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Increased residential energy consumption and reduced income caused by the lockdown measures invoked to combat the COVID-19 pandemic have deepened energy poverty, particularly in vulnerable communities. In this context, the pathway through which COVID-19 impacts energy poverty is constructed, and six relief measures are proposed: consistent financing of energy suppliers and consumers, developing various forms of socio-economic aids, leveraging fiscal stimuli to promote renewable energy transition, identifying vulnerable populations to improve policy effectiveness, designing equitable resource allocation mechanisms, and rethinking socio-economic transition in the post-pandemic era. [ABSTRACT FROM AUTHOR]

Green finance is an effective policy instrument in mitigating climate change, but to date little is known about its impact on carbon dioxide (CO 2) emissions. This study extends the literature on the relationship between green finance and CO 2 emissions while taking trade openness and economic development into consideration to comprehensively explore the conservation/feedback hypothesis using the Autoregressive-Distributed Lag–Error Correction Model (ARDL–ECM) on data collected from 2000 to 2019. By constructing a green finance index comprising green credit, green securities, green insurance, and green investment, results include the following. (1) Support was found for the conservation hypothesis running from green finance, trade openness, and economic development to emissions per capita; the conservation hypothesis also was supported for the unidirectional relationship running from trade openness and economic development to green finance. (2) Green finance is found to be significantly and negatively related to emissions per capita in both the short and long term. (3) Trade openness shows a positive effect on emissions per capita. Robustness tests are provided. This study deepens policy implications of green finance in the post-pandemic era and highlights the moderating role of renewable energy in the green finance impact on carbon mitigation. • This study constructs a green finance index for China. • The autoregressive distributed lag–error correction model is employed. • Green finance contributes to carbon mitigation in both the short and long run. • CO 2 emissions are Granger result of green finance, trade openness and economic growth. • Trade openness and economic growth are Granger causes of each other. [ABSTRACT FROM AUTHOR]

As Internet usage reshapes our societies, digital inequalities have increased over the past few decades. During the COVID-19 pandemic, many countries accelerated their digital transformation processes, and it is widely believed the COVID-19 pandemic has deepened existing inequalities in the digital realm. Yet, few studies have empirically examined whether digital inequalities in the labor market increased during the pandemic. This analysis studies how the COVID-19 pandemic affected Chinese workers' Internet usage and how this influence varied across socioeconomic groups. By using the ordered probit model and leveraging the most recent data from the China Family Panel Studies and the Johns Hopkins Coronavirus Resource Center, we find that the pandemic significantly increased the overall level of Internet usage in the country, and the mediating effects of the perceived importance of the Internet and access to the Internet are confirmed. As Internet usage increased, digital inequalities in China's labor market deepened, especially among young and wealthy workers with high social status in urban areas, while older and poorer workers in rural areas benefited less from this new 'digital wave.' Moreover, during the pandemic, Internet usage increased among employees working in state-owned enterprises (SOEs), which suggests a growing digital inequality gap between SOEs and other sectors. Following a series of robustness tests, our research findings remain valid. We propose a policy redesign that embodies a comprehensive long-term vision and guarantees raising the levels of Internet usage for socially and economically disadvantaged groups in China. • COVID-19 pandemic in China causes a significant increase of Internet usage rate; • Mediating roles of perceived importance of Internet and access to Internet are confirmed; • Digital inequalities deepen as Internet usage increased for certain socioeconomic groups; • The young and wealthy citizens with a high social status are benefitted from such digitalization. • Internet usage rate is significantly increased for SOE employees than other sectors. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the existence of pollution haven hypothesis (PHH) and test the casual relationship between inward foreign direct investment (FDI) and environmental pollutions, as well as other potential influencing factors of environmental performance. To this end, a panel vector error correction model (VECM) and panel co-integration test is conducted for two country groups - the BRICS (i.e., Brazil, Russia, India, China, and South Africa) and the MINT (i.e., Mexico, Indonesia, Nigeria, and Turkey) - during 1982–2014. Empirical results illustrate a bidirectional and positive causality between FDI inflows and GDP per capita for both groups, implying a virtuous circle of FDI-growth nexus. More importantly, both the BRICS and MINT countries illustrate bidirectional and negative causality between FDI inflows and environmental pressures (i.e., per capita energy consumption for BRICS and per capita carbon emissions for MINT). Such findings indicate the pollution haven hypothesis does not stand in this case. In addition, it is also found that the opening degree of trade can be promoted by FDI inflows, which has rarely been deeply analyzed in prior studies. Concluding remarks and policy suggestions are proposed in the last section. Image 1 • Vector error correction model are employed in this study. • A comparative analysis of BRICS and MINT countries. • Results refute the pollution haven hypothesis. • A virtuous circle exist between FDI and economic growth. • Trade openness can be promoted by FDI inflows. [ABSTRACT FROM AUTHOR]

