Green finance,technological progress,and ecological performance—evidence from 30 Provinces in China

The interaction between green finance and other factors, such as ecological environment, has been a research hotspot nowadays. Especially, the reasonable guiding of capital into energy conservation and environmental protection industries would greatly affect those factors, so as to the relation between them. This paper aimed to analyze the relationships between green finance, technological progress, and ecological performance quantitatively. The entropy method was used to respectively construct the system of index for green finance and technological progress, and index for ecological performance was measured by the super-SBM model. The panel vector autoregressive (PVAR) model was selected to empirically analyze dynamic relationships based on datasets from 30 provinces in China during 2008–2019 period. The results told that (1) from 2008 to 2019, China’s overall level of green finance, technological progress and ecological performance increased to varying degrees. Spatially, the areas with high-developed green finance greatly coincided with those such as large cities or the eastern coast that had good financial development. The distribution of technological progress index were similar, except some underdeveloped areas with relatively advanced scientific research institutes. The ecological performance, however, was high in the South and low in the north. (2) In the lag for 3 years, the influence of green finance on ecological performance in different regions was all positive for that all the coefficient symbols that passed the significance test were above 0, while that on technological progress was negative first and then positive. And the effects of technological progress on ecological performance were positive in ecological regions and negative in low ecological regions (0.0893 and -0.1211 in the case of three-stage lag respectively). (3) The contribution of green finance to ecological performance was high according to the results of variance decomposition, maintained at about 30%, and that of technological progress increased year by year (from 0.000 to 0.039). Therefore, we proposed to strengthen the development of green finance in underdeveloped regions. The emphasis should be laid on the researches and applications of green technology, the formulation of financing policies in innovation compensation and the establishment of a dynamic monitoring system for the ecological environment.

     

Industrialization,urbanization, and carbon emission efficiency of Yangtze River Economic Belt—empirical analysis based on stochastic frontier model

Carbon emission efficiency directly determines the level of green economic development. Based on the panel data of China’s Yangtze River Economic Belt (YEB) from 2008 to 2017, this paper uses the stochastic frontier analysis (SFA) model to analyze the overall carbon emission efficiency level, influencing factors, and changing trends, with a view to discussing the relationship between economic development and carbon emission efficiency. The results suggest, first, the overall carbon emission efficiency of the YEB is on an upward trend, but there is still much room for improvement. Second, the impact of industrialization and urbanization on carbon emission efficiency follows a U-shaped. As industrialization and urbanization progress, the impact on carbon emission efficiency shows a downward and then upward trend. Third, due to the rebound effect, technological progress has a slight negative impact on carbon emission efficiency. Energy consumption structure, government intervention, and foreign trade are all negative incentive factors. Therefore, efforts to improve carbon emission efficiency in the YEB should focus on transforming the economic growth model, adjusting the industrial structure, improving the energy consumption structure, and innovating green technology. The research results can provide a reference for the government policymakers to develop a green economy.

     

Temporal and spatial characteristics of green total factor productivity in energy-intensive industry in China

China’s energy-intensive industry (EII) is characterized by high pollution, high energy consumption, and high emissions. It is essential to boost this sector’s green total factor productivity (GTFP) in order to support the sustainable development of the China’s economy and help to achieve the objective of carbon neutrality. This work measures the evolution of GTFP in EII and its subsectors at provincial and regional level from 2001 to 2019, identifies the causes of these changes, and finally analyzes the particular spatial aggregation effect of GTFP in EII. It is discovered that the GTFP of China’s EII has significantly improved throughout the sample period and exhibits a spatial structure of “high in the coastal areas and low in the west and center.” The main driver of GTFP growth for China’s EII and its subsectors was technological advance. Smelting and pressing of ferrous metals (SPFM) and smelting and pressing of non-ferrous metals (SPNM) were the industries with the most significant technological progress. Remarkable spatial correlations existed among the GTFP of EII at provincial level. The GTFP values of EII in coastal regions were relatively high and tend to benefit the adjacent provinces but there was a polarization effect in the Middle Reaches of Yellow River (YR). Finally, policy implications are provided for the sustainable development of China’s EII.

