmetric, whereas the dynamics between ANEN and GDP are proven to be asymmetric and regime invariant. CREW and GDP supports a feedback hypothesis in a normal regime and a conservation hypothesis in a rare regime. The asymmetric causality between CREW and GDP validates an inverse feedback hypothesis and a negative growth hypothesis. A negative growth hypothesis is also ascertained between ANEN and GDP. The empirical findings convey meaningful insights for government and policymakers. • Examines the link between non-fossil fuel energy and economic activity in India. • Regime shifts, threshold and asymmetric cointegration found. • Feedback hypothesis in a normal regime is demonstrated in long run. • Positive change in combustible renewables & waste causes economic growth adversely. • Negative changes in alternative & nuclear energy drives positive economic growth. [ABSTRACT FROM AUTHOR]

As one of the three major fields of building energy consumption, public buildings (PBs)are under pressure regarding energy saving and emission reductions, with PB energy consumption accounting for 38% of the total consumption. Thus, CO 2 emissions released in PBs have become crucial for China in achieving its emission mitigation goal in the "Post Paris" period. This paper is the first to develop a support vector machine (SVM) method to predict and diagnose PB energy consumption based on 11 input parameters, including historical energy consumption data, climatic factors and time-cycle factors. Months with air-conditioning energy consumption in Wuhan were considered the study period, and we used June and July data for model prediction training, August data as the test set, and September data to diagnose the air conditioner energy consumption anomaly. The results show that air conditioning energy consumption was abnormal for four days in September. Relevant policies and suggestions are proposed based on the causal analysis. This research is expected to provide theoretical guidance and a practical data reference for building operations management. [ABSTRACT FROM AUTHOR]

At present, income distribution and environmental pollution are serious issues faced by the Belt and Road Initiative (BRI) countries, and exploring the impact of income inequality on energy efficiency is meaningful for the sustainability of BRI countries. Using the panel data of 33 BRI countries from 2000 to 2016, we first evaluate the energy efficiency of the countries by dynamic DEA model, and then adopt the Tobit regression model to investigate the nonlinear effect of income inequality on energy efficiency. The results suggest that, first, during 2000–2016, the overall energy efficiency of 33 BRI countries is relatively low, falling to 0.38, while the overall energy efficiency of high-income BRI countries is much higher than that of the middle-and low-income BRI countries. Second, the average energy efficiency of the BRI countries has declined since year 2013. Third, there is an inverted "U"-type effect of income inequality on energy efficiency in the whole sample, but the impact of income inequality on energy efficiency is heterogeneous for countries at different income levels. Specifically, in high-income BRI countries, income inequality shows a "U"-type effect on energy efficiency, while in middle-and low-income BRI countries, the relationship between income inequality and energy efficiency is an inverted "U"-type. Moreover, economic growth positively impacts the energy efficiency, while industrialization and energy structure negatively influence the energy efficiency. • A panel data of 33 BRI countries from 2000 to 2016 are used. • Dynamic DEA and panel Tobit regression model are adopted for analysis. • The nonlinear effect of income inequality on energy efficiency is investigated. • The overall energy efficiency of 33 BRI countries is relatively low. • The impact of income inequality on energy efficiency rely on national income levels. [ABSTRACT FROM AUTHOR]

The present study examines the presence of Environmental Kuznets Curve (EKC) in Malaysia by investigating impact of globalization (including overall, social, economic and political) on ecological footprint in the Malaysian economy using quarterly data from 1970 to 2018. This research utilizes the Quantile Autoregressive Distributed Lag (QARDL) method. This approach is useful as it depicts the causality patterns through various quantiles of the globalization and environmental degradation by providing more comprehensive explanations of the over-all dependence among the aforementioned variables almost ignored by the traditional approach (for instance ARDL and OLS). The outcomes of QARDL showed that the error correction coefficient is significant with the anticipated negative sign for all quantiles. This outcome provides evidence on the presence of considerable return to the long-run equilibrium association between the factors of interest and environmental degradation. Overall, the results recommended that overall globalization and economic globalization enhance the level of environmental degradation in the long run, however, political and social globalization help to reduce the level of environmental degradation in the long term. Moreover, the results of QARDL also confirmed the existence of inverted U-Shape curve in the Malaysian economy. In the shorter-run period, this study found a significant negative impact of overall globalization and political globalization on environmental degradation. The results recommended that the Malaysian government and policymakers need to give more attention to social and political globalization to achieve the goals of sustainable environment in the long-run equilibrium. [ABSTRACT FROM AUTHOR]

