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The behaviors of local governments can affect the enforcement of environmental regulations. Environmental regulation can influence the behaviour of energy-intensive enterprises. This paper examines the relationship between local government competition, environmental regulation and the investment efficiency of high energy consuming firms using a basic panel regression and moderating effects model based on data from 2011-2020 for high energy consuming firms in China. The paper found that local government competition and environmental regulation can promote increased investment efficiency in energy-intensive firms in the short term. However, environmental regulation is not beneficial to investment efficiency in the long run. Local government competition plays a positive moderating role in the impact of environmental regulation on the investment efficiency of high energy consuming firms. There is a threshold effect on the role of local government competition. When the level of government competition exceeds 2.097, it has a negative impact on the investment efficiency. We further test for heterogeneity and we find that this promotion effect is also more obvious in areas with high environmental taxes and low marketability. Finally, we provide constructive suggestions for the development of government and the improvement of the investment efficiency of high energyconsuming firms. [ABSTRACT FROM AUTHOR]

Carbon neutrality is the only way for green low-carbon development. Technological progress is an important starting point for improving energy efficiency. Through scientific and technological innovation, improving energy efficiency is a practical way to achieve the goal of carbon neutralization. Due to the limitation of data and index selection, there is no qualitative analysis of carbon neutrality in this paper. Compared with previous studies, the paper has the following contributions: Firstly, the energy efficiency score of China's provincial level is measured with the DEA method and it is found that the average energy efficiency score of the eastern region is the highest, followed by the western region, and finally the central region. The results also show that the energy efficiency is not in accordance with the economic growth. The regions with higher energy efficiency scores are not always economically developed because of huge energy consumption supporting the economic development. Secondly, the Tobit method is used to study the impact of the reverse technology spillover effect of OFDI on China's energy efficiency. The results show that the spillover effect has a significant positive effect on the improvement of China's energy efficiency, and has a positive impact on the eastern and western regions, but has no significant impact on the western region. Finally, we put forward some policy recommendations to increase energy efficiency to approach carbon neutrality and thus promote green economic development. This paper enriches the content of energy economy, the research method is innovative, and the conclusion is more scientific. [ABSTRACT FROM AUTHOR]

Intelligence relieving energy consumption and economic growth nexus is important for green development. To explore the potential power for sustainability, this paper uses entropy weight method to measure the intelligent level, adopts decoupling indicator between energy consumption and economic growth for green growth performance, and builds a spatial model to diagnose the mechanism of decoupling system. The results show that the achievements of intelligent development in the three regions are remarkable, and the intelligent level in the eastern region is the most prominent of all. Regardless of regional differences, intelligence is the main and stable driver deepening decoupling indicator; Notable pushing-out or pushing-in spilling power on regional decoupling through many channels can be identified, namely urbanization, income and FDI. Clean energy can help promote the driving effects of intelligence on decoupling and is not confined by regions. The fierce green competition race in the form of "anti-typicality" mode exists in various regions, especially in the Western region; only in the Middle region, the intelligent spatial spillover effect can form the driving force for decoupling. Accelerating the intelligent development and the application of clean energy is an effective measure to achieve the green environmental targets. [ABSTRACT FROM AUTHOR]

In order to explore an effective way to evaluate the comprehensive performance of high-quality development of China's manufacturing industry based on low-carbon constraints, this paper, based on the analysis of research background, drew on the latest domestic and international research results and experience, and fully considered the actual situation of high-quality development of China's manufacturing industry based on low-carbon constraints. Among the five criteria-layer evaluation index of economic development, energy consumption, technological innovation, environmental pressure and environmental pollution governance, 30 representative operating-layer evaluation indicators were selected, and a fuzzy matter-element extension evaluation model for the comprehensive performance evaluation of China's provincial high-quality development based on low-carbon constraints was constructed. By using the relevant statistical data in China Statistical Yearbook, China Energy Statistical Yearbook and China Environmental Status Bulletin, this paper conducted an evaluation study on the comprehensive performance of high-quality development of China's manufacturing industry based on low-carbon constraints in 31 provinces, verified the effectiveness of the fuzzy matterelement extension evaluation model, and provided an effective quantitative analysis method for the comprehensive performance evaluation of high-quality development of China's manufacturing industry based on low-carbon constraints. [ABSTRACT FROM AUTHOR]