Abstract A comprehensive understanding of the relationships between environmental regulations and green growth of economy is essential for policy design and decision-making. This paper combines hybrid measure with Global Malmquist Luenberger index to estimate national green growth level. A panel threshold regression technique is then employed to observe the non-linear impacts of both the formal and informal environmental regulations on green growth in Group 20 countries during 2001–2015. Results from empirical tests reveal that, for the formal environmental regulations represented by Environmental Policy Stringency (EPS), the market-based EPS is only significant at high-level phase while this is not the case in the low-level counterpart; non-market based EPS witnessed significant signs across the three phases, but in varied coefficients and significance levels. By comparison, the informal environmental regulations represented by environmental-related technologies and education levels show positive and significant impact on green growth, except for the case when countries have higher level of technologies. In addition, income per capita and gross Research & Development (R&D) expenditures present significant positive impacts on the dependent while share of service sector to the economy and investment on transport infrastructure witnessed negative effects across the models. Policy implications are proposed thereafter, although both the formal and informal environmental regulations are important to promote green growth, but they show different impacts at different phases. Graphical abstract Unlabelled Image Highlights • A global Malmquist Luenberger index has been employed to measure green growth. • Non-linear regulation-growth nexus has been examined by panel threshold model. • Environmental Policy Stringency show significant positive effects on green growth. • Education exerts larger impact on green growth than environmental-related technologies. [ABSTRACT FROM AUTHOR]

Abstract Particles with a diameter of <2.5 μm (PM 2.5) have serious adverse-effects on human health, which have caused widespread public concern in recent decades. Currently, most of the existing research on PM 2.5 have used linear regression analysis; very few studies on the subject have been conducted using non-linear models. This study adopts a panel threshold model, which is seldom used in environmental studies, to examine the non-linear effects of environmental regulation and economic growth on PM 2.5 in 30 OECD countries, and we also explore the key driving socio-economic factors for PM 2.5 emissions. The results of our analysis show that, along with an increase in environmental policy stringency, PM 2.5 emissions first rise and then show no significant correlations, and thus a reduction in emissions can be expected if current trends continue. As for GDP per capita, significant and negative correlations are found across the three phases divided by the panel threshold model, indicating a promoting effect for PM 2.5 mitigation. In addition, public expenditure on the air sector correlated positively with PM 2.5 concentrations, expanding the share of service economy reward to reduce air pollution, and urban population ratio exhibits an inverted U-shaped pattern. Future studies may shed more light on the regulation-PM 2.5 nexus, and more studies are needed to confirm the existence of bi-directional correlations between economic development and air pollution. Graphical abstract Unlabelled Image Highlights • Environmental regulation show different impacts on PM 2.5 at high-, mid- and low-level phases; • GDP per capita is negatively correlated with PM 2.5 at 1% level; • Expansion of service industry reduces pollution; • An inverted U-shaped relationship exist between urbanization and pollution. [ABSTRACT FROM AUTHOR]

