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China's paper industry accounts for a larger proportion of the global paper industry and consumes large amounts of energy. Energy conservation and pollution reduction of the industry have become the focus of China's national development strategy. Energy efficiency is an important index which directly determines the amounts of energy consumption and pollution emissions. To understand the energy efficiency evolution of China's paper industry, this paper establishes an input-output data of the paper industry for 29 provinces in China and applies DEA method and econometric models to estimate and comprehensively discuss the energy efficiency issues based on the framework of total factor efficiency. Our results indicate that China's paper industry has a large energy saving potential even though its energy efficiency has improved during the period 1990–2013. The saving potential is about 65% under the meta-frontier and 44% under the group-frontier. Moreover, there are significant differences between different regions in production technology and energy efficiency. The performance of eastern China is better than other regions. But the technology gaps between the different regions are shrinking and converging over time. Finally, some policy recommendations are proposed to improve the energy efficiency of the industry. [ABSTRACT FROM AUTHOR]

The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the water-energy-food nexus (WEFN) system, focusing on its interlinked structure and dynamic characteristics. This paper proposes a dynamic series-loop data envelopment analysis (DEA) model with a directional distance function for measuring WEFN efficiency in China. A spatial Durbin model is constructed to investigate the impact of extreme temperatures on WEFN efficiency. The results are as follows. (1) Compared with the black-box DEA model and series network DEA model, a series-loop network DEA model can reflect the "networking effect" and "looping effect" in the WEFN system. (2) The WEFN system performs well with an average series-loop efficiency of 0.875, but the efficiency of the water subsystem scores low and needs improvement. (3) At the national level, extremely high and low temperatures have no significant effect on the WEFN efficiency in local or adjacent provinces, whereas average temperature promotes the WEFN efficiency in local provinces but hinders it in neighboring provinces. In the regions with a low temperature difference, average temperature has no impact on the WEFN efficiency of both the province itself and its neighboring provinces. Overall, this study provides valuable insights into the complex interlinkages within the WEFN system and highlights the importance of considering these relationships when improving the system efficiency. [ABSTRACT FROM AUTHOR]

An increasing amount of resources is being utilized to combat the pollution problem in China. Measuring and improving the efficiency of this resource allocation is an effective way to promote pollution treatment at the present technical level. This paper utilizes a two-stage data envelopment analysis (DEA) model to attain allocation results based on the zero-sum gain and fixed-sum gain assumptions. We divide all the inputs into discretionary and non-discretionary inputs and construct two models for allocating resources based on the environmental efficiency scores. The new models are applied to calculate the performance and resource allocation scheme of 30 Chinese provinces from 2011 to 2015. Most provinces are inefficient at controlling pollution emission or treating pollution while using the given level of input resources. Based on the production possibility set of each province in 2015, the processing capacity of wastewater and gas could be increased by 1% and 3%, respectively, by reallocating resources for pollution treatment among different provinces. Environmental efficiency scores and resource allocation plans based on various assumptions are obtained in this paper to enlighten the corresponding decision-makers. Image 1 • The paper constructs two resource allocation models based on the DEA approach. • This research considers the allocation of public pollution treatment resources between different sectors. • Two strategies for resource allocation are composed to deal with different conditions relating to resources. • We apply the new models to measure the performance of 30 regions in China. [ABSTRACT FROM AUTHOR]

The metal industry (MI) in China is energy and emissions intensive. This paper tries to provide guidance for the green development transformation of China's MI, by investigating the green total-factor productivity (GTFP) and its influencing factors using a global data envelopment analysis and a spatial Tobit regression model. The estimation results show that: (1) from 2000 to 2015, GTFP of China's MI enjoyed a considerable improvement. However, the current value of GTFP of China's MI is still less than 0.5, indicating that GTFP of China's MI is far from efficient; (2) the spatial correlation test shows that GTFPs of China's provincial MIs have positive spatial correlations. Most of the provinces scattered in "high-high" and "low-low" agglomerations; (3) GTFP of China's MI is significantly positive related to the degree of marketization, fiscal decentralization, environmental regulation, industrial scale, is significantly negative related to resources endowment and product structure, and has "U" shaped relationship with the level of economic development. The above results suggest that China already has made remarkable achievements in promoting green development of its MI. However, there is much room for further improvement. Policy options for the green development transformation of China's MI include but are not limited to promoting market-oriented and financial system reforms, strengthening environmental supervision, and optimizing industrial scale and product structure. Finally, recommendations for the effective implementation of these policies are provided at the end of the study. • This paper analyzed the historical performance and influencing factors of GTFP of China's MI. • Results show that GTFP of China's MI achieved considerable improvement in the past few years. • However, the current level of GTFP of China's MI is still very low. • There are many effective policy options for further promoting GTFP growth of China's MI. • Some implications for the implementation of these policies are provided in this paper. [ABSTRACT FROM AUTHOR]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [ABSTRACT FROM AUTHOR]