     

How does power technology innovation affect carbon productivity? A spatial perspective in China

Power technology innovation has been positioned as an effective way to contribute to China’s carbon productivity. However, limited empirical evidence exists on the impact of power technology innovation on carbon productivity. Thus, based on the annual panel dataset of 30 China’s provinces from 2001 to 2019, this study explored whether and how power technology innovation promotes or impedes the improvement of carbon productivity. First, carbon productivity in the framework of total factor was calculated based on the metafrontier Malmquist-Luenberger productivity index. Second, the effect of power technology innovation on carbon productivity was investigated using the spatial Durbin model. And we also examined whether heterogeneous power technology innovations have a synergistic effect on carbon productivity. Third, influence mechanism of power technology innovation affecting carbon productivity was identified. Results show that (1) there are notable differences in China’s provincial carbon productivity, which is characterized by the spatial correlation. (2) Local power technology innovation has a promotion effect on carbon productivity in both local and neighboring provinces. Moreover, the promotion effect of breakthrough power technology innovation is stronger than that of incremental power technology innovation. (3) Catching-up Effect and Innovation Effect are important transmission channels through which power technology innovation improves carbon productivity. Finally, policy recommendations are provided.

     

Analysis of the mechanism of the impact of internet development on green economic growth: evidence from 269 prefecture cities in China

As the digital economy develops rapidly and the network information technology advances, new development models represented by the network economy have emerged, which have a crucial impact on green economic growth. However, the relevant previous studies lacked the role of analyzing the direct and indirect effects of internet development on green economic growth at the prefecture-level city level. For this purpose, this paper aims to examine the intrinsic mechanism of the impact of internet development on green economic growth and provide empirical support for cities and regions in China to increase internet construction. Furthermore, the mixed model (EBM), which includes both radial and non-radial distance functions, is applied to calculate the green economic growth index. Fixed effect model and mediation effect model are also employed to test influence mechanisms of the internet development on green economic growth using panel data of 269 prefecture-level cities in China from 2004 to 2019. The statistical results reveal that internet development has contributed significantly to green economic growth. When the internet development level increases by 1 unit, the green economic growth level increases by an average of 5.0372 units. However, regional heterogeneity is evident between internet development and green economic growth, that is, the promoting effect of internet development on green economic growth is gradually enhanced from the eastern region to the western region. We also find that internet development guides industrial structure upgrading improves environmental quality and accelerates enterprise innovation, which indirectly contributes to green economic growth. And internet development mainly achieves green economic growth through enterprise innovation. Based on the above findings, we concluded that policymakers should not only strengthen the guiding role of social actors to promote the stable development of the internet industry, but also foster the construction of the three models of “internet+industry integration,” “internet+environmental governance,” and “internet+enterprise innovation” to promote green economic growth.

     

How does biased technological progress affect haze pollution? Evidence from APEC economies

Biased technological progress is the act of energy conservation and emission reduction by changing the marginal rate of substitution. In this study, we introduced renewable energy into a production function, and proposed a method of identifying biased characteristics of technological progress, based on marginal productivity theory. A panel dataset for the Asia–Pacific Economic Cooperation (APEC) economies from 2000 to 2017 was analyzed to explore the effect of biased technological progress in reducing particulate matter (PM_2.5). We found that input biased technological progress tended to use more non-renewable energy. Input biased technological progress aggravated haze pollution; however, this effect decreased as the PM_2.5 concentration increased. Output biased technological progress significantly reduced haze pollution in high-income economies, but increased it in low-income economies. The effect of neutral technological progress on haze pollution was the opposite of the effect from output biased technological progress. We also found that increasing renewable energy consumption and reducing energy intensity were separate effective paths for input and output biased technological progress, respectively, to mitigate haze pollution. For neutral technological progress, improving total factor productivity was an important way to mitigate haze pollution. Finally, several policy recommendations are proposed to mitigate haze pollution in APEC economies.