Dematerialization at the national level occurs almost exclusively during periods of economic recession or low growth. While recession is not a sustainable strategy to curb environmental impact, such periods may offer important insights on the possibilities of reducing material use. Economic recession research has focused on the interactions between macroeconomic and financial variables with little systematic research dedicated to uncovering how resource use develops during periods of recession. Using a dynamic panel model, we investigate whether and to what extent material use in a sample of 150 economies between 1970 and 2010 was affected by recession and low growth. Recession occurred most frequently and in more than two thirds of all countries during the 1980s and the 1990s. In the 2000s, more than half of the recessions occurred during the financial crisis of 2008. Periods of recession were significantly and negatively correlated with material use - they tended to coincide with dematerialization. Material use decreased in recession years, but the significant correlations with growth in material use became weaker as growth rates increased. Construction minerals and metals, used to build stocks of manufactured capital, reacted more strongly to economic fluctuations than the throughput-dominated flows of biomass and fossil fuels. We conclude that the systematic link between recession and dematerialization can become policy-relevant if the mechanisms causing reductions in material use during these periods are identified. [ABSTRACT FROM AUTHOR]

Conventional wisdom has it that less working time is good for mitigating environmental pressure. Only a few studies have documented contradictory evidence. In this paper, we use panel threshold model, which is arguably the first of its kind in environmental analysis, to further document nonlinear relationships between working time and environmental pressure in EU-15 countries between 1970 and 2010. We find that the sign of this relationship shifts from positive to negative, as the working hours per worker decreases; France, Denmark, Germany, and the Netherlands experienced more environmental pressure with shorter working week. To the backdrop of reduced working time during our research period, our paper sheds new light on the traditional view of “the less, the better,” as curtailing working time beyond certain thresholds may inadvertently incur exacerbation of environmental pressure. [ABSTRACT FROM AUTHOR]

• EKC, Porter Hypothesis, and Jevons' Paradox are tested in China IS industry. • Cointegration, VECM, IRF and granger causality techniques are used for analyses. • Environmental regulation exerts a critical role in emissions reduction. • The three hypotheses are confirmed under certain conditions. • Policy recommendations for IS industrial low-carbon development are posited. By comprehensively evaluating the potential effectiveness of environmental regulations and technical innovation in facilitating emission reductions, this study highlights the complexity of the relationships — short- and long-term as well as dynamic responses — between carbon dioxide (CO 2) emissions, energy efficiency, economic performance, environmental regulation and technological innovation using the vector error correction model (VECM) by incorporating exogenous policy factors based on China IS industrial data during the period 1995–2017. Empirical analysis indicates: (a) the existence of the Environmental Kuznets Curve (EKC) Hypothesis is established given an inverted U-shaped curve of CO 2 emissions along with the increase of industrial output value; (b) weak Porter Hypothesis (pH) stands in the short term as innovation can be spurred by environmental regulation, whereas strong pH is supported in both the short and long term when energy efficiency and emission reduction can be achieved under strict regulations;(c) Jevons' Paradox is confirmed since the emissions increment brought by the massive increase in demand is greater than the emission reduction volume brought by energy efficiency improvement and; (d) Environmental regulation exerts a critical role in emission reduction, especially for the policies with market-based and common-and-control functions implemented since 2006. Corresponding policy implications to facilitate low-carbon transition of the ISI are proposed. [Display omitted] [ABSTRACT FROM AUTHOR]

• We projected a future transition path for new energy vehicles in china. • Phases of predevelopment, take-off, acceleration, and sprint are identified. • Niches, regime, and landscape for each phase are analyzed respectively. • We illustrate the essential role of government in the chinese context. • Implications for technology innovation and industrial coordination are proposed. The transport sector is a key emitter of greenhouse gasses. We applied socio-technical transition theory and the multi-level perspective (MLP) approach to depict the interplay of three MLP layers (niche, regime, and landscape) and to project future paths for the transition from traditional (fossil fuel) vehicles to new energy vehicles (NEVs) in China. Specifically, the exogenous context nurtures nascent innovations and restrains the development of traditional fuel vehicles; however, the socio-technical system of NEVs is still in the primary stage and cannot meet the needs of consumers. Under double pressures, the socio-technical system of traditional vehicles is generally stable, but there are factors that impinge on this stability. Four phases are identified according to national plans: the initial pre-development phase (2001 – 2011) protects nascent innovations; core technologies are developed and market share is expanded in the take-off phase (2012 – 2020); the acceleration phase (2021 – 2035) strengthens the trend by encouraging key technological breakthroughs, infrastructure construction, and international cooperation; and the last sprint phase (2036–) further develops the low-carbon transition in China's automobile industry. We also illustrate the essential role of government in the Chinese context. Policy implications related to electric power, technological innovation, and industrial coordination are discussed. [ABSTRACT FROM AUTHOR]