Considering both regional heterogeneity and industrial heterogeneity, this paper proposes a three-hierarchy meta-frontier data envelopment analysis (DEA) to decompose energy efficiency and energy-saving potential into three components, i.e., industrial structure, regional balance development, and management. Based on this approach, the paper then analyses the historical evolution and current status of energy efficiency in China. The results show the following. (1) From 2001 to 2015, Mainland China's energy efficiency increased by a factor of 2.48, primarily because of technological progress and the optimization of its industrial structure. (2) Nonetheless, the current energy efficiency in Mainland China remains very low and energy inefficiency is as high as 0.5922, indicating that 59.22% of total energy consumption is invalidly used. Severe industrial structure inefficiency and regional balance development inefficiency are the two main factors responsible for the very low energy efficiency. (3) By promoting industrial restructuring, regional balance development, and management improvement, Mainland China is expected to save, respectively, 13.67%, 24.54%, and 61.73% of its current total invalid energy consumption. Based on the estimation results, this paper formulates strategies to improve energy efficiency and save energy for China's provinces based on their specific situations, considering not only the direction of industrial restructuring in both the short and long terms but also the path to improved energy efficiency. In addition, a brief discussion about the applicability and the preconditions for an application of the multi-hierarchy meta-frontier approach is given at the end of the paper. [ABSTRACT FROM AUTHOR]

In the face of environmental degradation, sustainable development has become a common goal across the globe. Making a scientifically based investment scheme is of great significance to promote the sustainable development of China's economy. However, there is scarce research related to such an investment scheme of sustainable development. This paper proposes a new inverse data envelopment analysis method with undesirable outputs to make several scientifically based investment schemes from different perspectives, namely, the natural, regulation, and optimal perspectives. By this method, decision makers can scientifically forecast the specific amount of investment based on their actual sustainable development objectives, which is conducive for reducing the blindness of investment in the future. In addition, a new ideal perspective is defined to guide a definite direction for improving the level of sustainable development. Combined with the gray forecasting model GM(1,1), the methods proposed by this paper were then applied to analyze the investment problem for China's sustainable development during the 2015–2024 period. The results show that: the unbalanced distribution of labor investment and the excessive investment in capital and energy are serious barriers to China's sustainable development in the short term; and in the long term, the demand for investment in labor and capital will continue to increase along with a lower demand for energy investment, and that appropriately strengthening environmental regulations will not affect the overall demand for investment. Meanwhile, improvement directions for improving China's sustainable development are discussed, and the results show that most of developing and undeveloped regions in China have great potential for improvement. Finally, some suggestions are proposed in order to create better conditions for China's sustainable development. [ABSTRACT FROM AUTHOR]

The development of China's forestry resources has never been more challenging due to serious problems such as shortage, inferiority and uneven distribution of forestry resources. Therefore, the study and evaluation of China's forestry resources has a great significance to improve efficiency and ensure the sustainable development of the forestry resource. Meanwhile, the vast territory, huge population and widespread forest landscape of China have led to the numerous indexes and the huge data. To perform the research and evaluation accurately, this paper utilized the big data theory to analyze the relevant data of China's forestry resources. This study collected the data from 31 inland provinces and municipalities of China from 2005 to 2013, after which we carefully examined economic, social and ecological factors to choose assessment indexes and processed data accordingly. Firstly, we performed a cross-sectional dataset analysis using the method of data envelopment analysis to investigate the forestry resources efficiency in 31 inland provinces and municipalities of China in years 2008, 2012 and 2013. Secondly, we analyzed time series data of the 31 inland provinces and municipalities from 2005 to 2013 using the Malmquist total factor productivity index method. Our results showed the dominant factor that restraining forestry resources efficiency for the 31 inland provinces and municipalities is the implemented technology. So we suggest increasing the investment in science and technology to improve the overall efficiency of forestry resources, along with improvement of operation and management by relevant administrative departments to improve technology utilization. The innovation of this paper lies in the dynamic process of analysis. [ABSTRACT FROM AUTHOR]