The new energy industry helps to meet the challenges of energy exhaustion and environmental pollution. Based on the panel data from 2015 to 2021, this paper uses the BCC model and Tobit model to construct the empirical measurement of technology innovation efficiency of listed new energy enterprises with three-stage DEA technology and uses the convergence model to test the efficiency difference. The results show that: (1) Using the traditional BCC model, the technical innovation level of new energy enterprises is insufficient, and the overall comprehensive efficiency and pure technical efficiency are 0.220 and 0.302 respectively, which need to be improved. (2) The three-stage DEA model was used to control environmental factors and statistical errors, and the overall efficiency of technological innovation of new energy enterprises increased. The comprehensive efficiency and scale efficiency increased to 0.541 and 0.896 respectively. (3) The technological innovation efficiency of new energy enterprises presents temporal and spatial heterogeneity. The coefficient of variation of technological innovation efficiency of new energy enterprises ranged from 0.084 to 1.000 with significant differences. The technological innovation efficiency of new energy enterprises in eastern, central and western China shows a U-shaped fluctuation. [ABSTRACT FROM AUTHOR]

Faced with both economic and environmental pressures, how to improve energy efficiency in a green way is gradually attracting attention. Reasonable environmental regulations can promote the green transformation of energy and improve green energy efficiency, which is of great practical significance for achieving global sustainable development. This paper measures the green energy efficiency of 30 Chinese provinces in 2019 based on the Super-SBM model, selects five representative antecedent conditions of three environmental regulation dimensions: command-and-control, market-incentive, and voluntary public, and uses fsQCA to explore the group effects and enhancement paths of different types of environmental regulations on green energy efficiency. The results found that (1) there are four green energy efficiency enhancement paths: government pressure type, market mobilization type, government-led public association type, and multiple subject type; (2) commandand-control type environmental regulations play an important role in enhancing green energy efficiency in most provinces; and (3) multiple subject type enhancement paths can achieve higher green energy efficiency. This study investigates the impact of environmental regulation on green energy efficiency in order to provide reference and reference for the improvement of green energy efficiency in China's provinces. [ABSTRACT FROM AUTHOR]

With the rapid development of economy, environmental pollution is becoming more and more serious. Whether the environment and economy can achieve a win-win situation has always been a controversial issue. This paper conducts an empirical study on the correlation between environmental performance and financial performance of 16 heavy polluting industries in China. The evaluation index system is constructed by closely following the characteristics of high energy consumption and high pollution in heavy pollution industry, and the projection pursuit model based on RAGA is applied to measure the environmental performance and financial performance of enterprises, which can overcome the interference and limitation of artificial assignment of data structure by traditional methods and has the characteristics of strong anti-interference and high accuracy. On this basis, the relationship between the two is investigated by establishing a multiple regression equation, and the results show that the environmental performance of listed companies in China’s heavy pollution industry has a negative relationship with financial performance, and the improvement of environmental performance does not bring about an overall improvement in financial performance. Finally, this paper makes an in-depth analysis of the causes of this result and puts forward some corresponding suggestions. [ABSTRACT FROM AUTHOR]