Replacing traditional energy sources with renewable energy sources is an effective way to achieve emission reduction targets. Focusing on OECD countries from 1990 to 2018, this study examines the determinants of renewable energy innovation by applying a negative binomial model. There are four main findings: (1) Renewable energy patents show an inverted U-shaped curve, peaking in 2010; solar energy accounts for the largest share of patents; and the US is the largest renewable energy innovator, followed by South Korea and Germany. (2) Renewable electricity installed capacity, share of expenditure on research and development (R&D) of GDP, and implementation of the Kyoto Protocol are all found to promote innovation; by comparison, the proportion of renewable energy power generation of the total electricity generating capacity shows a negative effect. The price of crude oil shows no significant effect due to the offset effect between the European and non-European country groups. (3) Share of R&D expenditure of GDP is confirmed to be the force driving technological progress in the solar, geothermal, and marine sectors, and it plays a more important role in Japan than in the US or Europe. Implementation of the Kyoto Protocol has no significant effect on innovation in European countries. (4) Three institutional factors—namely, the legal system and property rights; regulations; and freedom to trade internationally—are confirmed to be the driving forces, whereas this is not the case for the growth and free circulation of money. Policy implications for the optimization of the renewable energy sector's structure, the enhancement of renewable energy capacity, and the improvement of R&D investment and the institutional environment are proposed. Future research should shed light on a broader sample, using micro-level and socio-technical analysis. • A negative binomial model is used for the OECD countries during the period 1990–2018. • Renewable capacity, R&D investment, and KP are the driving forces of innovation. • Share of renewable power generation capacity negatively affects innovation. • Institutional factors are confirmed to be the driving forces of innovation. • The determinants of five renewable innovation subcategories are examined. [ABSTRACT FROM AUTHOR]

The effect of urbanization on the environment in coastal regions has been extensively examined in previous studies, but neither the reverse effect nor the role of the marine economy has been investigated. To address this gap, this study uses a panel vector autoregressive model to further explore the interactions between marine economic growth, marine pollution, and urbanization in 11 Chinese coastal provinces/municipalities from 2000 to 2016. The per capita gross ocean product (GOP) and the per capita volume of industrial wastewater discharged directly into the sea decreased during the research period, whereas the urbanization rate increased. The spatial pattern of the main polluted areas showed a shift from north to south. Marine economic growth had a single-direction influence on marine pollution and urbanization in coastal regions, implying that urban expansion did not increase the ocean output. Consistent with previous findings, urban expansion aggravated environmental damage to the ocean. According to both impulse response analysis and variance decomposition, urbanization had a significant role in explaining variation in the three factors examined in this study. In addition, according to heterogeneity analysis, the three factors were most affected in the mid-income regions and southern coastal areas, while the areas with more developed marine services could better resist the negative effects of marine pollution and urban expansion. The policy implications of increasing the proportion of the marine economy and of controlling the acceleration of urbanization are explored. • A panel vector autoregressive model was applied to 11 Chinese coastal regions. • Marine economic growth is a Granger cause of both pollution and urbanization. • Urbanization has caused marine pollution, but not vice versa. • The variables are most affected in mid-income regions and southern coastal areas. • Developed marine services mitigate negative effects of pollution and urbanization. [ABSTRACT FROM AUTHOR]