Environmental efficiency improvement has played a crucial role in the theory and practice of stimulating clean production. This paper analyzes the interaction between environmental efficiency and output efficiency, particularly whether they reinforce each other or compete with each other, on the basis of a data set of 137 firms in the textile industry in China's Jiangsu Province. In the first stage, generalized data envelopment analysis is applied to calculate efficiency measures of energy, waste water, waste gas, soot, and output efficiency taking capital, labor, water, and energy as inputs, industrial output value as desirable output, and waste water discharges, waste gas and soot emissions as undesirable outputs. In the second stage analysis, a structural equation model with latent variables is applied to analyze the interaction between the latent variable environmental efficiency, measured by the four observed environmental indicators, and output efficiency, taking also into account the endogenous variable profit. The main outcomes of the structural equation model are the following. Firstly, environmental efficiency negatively impacts on profit while profit positively impacts on environmental efficiency. In a similar vein, output efficiency is found to depress profit while profit increases output efficiency. Thirdly, environmental efficiency has a positive impact on output efficiency while there is no effect of output efficiency on environmental efficiency. Fourthly, taxes impair a firm's output efficiency. From the findings it follows that a swap of general taxes for an energy tax is likely to improve both output efficiency and energy efficiency. The latter outcome implies a win–win situation which will facilitate the further implementation and adoption of environmental policy. Finally, the paper illustrates the applicability of structural equation modeling in efficiency analysis. [ABSTRACT FROM AUTHOR]

The process of a regional industrial system in China can be separated into two internal stages: production stage and pollutant abatement stage. This paper aims to examine the efficiency of Chinese regional industrial systems by taking the operational performance of its two internal stages into consideration. Unlike traditional data envelopment analysis models that treat decision making units as “black box” when measuring their efficiencies with undesirable factors, this paper proposes a two-stage model based on slacks-based measure to evaluate the efficiency of Chinese regional industrial systems. By decomposing the efficiency into production efficiency and abatement efficiency, the proposed model can estimate the efficiencies of the whole regional industrial system, its production stage and abatement stage simultaneously. The model provides a way of improving performance of a regional industrial system through identifying its inefficient internal stages. This can help to find out the main sources of the inefficiency that arise from the internal stages within the system, which cannot be done by using conventional environmental data envelopment analysis models. Findings resulting from the model application show that there are great disparities in regional industrial systems' efficiencies, and the inefficiency of Chinese industrial system is largely driven by the abatement stage. [ABSTRACT FROM AUTHOR]

Obtaining the most economic benefits while using the least resources and causing the least environmental damage is an urgent and key problem in achieving sustainable development. The concept of eco-efficiency provides a comprehensive perspective for observing and solving this problem. This paper proposes an extended data envelopment analysis model, named the WIN-US-SBM, as a comprehensive eco-efficiency evaluation method that can accommodate undesirable outputs, all the identification problems of decision-making units (DMUs), possible slacks of variables, and the problems of an insufficient number of available DMUs and intertemporal comparability. China's Western Taiwan Straits Economic Zone (WTS Economic Zone) is an important regional economic growth center. By applying WIN-US-SBM and ArcGIS software, we investigated data on the temporal and spatial evolution characteristics of eco-efficiency in the WTS Economic Zone for the years 2009–2016. Later, the global Malmquist–Luenberger index was used to decompose the sources of growth in eco-efficiency. Finally, the main driving factors of eco-efficiency were explored through a Tobit regression analysis. The empirical results show that: (1) The overall eco-efficiency of the WTS Economic Zone had greatly improved, increasing by 11.46% annually, and the cumulative growth rate of eco-efficiency was 110.84% from 2009 to 2016. (2) The eastern area had the highest average eco-efficiency, followed by the western area and the middle area in that order. Also, the growth rate of the middle area ranked first (16.68%), whereas the eastern area had the slowest growth in eco-efficiency (7.22%). (3) On the whole, the growth of eco-efficiency was driven mainly by technological progress and was restricted by the decrease in management level, which implies that policy makers should focus on improving management and technical levels. (4) High levels of economic development, population density, market openness, and industrial structure had positive effects on the eco-efficiency of the WTS Economic Zone, whereas energy intensity and expenditure on science and technology had negative impacts. • An extended DEA model is proposed to measure eco-efficiency more comprehensively. • The proposed model can be widely applied to input-output efficiency evaluations. • The eco-efficiency of the WTS Economic Zone was evaluated based on a novel model. • The growth of eco-efficiency was driven mainly by technological progress. • The eco-efficiency level is negatively related to energy intensity. [ABSTRACT FROM AUTHOR]