     

Polycentric agglomeration and haze pollution: evidence from China

Polycentric agglomeration has gradually become a salient feature of rapid growth in urbanization in China. Using province-level balanced panel data over the period 2000–18, we examine the impact of polycentric agglomeration on haze pollution and its mechanism of action. The results show that the impact of polycentric agglomeration on haze pollution exhibits a significant inverted U-shaped feature. Nevertheless, except for a few provinces where polycentric agglomeration exceeds the turning point, the degree of polycentric concentration in most provinces lies to the left of the turning point. Further, a mediating effect model illustrates that industrial structure rationalization and technological progress are effective paths through which polycentric agglomeration affects haze pollution. Finally, we demonstrate that the effect of polycentric agglomeration on haze pollution is influenced by transportation and communication infrastructure; improved transportation and communication infrastructure contributes to the haze control effect of polycentric agglomeration.

     

Evaluating pollution damage function through carbon pricing,renewable energy demand,and cleaner technologies in China: blue versus green economy

Climate change and increased greenhouse gas emissions boost the global average temperature to less than 2°C, which is the estimated breakeven point. The globe is moving into blue pollution economies as the environmental sustainability objective becomes more distorted. The study looked at three United Nations Sustainable Development Goals, namely (i) affordable and clean energy; (ii) industry, innovation, and infrastructure; and (iii) climate change, to see how far the Chinese economy has progressed toward green and clean development strategy. In the context of China, the “pollution damage function” was intended to refer to carbon damages related to carbon pricing, technological variables, sustained economic growth, incoming foreign investment, and green energy. The data was collected between 1975 and 2019 and analyzed using various statistical approaches. The results of the autoregressive distributed lag model suggest that carbon taxes on industrial emissions reduce carbon damages in the short and long run. Furthermore, a rise in inbound foreign investment and renewable energy demand reduces carbon damages in the short term, proving the “pollution halo” and “green energy” hypotheses; nonetheless, the results are insufficient to explain the stated results in the long run. In the long run, technology transfers and continued economic growth are beneficial in reducing carbon damages and confirming the potential of cleaner solutions in pollution mitigation. The causal inferences show the one-way relationship running from carbon pricing and technology transfer to carbon damages, and green energy to high-technology exports in a country. The impulse response estimates suggested that carbon tax, inbound foreign investment, and technology transfers likely decrease carbon damages for the next 10 years. On the other hand, continued economic growth and inadequate green energy sources are likely to increase carbon pollution in a country. The variance decomposition analysis suggested that carbon pricing and information and communication technology exports would likely significantly influence carbon damages over time. To keep the earth’s temperature within the set threshold, the true motivation to shift from a blue to a green economy required strict environmental legislation, the use of green energy sources, and the export of cleaner technologies.

Graphical abstract

Source: Authors’ self-extract

     

Research on measurement and improvement path of industrial green development in China: a perspective of environmental welfare efficiency

The increasing concern about the environmental issue and its serious adverse effects on human health has made China’s industrial green transformation being a matter of public concern. In this study, a network slack-based measure (NSBM) was applied to explore China’s industrial green development level from the perspective of environmental welfare efficiency (EWE), considering not only the impact of industrial development on environment and economy, but also the impact on human well-being. Based on the data of 30 provincial administrative regions in China from 2004 to 2017, the comprehensive efficiency (CE) of China’s industrial sector was measured and decomposed. The results show that the industrial production efficiency (IPE) is much higher than the EWE, and the improvement of the EWE will be the key to realize the green transformation of China’s industry. On this basis, considering the effects of spatial interaction, the spatial Durbin model was established to analyze the driving factors of EWE. Finally, this research puts forward promotion path of industrial green development.

     

Green growth and environmental sustainability in China: the role of environmental taxes

Environmental Science and Pollution Research - This study aims to investigate the impact of environmental-related taxes on green growth and CO2 emissions in China covering the time 1996–2019....     