The disparities in development levels of countries in Africa necessitate correspondingly sensitive categorization approaches because effective renewable energy-related (RER) decisions, policy-making, and subsequent implementation hinges on workable categorization indices. However, studies on sensitive categorization approaches for energy-environment-economy (3E) interdependencies for Africa is rare. This study uses a sensitive characteristic-driven approach to explore the interdependencies in 3E indicators for carbon dioxide (CO 2) emissions, renewable energy consumption (REC), fossil fuel energy consumption, gross domestic product (GDP), population, and gross fixed capital formation in 39 African countries. Further, we forecast the dollar values of policy innovations necessary to facilitate the transition to 100% renewable energies for 2030. Using balanced data spanning 2000–2014, the empirical results from the panel vector error-correction model show long-run Granger causality in CO 2 emissions, REC and GDP models for Africa, but no evidence of such relationship was found four sub-panels. The results depict varied individual unidirectional and bidirectional causalities among the variables in each panel. Evidence from variance decomposition analysis show that ∼93% of innovations required to achieve renewable energy-led Africa must happen in REC. Results from the high precision own-data-driven forecast puts total energy demand in Africa at ∼25QBtu in 2030 with ∼40% from renewables. Estimates of the dollar value of innovations depict that it would cost Africa ∼ US$3367.2 billion [in 2030 only] to transition to 100% renewables. We find RER investment (RERIs), in billion US$, ranging from 2.69 to 1274.12 for seven sub-panels. Yet, the panel of Moderate Lower Middle-Income Economies need not to make further investments because their existing REIRs could be enough to help the region reach 100% renewables by 2030. The findings herein imply that RER policies in Africa must be intensified to achieve 100% renewable energy target. A chord showing short-run individual unidirectional causalities running from various independent variables to renewable energy consumption (REC) for Africa panel. FFEC, GDP, POT, GFCF, and CO 2 represent fossil fuel energy consumption, gross domestic product, total population, gross fixed capital formations, and carbon dioxide emissions, respectively. The length and area of REC indicate the fraction of the sum of Chi-square statistics [see Table S2] derived from utilizing the Wald Test to test for the presence of short-run causalities (SRCs) in the REC model relative to SRCs identified for all models in the Africa panel. All five independent variables individually Granger cause REC but the magnitude [based on the Chi-square statistics] of the causality ranked in ascending order are CO 2 , GFCF, FFEC, POT, and GDP. Image 1 • Energy-environment-economy interdependencies are explored for panels of sensitively grouped African countries. • We find no long-run relationship in CO 2 and GDP models for four panels. • Renewable energy contributes ∼40% of the ∼25QBtu total energy demand in 2030. • Energy investments of ∼US$3367.2 billion is required to achieve 100% renewables in 2030 for Africa. • The findings imply intensifying current renewable energy policies. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the validity of Environmental Kuznets Curve hypothesis for ecological footprint with the role of renewable energy use, non-renewable energy use and trade openness in 24 Organisation for Economic Co-operation and Development countries. For this purpose, we investigate the period from 1980 to 2014 using with second generation panel data methodologies which allow to cross-sectional dependence among countries. The group-mean results show that the inverted U-shaped Environmental Kuznets Curve hypothesis does not hold in Organisation for Economic Co-operation and Development countries because we found the U-shaped relationship between economic growth and ecological footprint. In addition, it is concluded that increasing renewable energy consumption reduces ecological footprint and increasing non-renewable energy consumption increases environmental degradation. Image 10447 • We examine the validity of Environmental Kuznets Curve hypothesis for ecological footprint. • Renewable and non-renewable energy use and trade openness are explanatory variables. • Study is done for 24 OECD countries from 1980 to 2014. • Results show that the EKC hypothesis does not hold. • Renewable energy consumption reduces ecological footprint. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to explore the impact of institutional quality on growth-emissions nexus in a panel of three East Asian countries over the period from 1990 to 2016. We also incorporated energy consumption and trade openness as important indicators in the model to avoid variable bias. The results of unit root tests show that the variables are stationary at first difference. The panel cointegration test confirmed that all the variables are cointegrated. We employed Fully Modified Ordinary Least Squares and Dynamic Ordinary Least Squares methods to estimate the long-run effects of explanatory variables on economic growth. The main findings are: (i) a positive significant interaction variable between carbon emission and institutional quality indicates that efficient and impartial domestic institutions are very important to increase economic growth and decrease carbon emissions, simultaneously. (ii) Institutional quality, energy use and trade openness stimulate economic growth. (iii) The VECM granger causality test results show that there is a one-way causality runs from institutional quality to economic growth, carbon emission and energy consumption, from trade openness to carbon emissions in both short-run and long-run, from energy use to trade openness, from energy use to carbon emission in both short-run and long-run. Moreover, feedback effect is present between economic growth and carbon emission, and between economic growth and energy use in both short-run and long-run. It is therefore, necessary to regulate and strengthen the role and effectiveness of local institutions with the aim of lowering carbon emissions in the course of economic development. Image 1 • Impartial and effective domestic institutions are very important to reduce carbon emissions in the course of economic growth. • Energy consumption and trade openness do contribute to enhance economic growth. • Feedback effect is present between economic growth, carbon emissions and energy consumption in both short run and long run. [ABSTRACT FROM AUTHOR]