In recent years, the profit growth of wind power enterprises in China is generally weak, and the phenomenon of "wind curtailment" in some areas is relatively common. The comprehensive evaluation of wind power performance in various regions of China and the study of the driving forces of wind power performance differences in different regions are of great significance for scientific planning and layout of wind power investment. Based on the panel data, this paper combines Data Envelopment Analysis (DEA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to establish an evaluation model to evaluate the wind power performance of China's 29 provinces and cities from 2011 to 2018. Then uses the evaluation results as input data of Adaptive Neuro-Fuzzy Inference System (ANFIS) prediction model to predict the wind power performance of 2019 in various regions of China under the current policy and environment. Finally, the main factors affecting the performance of China's wind power generation are explored by establishing a regression model. The research results show that at present, the main factors affecting the performance of China's wind power generation are local power consumption capacity, economic development degree and the rate of wind abandonment. On the premise of solving the problem of wind curtailment, appropriately promoting power consumption and renewable energy policy reform, from Feed-in-Tariff (FiT) to a Renewable Portfolio Standard (RPS), are effective means to promote the development of wind power generation in China. Image 1067 • In wind-intensive areas, wind power performance levels are relatively low. • Power consumption capacity and wind curtailment rate are the main influencing factors. • Current policy cannot effectively solve the problem of wind curtailment. • Renewable energy policies with regional differences should be adopted. [ABSTRACT FROM AUTHOR]

Abstract: The rapid economic development of China has intensified the country's environmental problems such as pollution and waste. As industry is the main contributor to environmental deterioration, the development mode of industry has attracted attention from the government and the public. In this paper, we have assumed that the industry is permitted a fixed total amount of pollution in order to avoid excessive pollution. If one province shows increased pollution, other provinces are required to reduce pollution by the same amount to maintain the total level of pollution. However, so far, few studies have considered such competition over outputs. This paper presents a new data envelopment analysis approach, which considers both the fixed and the variant sum desirable outputs in the performance improvement of a decision making unit, to evaluate the environmental efficiencies of China's industry from 2007 to 2011. The analysis results demonstrate that some economically developed provinces have better performance than less developed provinces; in particular, all efficient provinces are the developed ones. The Chinese government should focus on the increasing differences in environmental efficiencies among regions and take measures to address them. [Copyright &y& Elsevier]