“Green” economic development in China: quantile regression evidence from the Yangtze River Economic Belt

As China’s economy began transitioning from one focused on high-speed growth to one focusing on high-quality development, sustainable green development has become the main goal pursued by the government. This study empirically measures the marginal impact of per capita GDP, technological innovation level, industrial structure, openness, fiscal decentralization, and urbanization level on per capita wastewater discharge in 11 provinces (cities) along the Yangtze River Economic Belt (YREB) from 2008 to 2018 using a quantile model. The key findings were as follows: (1) factors such as the per capita GDP, industrial structure, foreign direct investment, and urbanization in the YREB significantly increased water resource pollution; (2) the quantile model regression results showed that the relationship between economic growth and ecological pollution followed the so-called environmental Kuznets inverted U-curve. Wastewater discharge per capita was low in areas with low per capita GDP, meaning that the ecological environment in these areas was more fragile and that the environmental pollution costs due to economic growth were therefore relatively much higher in these areas; (3) fiscal decentralization significantly reduced water resource pollution in relatively developed areas although the effects in the relatively developing areas were not significant; and (4) the effects of technological innovation on reducing water resource pollution in the YREB were positive but not very significant. The results also confirmed that traditional patterns of economic growth increased water pollution in the YREB. For this reason, the government needs to urgently improve policies—for example, upgrading economic structures, preventing over-urbanization, speeding up technological innovation, introducing environmentally friendly foreign investment, and providing more rewards to best practitioners of environmental governance—that is conducive to the achievement of green ecological development.

     

Role of financial inclusion and export diversification in determining green growth: evidence from SAARC economies

This study quantifies the impact of financial inclusion and export diversification in attaining the target of green growth for SAARC economies during the period 2000 to 2019. For the analysis purpose, this study employed second-generation econometric techniques that deal with heterogeneity and cross-sectional dependence issues. To this end, CUP-FM and CUP-BC are used to investigate the long-run dynamic equilibrium relationship among the variables of interest. The outcomes show that financial inclusion and institutional quality are eco-friendly variables and play a vital role in attaining green growth. In contrast, export diversification and FDI are inversely related with green growth in SAARC economies. Furthermore, a unidirectional causality running from financial inclusion to green growth and financial inclusion to export diversification is observed. On the basis of investigated outcomes, this research suggests essential policy recommendations to attain green growth.

     

Can transportation infrastructure reduce haze pollution in China?

Traffic emission is one of the main sources of haze pollution, but few studies have evaluated the dynamic impact and mechanism of transportation infrastructure on haze pollution based on a spatial perspective. This study selects the annual data of 30 provinces in China from 2000 to 2017 and uses a dynamic spatial Durbin model to study the dynamic impact of transportation infrastructure on haze pollution. The results show that transportation infrastructure has a significant spatial spillover effect on haze pollution, and the spatial spillover effect has regional heterogeneity. Specifically, whether long term or short term, highway traffic has a boosting effect on haze pollution, while railway traffic has an inhibitory effect on haze pollution. In addition, transportation infrastructure can affect haze pollution through three paths: expanding economic scale, promoting transformation of industrial structure, and promoting technological progress. At the regional level, the improvement of highway traffic density in eastern, central, and western regions will significantly increase haze pollution. The enhancement of railway traffic density has a significant inhibitory and boosting effect on haze pollution in central and western regions, respectively. For the eastern region, railway traffic construction can only restrain local haze pollution, but cannot exert the spatial spillover effect of railway traffic to reduce haze. The conclusions of this paper provide policy inspirations for giving full play to the haze reduction effect of transportation infrastructure and the development of green transportation.