Based on the energy consumption data of the logistics industry in 30 provinces and cities in China, this paper uses the carbon emission accounting method of IPCC to estimate the total carbon emissions of the logistics industry in China from 2010 to 2019, and introduces the carbon emission Theil index. The Logarithmic Mean Divisia Index (LMDI) model is used to measure the regional differences in carbon emissions of China's logistics industry and decompose the influencing factors. The research results show that the total carbon emissions of China's logistics industry have increased significantly, and the total carbon emissions and growth rates of the eastern region are significantly higher than those of the central and western regions. On the whole, the inter-provincial differences in carbon emissions of China's logistics industry have not changed substantially and have shown a downward trend. Intra-regional differences are the main reason for the overall difference in carbon emissions in China's logistics industry, and inter-regional differences have little impact on the overall difference. Among the three major regions, the eastern region has the largest inter-provincial carbon emissions difference, followed closely by the central region, with the western region having the smallest difference. Furthermore, the difference in carbon emissions between the eastern, central, and western regions is expanding, the results of the LMDI model show that the economic development effect is the most important positive effect of the logistics industry's carbon emissions in terms of the national average. The population scale effect is second, and the energy intensity effect is the main negative effect, followed by the energy structure effect. In terms of regional differences, the energy intensity effect is the most obvious in the eastern region, and the population scale effect has a relatively greater impact on the western region. The effect of economic development on the eastern and western regions is higher than in the central region. [ABSTRACT FROM AUTHOR]

In order to explore the comprehensive assessment method of air quality of pollutant emission of energy consumption in China's urban internal industrial parks, based on the full consideration of the actual situation of air pollution control in Nanjing HX Industry Park, this paper selects 15 air quality assessment indicators. According to the national air quality standard, the air quality standard of Nanjing and the air quality standard of Nanjing HX Industry Park, the air quality assessment standard is determined about pollutant emission of energy consumption in Nanjing HX Industry Park. Through the technical treatment of the selected assessment indicators, the niche suitability model is introduced, and based on this, the spatial niche suitability model is reconstructed to comprehensively assess the air quality of pollutant emission of energy consumption in Nanjing HX Industry Park. The study found that the air quality of Nanjing HX Industry Park has been improved from level III in 2012 to level I in 2020. According to the assessment results, the differences of assessment results of different niche suitability models are discussed, which fully reflects the advantages of spatial niche assessment methods. The change law and influencing factors of the assessment results are further discussed. [ABSTRACT FROM AUTHOR]

At present, China is the world's largest energy consuming country and industrial manufacturing country, especially industrial enterprises are the main energy consumers. The steel industry occupies an important position in China's national economy, and has the characteristics of high energy consumption, high pollution and high emissions. Therefore, based on the perspective of energy management, this paper selects 54 large-scale steel companies from China Iron and Steel Association from 2009 to 2017 as a sample, and applies the SBM super-efficiency model that includes undesired output and the differences-in-differences (DID) method to explore the impact of companies implementing energy management systems on corporate performance. The empirical results show that: the implementation of energy management system has a positive impact on enterprise performance. Moreover, the impact of energy management system on economic performance is greater than that on environmental performance. Through the analysis of regional heterogeneity and ownership heterogeneity, it is further found that the implementation of energy management system in eastern region enterprises and state-owned enterprises has a more obvious impact on enterprise performance. The results of this paper can encourage those managers who want to apply energy management system in enterprises to achieve sustainable development, so as to improve the efficiency and results of energy management. [ABSTRACT FROM AUTHOR]

To explore the effect of financial development on energy efficiency is of guiding significance for grasping China's energy situation and making fiscal policies. First, this paper considers the environmental pollution into the output variables, and builds an SBM model to evaluate the energy efficiency. Second, this paper explores the dual effect of financial development on energy efficiency, and based on the interaction characteristics of multiple factors, the configuration of energy efficiency is discussed by using fsQCA method. The results are as follows: there are obvious differences in energy efficiency in different regions, with a declining trend from eastern to western. Regions that achieve high energy efficiency tend to have better financial development and industrial structure. When financial development and industrial structure are relatively good, regions should consider the role of FDI and give full play to its spillover effect. Regardless of financial development, regions should steadily achieve economic growth, attach importance to innovation input and correctly guide foreign investment. [ABSTRACT FROM AUTHOR]