Alleviating energy poverty is a significant issue in many countries, for which effective energy poverty measurement is the prerequisite. This paper seeks to make a comprehensive and systematic assessment of the energy poverty performance of 30 provinces in China for 11-year period (2007–2017) by emphasizing their spatial-temporal changes. The paper firstly constructed energy poverty measurement conceptual framework based on overviewing previous studies. Secondly, a technique based on the integrated fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) and Data Envelopment Analysis - Assurance Region (DEA-AR) for performance assessment was proposed. Then, the energy poverty performance was assessed, and clustering analysis was conducted to investigate the spatial-temporal changes of energy poverty in China. Finally, sensitivity analysis was applied for verifying the robustness of the proposed method. It is found that the energy poverty condition in China tends to be similar among most regions, but the gap between the best and worst performers gets wider. In addition, provinces with better economic conditions, have higher performance and are classified into the progressive group for alleviating energy poverty. On the contrary, provinces, whose economy lags, have regressed the most and are also the worst performers in reducing energy poverty. Thus, policies to improve household energy cleanability in high-income provinces and increase energy affordability in low-income regions would help reduce energy poverty in China. • A comprehensive energy poverty assessment framework was proposed. • An integrated Fuzzy DEMATEL/DEA-AR was proposed to evaluate the performance. • The comparison between the proposed Fuzzy DEMATEL/DEA-AR model and conventional DEA was conducted. • Spatial and temporal analysis of energy poverty performance in China was conducted. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of the implementation of smart city policy (SCP) on energy efficiency (EE) in China. For this purpose, we have developed a non-convex metafrontier data envelopment analysis (DEA) approach to measure EE, and empirically examine the impacts of SCP on China's EE using Difference-in-Differences (DID) analysis, using a dataset of 251 cities between 2003 and 2016. Results show that there exists significant regional heterogeneity across cities, with the SCP exerting a significant positive effect on EE, indicating that the SCP can effectively improve EE during the study period. These findings are robust to different sub-sample, energy efficiency alternative measures, estimation strategies, and Baidu Search Index. Based on empirical results, the implications of SCP are outlined. • Energy efficiency measures of 251 Chinese prefectural-level cities are estimated. • Eastern region performs the best, followed by the central and western regions. • The effects of smart city policy on energy efficiency is investigated using DID method. • The smart city policy can effectively improve energy efficiency during the study period. • Empirical results are robust to different sub-sample, energy efficiency alternative measures, etc. [ABSTRACT FROM AUTHOR]

China has developed a remarkable economic growth in the past 30 years by accompanying with undesirable outputs. The assumptions of weak and strong of undesirable outputs have become the focus discussion in data envelopment analysis (DEA) models. To have a comprehensive environmental efficiency measurement, this paper proposes three DEA models considering weak disposability, strong disposability and distinguishing weak and strong disposability of undesirable outputs, respectively. We further combine with the Malmquist-Luenberger productivity index to assess the environmental efficiency and the dynamic change trend of 30 provinces in China from 2005 to 2014. The results show that distinguishing technical features of undesirable outputs makes a significant difference to final environmental efficiency score at different regions. The environmental efficiency of the whole nation, however, does not show any increasing trend during the ten years. Enhancing environmental efficiency of central and west area is an urgent task for Chinese government. The change trend of Malmquist-Luenberger productivity index and technological change shows a similar shape. Technical progress is the main driving force to enhance the environmental efficiency. Relevant suggestions are presented for improving the regional environmental efficiency in China in the future. [ABSTRACT FROM AUTHOR]

Abstract China is the world's largest producer and consumer of non-ferrous metals, and the non-ferrous metals industry is energy- and emission-intensive. The CO 2 emissions of the industry have increased nearly four times from the level in 2000 to reach 310 million tons in 2014. To cope with the issues of CO 2 emission and other environmental problems under the background of low-carbon development, it is necessary to analyze the CO 2 emission performance of China's non-ferrous metals industry. Based on group heterogeneity, this paper uses data envelopment analysis to calculate the Shephard distance function and then uses the Shephard distance function and non-parametric meta-frontier methods to construct the meta-frontier Malmquist CO 2 emission performance index (MMCPI) of China's non-ferrous metals industry during the period 2006–2014. The index is further decomposed into three parts: technical efficiency change, technological progress change and technological catch-up effect. The results showed that the MMCPI of China's non-ferrous metals industry exhibits an upward trend during the review period. The improvement in CO 2 emission performance is most significant in the central region, followed by the eastern and western regions. Based on the decomposition of MMCPI, the effect of technological progress are significantly different for the different regions, indicating that more targeted policies are need for different regions. [ABSTRACT FROM AUTHOR]