Pursuing a responsible and sustainable development, the United Nations urged to decouple economic growth from environmental impacts. Several European Union (EU) policies have been implemented towards such goal. Although multiple authors have evaluated the decoupling of the economic growth from the resource use or environmental concerns, the environmental assessment mostly focused on pressures rather than impacts, and used single indicators assumed to be a proxy of the overall effects on the environment. Furthermore, no studies were found using a process-based life cycle approach to quantify the environmental impacts of consumption. To solve such research gap, this paper assesses the decoupling in the EU focusing on potential environmental impacts, complementing a production-based approach with two options for accounting for the impacts of consumption. The aim of this paper is to evaluate the decoupling of the economic growth (in terms of Gross Domestic Product) from the environmental impacts due to EU-28 consumption, assessed by means of life cycle assessment (LCA). The decoupling is then assessed in impact terms rather than limited to pressures by using the Environmental Footprint (EF2017) indicators, which allows assessing 16 different impacts. The Consumption Footprint indicator quantified the environmental impacts of EU apparent consumption, including the territorial impacts (Domestic Footprint) and the embodied impacts in both imports and exports (Trade Footprint). The inventory of pressures for the trade component is compiled either with a bottom-up approach (process-based LCA of representative traded goods) or a top-down approach (input-output-based LCA). Methodological aspects influencing the decoupling assessment and the resulting outputs are presented and discussed. According to the results, the environmental impacts of EU-28 consumption showed decoupling during the last decades (2005–2014), between relative to absolute decoupling depending on the inventory modeling approach taken. Some countries showed higher decoupling levels than others displaying a heterogeneous map of EU-28 decoupling, which was led by acidification, particulate matter, land use and eutrophication impacts. Notwithstanding current limitations, the assessment of decoupling using consumption-based environmental indicators is very promising for supporting policy-making towards addressing the actual impacts driven by the EU production and consumption system. • Comprehensive assessment of the decoupling of environmental impacts of EU-28 consumption from GDP. • A life cycle perspective is taken for the environmental impact modeling. • Decoupling assessment need further refinements to be used for policy support. • Top-down and bottom-up approaches indicated from relative to absolute decoupling. • Decoupling of environmental impacts from human development index is also evaluated. [ABSTRACT FROM AUTHOR]