In order to explore effective ways for energy conservation and emission reduction, seven correlated variables are selected in this paper according to the government statistics with the extended STIRPAT model, and the impact of China's industrialization and urbanization on carbon emission intensity of energy consumption is studied. The study found that urbanization rate and urban population employment rate are the main factors affecting per capita carbon emission of energy consumption in China;the industrialization has a reverse impact on per capita carbon emission of energy consumption, indicating that China's industrialization is relatively low and is not the main factor affecting per capita carbon emission of energy consumption; the service industry added value rate and the agricultural industry added value rate also have reverse effects on China's per capita carbon emission of energy consumption, and the degree of impact is relatively small. Therefore, China is supposed to develop industry vigorously in the future, to appropriately control the development speed of urbanization and to increase the agricultural industry added value rate moderately, so as to achieve effective control of per capita carbon emission intensity of energy consumption. [ABSTRACT FROM AUTHOR]

The rapid development of China's logistics industry is accompanied by the deterioration of the ecological environment and excessive energy consumption. Therefore, how to effectively measure and improve the green total factor productivity (GTFP) of the logistics industry is an important guarantee for achieving the coordination of the logistics industry development and the ecological environment protection in the high-quality development stage. This study evaluated the logistics industry's GTFP of 30 provinces in China from 2004 to 2017 using the Epsilon-based measure model (EBM) and global Malmquist-Luenberger index (GML). Then, this paper applied the geographically and temporally weighted regression (GTWR) to analyze the spatiotemporal non-stationarity of influences of driving factors on GTFP. There are three main conclusions drawn in this paper. Firstly, the GTFP of the logistics industry has significant spatial and temporal differences. From a temporal perspective, the GTFP has undergone a process of alternating changes in ascent and descent. From a spatial perspective, the GTFP has an obvious "east-central-west" gradient decreasing trend. Secondly, compared with the ordinary least squares (OLS) and the geographically weighted regression (GWR), GTWR performs best in terms of goodness of fit. Thirdly, the regression results of GTWR indicate that the influences of factors have different directions and intensities on GTFP in the logistics industry at different times and regions, showing obvious characteristics of spatiotemporal non-stationarity. Finally, some practical recommendations are put forward in this paper. [ABSTRACT FROM AUTHOR]

It is of great significance to improve Total Factor Energy Efficiency (TFEE) for China's energy saving, emission reduction and ecological protection. This paper focuses on the calculation and decomposition of TFEE of eight economic regions in China considering the effects of undesirable outputs. The TFEE values of the eight economic regions in China are calculated via the input-oriented radial CRS super-efficiency SBM model. In order to overcome the shortcomings of the traditional ML index, this paper firstly builds an improved ML index using MinDS function, then decomposes the TFEE values through Zofio decomposition analysis method, and then identifies the driving factors of TFEE via Tobit model, and finally clarifies the path of improving TFEE in the economic regions. The findings show that the TFEE values of the eight economic regions in China are basically higher in the southeast and lower in the northwest. The dominant factor affecting the TFEE values in the eight economic regions is industrial structure, followed by technological development level. The research conclusions of this paper can provide reference for the formulation of policies for energy conservation and ecological protection. [ABSTRACT FROM AUTHOR]

The equipment manufacturing industry is not only a high-carbon industry, but also an important export industry in China. There is a close relationship between the export growth of China's equipment manufacturing industry and its carbon emissions. Based on this, this paper focuses on the equipment manufacturing industry, and establishes a Tapio model to combine the decoupling theory with export carbon emissions. Meanwhile, the relative advantages and disadvantages of the eight decoupling modes are evaluated and determined. Then, the decoupling elasticity index and the decoupling grade index are used to analyze the carbon emissions of China's equipment manufacturing industry and its seven sub-sectors. The study implies that, from 2000 to 2018, the relationship between the overall carbon emissions of the equipment manufacturing industry and export growth was decoupling, and most of the sub-sectors were basically in the state of strong decoupling or weak decoupling. Therefore, the two decoupling optimization paths, which are increasing economic growth and decreasing energy consumption, are designed here to further improve the decoupling effect between the export growth of China's equipment manufacturing industry and its carbon emissions. [ABSTRACT FROM AUTHOR]