Abstract In recent years, urban energy efficiency has received much attention from researchers. However, ignorance of the competitive relationships among regions results in inaccurate energy efficiency. Game cross-efficiency data envelopment analysis (DEA), which can account for the competitive relationships, is a reliable method to measure energy efficiency. First, this paper applies game cross-efficiency DEA to analyze the urban total factor energy efficiency (UTFEE) of 26 Chinese prefectural-level cities from 2005 to 2015 under environmental constraints. Then, a comparative analysis and a concrete analysis are conducted based on the urban energy efficiency. Finally, a Tobit model is used to examine the effects of 10 potential influence factors. The measurement results show that the urban energy efficiency considering the competitive relationship is lower than the traditionally calculated efficiency. Additionally, the urban energy efficiency did not improve during the research period. Furthermore, regression analysis suggests that economic development and city scale can promote urban energy efficiency, while government expenditure, industrial structures, energy prices, foreign investments, research investments and production endowment have negative impacts on urban energy efficiency. According to our results, some implications of theory and practice are discussed for researchers and policy makers. [ABSTRACT FROM AUTHOR]

Abstract Improving CO 2 emissions efficiency has become a crucial task faced by China to develop a low-carbon economy and choose a CO 2 emissions mitigation path. Existing researches have focused on estimating national CO 2 emissions efficiency, but have ignored the industrial heterogeneity in the region or explanation for inefficiency. To fill the gaps, this paper applies a metafrontier-Malmquist index analysis method combined with a three-level common frontier model to comprehensively estimate and decompose the carbon emissions efficiency and dynamic changes of China's industries and regions during 2010–2015. First, we use data envelopment analysis with directional distance function by considering three-level frontiers to calculate CO 2 emissions efficiency. Results show that China's overall CO 2 emissions efficiency is at the middle level with an average value of 0.511. The efficiency of CO 2 emissions in the eastern region is the highest, followed by the central and western regions, and the CO 2 emissions efficiency in the tertiary industries is greater than that in the primary and secondary industries. Second, we decompose CO 2 emissions efficiency into technological, industrial and management efficiency, and found that management efficiency is the main reason for low CO 2 emissions efficiency in developed regions and industries. Third, the Malmquist-Luenberger index is utilized to decompose CO 2 emissions efficiency into 9 items, and we obtained that continuous technological progress is the leading cause driving different degrees of improvement in CO 2 emissions efficiency. Graphical abstract Image Highlights • Apply non-radial model to estimate CO 2 emissions efficiency of China. • Use industrial, technical and managerial efficiency to explain inefficiency. • Build three-level metafrontier-Malmquist-Luenberger index to discuss dynamic changes. • Eastern region and tertiary industry have the highest CO 2 emissions efficiency. • Continuous technological progress is the main reason for gaps of efficiency. [ABSTRACT FROM AUTHOR]

Abstract Carbon emissions trading is one of the important economic means to solve the environmental externality. Based on the data of CO 2 emissions from the thermal power plants over the period from 2005 to 2010 in China, this paper uses no-parametric optimization models to estimate the potential economic gains and potential carbon emissions reduction under three allocation strategies of carbon emissions trading allowance. Results show that the maximum potential gains can be obtained by the spatial allocation scenario for the combination of CO 2 -SO 2 emissions trading, and the output growth ratio among power plants varies huge. The establishment of jointed CO 2 -SO 2 emissions trading is usually highly beneficial to achieve the three targets, including the optimal allocation of resources, the increase of potential gains and the reduction of pollutant emissions. [ABSTRACT FROM AUTHOR]

Abstract The green efficiency of water resources is important for industrial cleaner production and sustainable development. Existing studies pay much attention to the economic efficiency of water resource utilisation, ignoring its green efficiency. In order to solve this problem, an index of green total factor water efficiency (GTFWE) that can reflect the economic efficiency and green efficiency of water resources is constructed based on the DEA-SBM model with undesirable output. In addition, GTFWE is comprised of green total factor water management efficiency (GTFWME) and green total factor water environmental efficiency (GTFWEE) using the four-stage DEA model. The empirical results show that GTFWE in China's industry is at a low level, the effect of GTFWEE on GTFWE is generally increasing, and GTFWME is decreasing. However, there are large differences in these trends between regions and provinces in China. The GTFWME of Beijing, Tianjin, and seven other provinces needs improvement, while the GTFWME and GTFWEE of Hebei, Inner Mongolia, and other 15 provinces is low and also need improving. In contrast, both GTFWME and GTFWEE are high in the Shandong and Guangdong provinces. This paper provides a method for assessing GTFWE in China's industry and proposes some important policy implications for promoting the efficiency of China's industrial green total factor water resources. [ABSTRACT FROM AUTHOR]