     

Green finance and corporate environmental responsibility: evidence from heavily polluting listed enterprises in China

Green finance is not just a global trend, but it has become an important channel for industrialized countries to achieve sustainable growth. However, few studies have discussed the environmental governance effects of green finance from the micro-firm level. Based on the data of Chinese A-share listed firms in heavily polluting industries, we, combining with property rights and environmental regulation, empirically research the influence of green finance on corporate environmental responsibility (CER) performance. Results indicate that green finance has a significant negative effect on the environmental responsibility of heavily polluting firms. The result remains after a series of robustness tests. In addition, property rights and environmental regulation play a moderating role in the above relationship. The negative impact of green finance on CER is stronger in private firms and firms in areas with low environmental regulation intensity. Moreover, we observe that green finance decreases the CER performance of heavily polluting firms by increasing financing constraints, reducing environmental investment, and diminishing technological innovation. This study identifies the external factors that influence CER and also provides implications and theoretical support for the government to improve the setting and the implementation of green finance policy in the future.

     

Does agriculture-induced environmental Kuznets curve exist in developing countries?

Even though the economic growth and the increased agricultural production bring welfare increment, they could also load significant environmental costs to society. This study aims to investigate the existence of agriculture-induced EKC hypothesis in 47 developing countries during 1976–2017 by using dynamic panel data estimators. According to the long-run findings of the DOLS and the FMOLS estimators, there is an inverted U-shaped relationship that exists between income and the CO₂ emissions, while agricultural production has a negative impact on environmental quality. In addition, the PMG estimator is also employed for robustness check. Likewise the DOLS and the FMOLS findings, the long-run results of the PMG estimator also support the existence of agriculture-induced EKC for developing countries. The empirical findings of this study provide stimulus results of policy makers to re-consider their current production infrastructure of agricultural sector to achieve sustainable development.

     

Measurement of China’s green GDP and its dynamic variation based on industrial perspective

Over the previous two decades, Chinese economic development presented a rapid growth. However, with continuous industrialization and urbanization, China is confronted with great challenges of energy security and environmental issues. These problems are closely related to the current accounting method of economic growth to a certain extent. In order to meet these challenges, it is imperative to establish a green accounting system of economic growth and measure China’s green GDP and its changing trend based on the industrial perspective. Using the System of Environmental Economic Accounting (SEEA) and industry data, this paper estimates China’s green GDP and green value added by industry sectors in 2005, 2007, 2010, 2012, 2015, and 2017. The results reveal the following: First, the ratio of green GDP to traditional GDP gradually increases from 89.85 to 95.83% during 2005–2017, which means that the negative externalities of economic growth of the resource and environment are gradually weakened. Second, the difference between traditional GDP and green GDP during 2005–2017 is about 6.96%, with the carbon emissions accounting for 70.71% of environmental impact. Third, due to more than 80% of the environmental impact coming from three sectors: manufacturing (49.99%), electricity industry (22.63%), and other services (11.37%), these three sectors should be key sectors for energy conservation and emission reduction; fourth, the green GDP of the mining, electricity industries, and manufacturing accounts for the lowest proportion of GDP, which means that the development patterns of these three industries in recent years should be adjusted and optimized step by step.

     

The nexus between remittances,natural resources,technological innovation,economic growth,and environmental sustainability in Pakistan

Globally, the issues about sustainable development are on the increase. Moreover, these issues are rising every day in Pakistan, as remittances are increasing, technology innovation is ambiguous, natural resources are degraded, and economic expansion might pose serious challenges to the environment. Thus, this research looks at how remittances, natural resources, technological innovation, and economic growth affect carbon dioxide (CO₂₎ emissions in Pakistan by controlling energy consumption and urbanization from 1990 to 2019. The Bayer and Hanck test of combined cointegration discloses a cointegration between remittances, natural resources, technological innovations, economic growth, and CO₂ emissions. Moreover, the autoregressive distributive lag model (ARDL) proposes a significant positive association between remittances and CO₂ emissions in the long run, indicating that the increase in remittances distresses the environmental performance of Pakistan. Our study confirms that natural resources decrease CO₂ emissions while technological advancement, economic progress, energy use, and urbanization increase CO₂ emissions. In addition, the results of robustness checks by employing fully modified ordinary least squares and dynamic ordinary least squares are parallel to the conclusions of ARDL estimations. Furthermore, the frequency causality test results show that remittances, natural resources, technological innovation, economic growth, energy use, and urbanization cause CO₂ emissions at different frequencies. Therefore, to achieve the sustainable development goals, appropriate policy repercussions can be developed toward advanced and environmentally sustainable sources of energy.