Few studies have discussed marine industrial upgrading and its association with marine economic growth and technological innovation. This study uses a vector error correction model (VECM) to explore the short-term and long-term relationship between marine economic growth, technological innovation, and industrial upgrading in China from 2006 to 2016. Results reveal the existence of two co-integration relationships between the three variables: specifically, in the long term, marine economic growth positively affects marine technological innovation, and vice versa; however, neither promote industrial upgrading and neither are promoted thereby. These findings indicate that marine economic growth and technological innovation are mutually promoting in the long term, but the mutual driving mechanism between the upgrading of marine industry and the other two variables has not yet formed. The study also reveals that the shift from secondary industry toward tertiary industry is not conducive to improving marine technological innovation, which is especially alarming given the current service-oriented tendency of China's marine industry. Key policy implications include the need to expand the relative size of the marine economy, prioritize developing marine secondary industry, develop marine technology, and train high-level marine professionals. Image 1 • Relations of marine growth, innovation and industrial upgrading in China are studied. • A vector error correction model has been used. • Marine growth and innovation are mutually promoted in the long-term. • Neither affects or is affected by marine industrial upgrading in the long-term. • Shifting toward marine tertiary industry inhibits innovation and economic growth. [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 separates marine carrying capacity into four key dimensions, i.e., social, economic, resource, and ecological, and uses the entropy method to evaluate the carrying capacity of China's 11 coastal regions during the period 2007–2016. We then predict the values of marine carrying capacity in the subsequent five years (2017–2021) using the grey Verhulst model. Results reveal a significant disparity in marine carrying capacity among the 11 coastal regions of China, and social and ecological carrying capacities illustrate among the four subcategories. Pearl River Delta in the south has the highest marine carrying capacity value and shows an increasing trend, while Yangtze River Delta and Bohai Rim Region in the north are stable. With regard to the predicted values for 2017–2021, forecasting results illustrate that the industrial structure of China's coastal areas is gradually turning towards the mode of diversified and comprehensive utilization of marine resources. • We evaluate marine carrying capacity in China during 2007–2016 and its four sub-categories. • The entropy method and grey Verhulst model were applied to the data. • A significant disparity in marine carrying capacity is revealed in China. • The Pearl River Delta performs better than other two coastal regions. • Industrial structure and resource utilization show a diversified development trend. [ABSTRACT FROM AUTHOR]

Conventional wisdom has it that marine economic growth and technological innovation help to reduce pollution of the oceans. Few studies, however, have examined whether the relationship is nonlinear and to what extent the effects have been realized. To fill this gap, this study takes 11 coastal regions of China during the period 2000–2016 and, using the panel threshold model, examines the nonlinear effects of per capita gross ocean product (GOP) and marine patents on marine pollution as represented by the quantity of industrial wastewater discharged directly into the sea. The results reveal that the increase in per capita GOP strongly promotes marine pollution across the three phases of panel threshold model, but the degree of influence is gradually declining, implying that China is still located in the first half of the Environment Kuznets Curve (EKC), before the peak. Thus, a negative correlation of the GOP–pollution nexus can be expected if current trends continue, which suggests that the development of the marine economy may alleviate ocean environmental pressures. As for marine patents, no significant correlations in the low- and mid-level phases were found, but a strong impact by marine patents on pollution is shown in the high-level phase, indicating that the accumulation of technological innovation related to the marine economy is playing an increasingly important role in reducing marine pollution. Finally, the numbers of provinces/municipalities in the three phases have been identified. Several important policy implications for development of the marine economy are highlighted. • We use threshold model to explore effect of marine growth and patents on pollution. • Marine growth in China is still in the first half of Environment Kuznets Curve. • Marine patents have begun to significantly alleviate marine pollution. • Numbers of regions in the three threshold regimes have been identified. • We are the first to account for nonlinear marine pollution processes in China. [ABSTRACT FROM AUTHOR]