Due to the gradual agglomeration of economic activities and the continuous reinforcement of spatial linkages in specific geographic locations, the geospatial factor should become an important starting point to understand the relationship between industrial restructuring and energy conservation and emission reduction. This paper first introduces a non-separable hybrid DEA model that considers undesirable output to measure the energy efficiencies of 285 prefecture or higher-level cities in China during 2003-2016; then, a dynamic spatial panel model is used to investigate the influence of different types of industrial agglomerations and agglomeration modes on energy efficiency. According to the obtained study results, for the investigation period, the overall energy efficiency of China with regard to pollutants remained at a low level and presented a "U-shaped" decreasing-increasing trend. To be specific, China's energy efficiency distribution presented a trend of "high in the east and low in the west." The energy efficiency of East China changed relatively gently, while the energy efficiencies of central China and western China changed dramatically. China's energy efficiency also presented a significant spatial agglomeration effect, i.e., cities with close energy efficiencies are usually adjacent to each other. At the national level, agglomeration of the manufacturing sector significantly inhibited the increase of energy efficiency; the agglomeration of the producer service sector and the co-agglomeration of the manufacturing sector and the producer service sector both facilitated an increase of energy efficiency. The influence of industrial agglomeration on energy efficiency differed across different city scale grades. Based on these conclusions, the paper proposes the following policy implications: 1) make full use of the energy savings and emission reduction effect of agglomeration; 2) accelerate the optimization of industrial layout; 3) develop high-end service industry and productive service industry; and 4) create an agglomeration environment that encourages benign industrial competition. [ABSTRACT FROM AUTHOR]

This paper uses the super-efficiency DEA model to study the super-efficiency energy efficiency values of 30 provinces in China from 2006 to 2018, compares the differences between different regions, and verifies the impact of different environmental regulatory tools on energy efficiency. The results show that the regions with the highest energy efficiency in China's provinces are, in order, the eastern region, the central region, and the western region. At the same time, the impact of different environmental regulatory tools on energy efficiency is quite different. The number of environmental administrative penalties has a negative impact on China's energy efficiency, that is, increased number of environmental administrative penalties will reduce China's energy efficiency; market-encouraging environmental regulations tools impact on China's energy efficiency show a positive correlation, which means that market-encouraging environmental regulation tools are conducive to achieving a win-win goal of environmental regulation and energy efficiency in China. The voluntary environmental regulation tool has a negative correlation with energy efficiency, but it is not statistically significant, indicating that it is not the main factor affecting energy efficiency. In terms of other influencing variables, the level of economic development and technological progress are positively related to energy efficiency. The proportion of the secondary industry in regional GDP is positively related to energy efficiency, the relationship between energy consumption structure and energy efficiency is negative correlation, the degree of opening to the outside world has a negative correlation to China's energy efficiency. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, CO2 emissions have surged and environmental pollution has become increasingly serious, drawing broad attention domestically and overseas. To improve China's environmental quality, the Chinese government has set a series of ambitious goals to control carbon intensity and even cut total CO2 emissions. China's energy consumption structure relies heavily on coal, which is the largest contributor to CO2 emissions in China. However, so far research on the relationship between energy consumption structure and CO2 emissions in China remains scarce. This paper investigates this topic for the first time and calculates the input-output and alternative elasticities and impacts the energy consumption structure on carbon emissions per capita on the basis of the translog production function as the theoretical framework. The empirical results suggest that to substitute coal with oil or gas may decrease CO2 emissions significantly, and replacing coal with gas is the optimal choice. As such, improving China's energy structure by increasing the share of gas and decreasing the reliance on coal would cut China's CO2 emissions remarkably and benefit China's environmental quality. [ABSTRACT FROM AUTHOR]