     

Effects of urbanization and nonrenewable energy on carbon emission in Africa

This study investigates the impact of urbanization and nonrenewable energy consumption on carbon emissions. The context of the analysis is 54 African Union countries from 1996 to 2019. For estimation, we use panel quantile regression (PQR) and fully modified ordinary least squares (FMOLS). Our regression results demonstrate that there is a positive correlation between urbanization and CO₂ emission. Further, our empirical results confirmed that nonrenewable energy consumption increases environmental pollution in African Union countries. The outcomes demonstrate the EKC hypothesis because at the initial stage of development, when economic growth increases, environmental pollution increases; after a threshold point, environmental pollution decreases as economic growth increases. It can find an inverted U-shaped relationship between economic growth and CO₂ emission. The findings also show that urbanization should be planned; otherwise, it can lead to environmental degradation in the long run. Africa continent takes strict action and builds a blueprint for efficient and effective energy production and consumption. The only solution to achieve green growth in Africa is to shift from fossil fuel energy supply to renewable energy supply.

     

An updated review on advancement in fermentative production strategies for biobutanol using Clostridium spp.

A significant concern of our fuel-dependent era is the unceasing exhaustion of petroleum fuel supplies. In parallel to this, environmental issues such as the greenhouse effect, change in global climate, and increasing global temperature must be addressed on a priority basis. Biobutanol, which has fuel characteristics comparable to gasoline, has attracted global attention as a viable green fuel alternative among the many biofuel alternatives. Renewable biomass could be used for the sustainable production of biobutanol by the acetone-butanol-ethanol (ABE) pathway. Non-extinguishable resources, such as algal and lignocellulosic biomass, and starch are some of the most commonly used feedstock for fermentative production of biobutanol, and each has its particular set of advantages. Clostridium, a gram-positive endospore-forming bacterium that can produce a range of compounds, along with n-butanol is traditionally known for its biobutanol production capabilities. Clostridium fermentation produces biobased n-butanol through ABE fermentation. However, low butanol titer, a lack of suitable feedstock, and product inhibition are the primary difficulties in biobutanol synthesis. Critical issues that are essential for sustainable production of biobutanol include (i) developing high butanol titer producing strains utilizing genetic and metabolic engineering approaches, (ii) renewable biomass that could be used for biobutanol production at a larger scale, and (iii) addressing the limits of traditional batch fermentation by integrated bioprocessing technologies with effective product recovery procedures that have increased the efficiency of biobutanol synthesis. Our paper reviews the current progress in all three aspects of butanol production and presents recent data on current practices in fermentative biobutanol production technology.

     

Climate change impact assessment on Northeast China’s grain production

The international community is paying more attention to climate change because a consensus has been reached that climate change has an adverse effect not only on the environment but also on agriculture. Therefore, in this study, present and future climate datasets (obtained from general circulation models) including atmospheric carbon concentration were used to assess the impact of climate change on grain production for an important base of China (Northeast). An empirical model has been developed using climate and other additional variables (effective irrigation area, fertilizer, and labor force) to assess the effect of climate change on grain production. The results revealed that maximum temperature is a key climate determinant in grain production of the study area. Atmospheric carbon concentration showed a significant impact on grain outputs in most of the cases. During the analysis, it was observed that precipitation displayed a declining trend while an effective irrigation area showed positive non-significant contribution to grain production. Analysis based on different representative concentration pathways exhibited that maximum temperature may contribute negatively to grain production in the future. Overall, the analysis showed that climate change has a significant contribution to grain production. In conclusion, the implications for future research and policymakers have been addressed. Particularly, the importance of considering regional differences in adaptation planning in agricultural regions was also considered.