• Spatial panel models have been applied to 283 Chinese cities during 2000–2013. • We illustrate the inverted U-shaped relation between population density and productivity. • Density plays an important mediating role in the effect of housing prices on productivity. • The mechanism is mainly spillover effect, while the effect has different outcomes for different samples. • Increasing housing prices and population intensification are both essential driving forces for productivity improvement. The issue of what to promote in total factor productivity (TFP) in urban areas has been widely discussed in academia and housing prices and population density are confirmed to be two of the most essential driving factors. However, research into the interaction of housing prices and population density with TFP has been neglected, with no previous studies taking spatial factors into consideration, which may bias the results. From this perspective, using spatial panel data models and employing instrumental variables to solve the endogenous problem, this study examines the impact of housing prices on TFP through the mediating effect of population density for 283 Chinese cities during the period 2000–2013, and confirms that the mediating effect accounts for 18.70 % of the total effect. The results show the positive and significant association of housing prices with TFP and the inverted U-shape of population density. The underlying logic is that housing prices change population density by attracting people with high purchasing power and discouraging those unable to afford housing, whereas increased density helps to promote productivity since the settled inhabitants always have highly developed work skills and are well educated. The influencing mechanism of housing prices on TFP through population density is analyzed, namely the spillover effect. We find that the spillover effect exists in the eastern and central regions, as well as first, second, and third tier cities, while for western regions and fifth tier cities, population mobility and increased in housing prices slows their economic development. There is no evidence of any spillover effect in fourth tier cities. A discussion and suggested policy implications are also provided. [ABSTRACT FROM AUTHOR]

A quantitative measure of performance that integrates national-level carbon emission profiles with key parameters of social and economic wellbeing can provide an effective management tool for policy interventions. This paper constructs non-parametric evaluation and decomposition models using hybrid measure and meta-frontier techniques. The proposed models are employed to estimate the wellbeing performance of carbon emissions (WPCE) and identify the sources of WPCE inefficiency. Empirical analyses based on the Group 20 (G20) countries for the 2000–2015 period shows the worst performance is in the BRICS country group (i.e. Brazil, Russia, India, China, and South Africa) – known for rapid growth – whereas the developed and the developing economies of the G20 group show positive trajectories of performance. As for China, its performance measure of WPCE was the lowest among the G20 indicating significant potential for further improvement. The analysis also highlights the role of managerial failure as the primary driver of inefficiency, more important than technological inefficiency in explaining efficiency loss within the G20 countries. This critical finding – the relevance and importance of managerial capability – suggests the need for a high level of attention to governance and managerial capacity to ensure continued improvements in performance on carbon emissions and human wellbeing. A lesson to be drawn from this study is that China's policies to promote a low carbon economy can benefit from increased priority given to low-carbon technological innovation for the energy system transition and enhancement of environmental governance and managerial capacity to achieve a long-term sustainability. • Welfare performance of carbon emissions (WPCE) are evaluated for G20 countries. • A hybrid non-parametric evaluation and meta-frontier techniques are employed. • Developing countries performed the best followed by developed and BRICS countries. • Gaps of WPCE are non-negligible and sources of performance loss are divergent. • Policy implications for China drawing on the cross-country comparisons are proposed. [ABSTRACT FROM AUTHOR]

Abstract The research on economic recession has been more focused on the interactions between macroeconomic and financial variables. However, whether material use has been affected during the recession period has remained under-explored. In order to fill up this gap, this study investigates the relationship between material use and economic recession, as well as other socio-economic drivers, by using the material flow analysis and the system generalized method of moments for 157 economies worldwide during 1980–2011. Results show that economic recession poses significant and negative impact on domestic material consumption at 1% level, illustrating its role as a determinant factor on material mitigation. By dividing the research sample into extractive and non-extractive economies, as well as high-, mid- and low-income groups, we again confirmed the significant negative correlations as expected. No significant sign is found between recession and physical trade balance. Besides, other drivers such as population, Gross Domestic Production (GDP) per capita and technological variables also exert marked effects at different situations. This research work provides an empirical study on how recession and other factors affect material use at various scenarios, which have essential implications for understanding material flow dynamics in different economic cycles. Graphical abstract Image 1 Highlights • Recession is the determinant factor in reducing material use. • Recession-material nexus varies along with countries of different income levels and trade patterns. • Recession has no explanatory power to physical trade balance. • Income significantly promote material consumption. • Expansion of service sector helps to reduce material consumption. [ABSTRACT FROM AUTHOR]