As China has committed to the international community to effectively control CO2 emissions, it is necessary for the regions of China to launch an in-depth analysis about energy use and CO2 emission efficiency. In this paper, each province of China will be regarded as an independent decision-making unit. After judging their return to scale state by the traditional DEA theoretical model, we use the SBM and RE/CE models, which respectively solve the problems of slack variables, and the traditional model does not reflect factors such as price, which is truly existing. Then we get a more comprehensive efficiency that reveals Chinese energy use and the CO2 emissions situation. From the empirical study of 30 regions in China, we know that the southern region of China has the most efficient score while northeastern China has poor performance. Price factor has a significant influence on energy use and CO2 emissions efficient score of some provinces. Our study shows that northern and northeastern China should make more of an effort on energy consumption reduction in order to improve the efficiency score. Instead, northeastern and central China should pay more attention improving energy conversion technology in order to increase their efficiency. [ABSTRACT FROM AUTHOR]

With the continuous improvement of the economy, more and more attention has been paid to environmental problems. Beijing is China's economic, political, and cultural center, and its low-carbon development by external concerns. In this paper, the relationship between economic development and environmental pollution is analyzed by using the symbolic regression method, which is based on the data of per capita CO2 emissions, total energy consumption, energy intensity, and per capita GDP in Beijing city during 1980-2015. The study found that the presence of the M-curve model between per capita CO2 emissions and per capita GDP, total energy consumption, and per capita GDP are in line with the traditional model of the EKC curve, and that the L-curve model exists between the energy intensity and per capita GDP, respectively, with promising performance. Based on our analysis, we present policy suggestions for reducing carbon emissions and developing a low-carbon economy in Beijing. [ABSTRACT FROM AUTHOR]

This paper measures energy efficiency in China using the three-stage data envelopment analysis (DEA) model and then tests the convergence of China's energy efficiency. The study finds that environmental factors and random factors both have significant impacts on energy efficiency. After eliminating the influences of environmental and random error factors, the results present that the pure technical efficiency improves and the scale efficiency decreases, but pure technical efficiency is far lower than scale efficiency in terms of energy utilization, which indicates that low pure technical efficiency is the main factor constraining China's energy efficiency. China's energy efficiency presents obvious regional differences, and the energy efficiency in eastern regions is higher than that in midwestern regions. Based on the matching relationship between energy efficiency and input level, China can be regionally divided into four energy utilization modes: high efficiency and high input mode, high efficiency and low input mode, low efficiency and high input mode, and low efficiency and low input mode. Nationally, the difference in regional energy efficiency should maintain a relatively high level in the short term; divergence occurs in terms of pure technical efficiency and overall technical efficiency, while scale efficiency manifests a significant absolute convergence feature. Differential energy strategy should be carried out according to the features of different districts. Eastern regions should decrease the dependence on external energy, and develop advanced techniques with lower energy consumption. The improvement of energy efficiency in Midwest regions should depend on changing a traditionally highly energy-intensive industrial structure, undertaking clear industrial transfer from the east, excavating latent energy savings with the high-energy industry sector, and accelerating the transformation to an intensive pattern. Strengthening the energy corporation of China not only enhances energy efficiency in eastern regions but also improves energy efficiency in midwestern regions by spillover effect. Accordingly, it could improve energy efficiency balance and robustness. [ABSTRACT FROM AUTHOR]

This paper proposes a metafrontier non-radial and non-oriental DEA to examine environmental efficiency in China. This approach takes the regional technology heterogeneity, non-radial slacks, and undesirable outputs into consideration simultaneously. The results show that undesirable output inefficiency largely contributes to environmental inefficiency. And under the metafrontier technology assumption, the technology gaps between three regions have been widened. Technology gap ratio, factor endowment level, and environmental governance capacity have a positive impact on TFEE, while industrial structure, foreign capital reliance, and energy consumption structure show the negative effect on it through two-stage regression analysis. This result suggests that emission reduction stress in China is greater than the energy savings stress in the future. [ABSTRACT FROM AUTHOR]