Abstract Technology advances are considered to be effective in reducing carbon emissions. However, studies show that the effect of such advances on reducing carbon emissions is not as effective as expected, owing to the existence of the rebound effect (RE). This paper proposes a new method integrating the Data Envelopment Analysis (DEA) production model and the sequential Malmquist-Luenberger (SML) index to calculate China's macro-carbon RE. An extended DEA production model is used to eliminate the impact of input scale, and the SML index is employed to avoid the phenomenon of technology regress. Results show that the carbon RE can be calculated more precisely. The new method is then applied to calculate carbon RE values from 30 Chinese provinces from 1996 to 2015, and results indicate that the carbon RE does indeed exist in China and that national average carbon RE values vary from 7.4% to 43.8%. Furthermore, both the backfire effect and the super conservation effect are evident in some provinces. Based upon the obtained results, certain policy implications are suggested to facilitate China in effectively implementing carbon emission reduction actions. [ABSTRACT FROM AUTHOR]

China is a large country of egg consumption, the study on China's laying hens breeding green total factor productivity (LHBG) is conducive to reducing pollution emissions while improving the productivity of laying hens to promote the cleaner production. Obviously, existing studies on laying hens breeding neglect regional and scale differences as well as serious pollution issues. Therefore, based on the directional distance function (DDF) - Data Envelopment Analysis (DEA) model, this paper constructs a three-level Metafrontier-Malmquist-Luenberger (MML) index, considering negative output, to evaluate LHBG from 2004 to 2018. Firstly, in terms of scale, the results show that LHBG is the largest in middle scale, followed by small scale and large scale. Secondly, from a regional point of view, the results indicate that China's LHBG presents a reverse stair-step distribution, that is, LHBG is the lowest in the eastern region, followed by the central region and the highest in the western region. The differences between regions and provinces are affected by the traditional farming habits, non-agricultural employment opportunities, the level of urbanization and resource conditions. Thirdly, this paper obtained that the three decomposition efficiencies of LHBG are manifested as the decrease in management efficiency, and the increase in scale structure efficiency and technical efficiency. Fourthly, climate factors have an impact on the laying hens breeding. According to the empirical results, this paper finally puts forward policy suggestions for improving LHBG and environmental protection policy recommendations for layer breeding. • Research on the efficiency of China's laying hens, which subject is innovative. • Environmental factors are introduced into the evaluation system. • The scale heterogeneity and regional heterogeneity of laying hens are considered. • Construct three-levels DDF-MML model and decompose into three efficiencies. [ABSTRACT FROM AUTHOR]

The construction of ecological civilization has become necessary to ensure that emerging industrialized countries can achieve healthy and sustainable development under the background of tightening resource constraints, serious environmental pollution, and the deterioration of the ecological environment. In the case of China, one representative emerging industrialized economy, this paper builds an ecological civilization performance evaluation system to measure the efficiency of ecological civilization in 30 provinces and municipalities in China by using the data envelopment analysis (DEA) game cross-efficiency model. From the perspective of the "five-in-one" approach, and by taking full account of the three main bodies of government, enterprises and residents, this paper selects nine explanatory variables, namely industrial structure and degree of marketization (Economic perspective), government environmental risk awareness and government green actions (Political perspective), residents' happiness and corporate environmental responsibility (Social perspective), culture education investment (Cultural perspective), and green travel and ecological construction (Ecological perspective). Geographically Temporally Weighted Regression (GTWR) is used to analyze determinants of the Chinese ecological civilization performance. The results show that China's ecological civilization performance is low, and the efficiency ranking of most provinces fluctuates greatly. The regional development of China's ecological civilization performance presents a spatial distribution pattern that was high in the east and low in the west. The impact of various influencing factors on the China's ecological civilization performance is largely positive, and indicates regional characteristics. These results not only contribute to advancing the existing literature on ecological civilization performance evaluation, but also merit particular attention from policy makers in emerging industrialized countries. • A new indicator is built to assess ecological civilization performance. • Vertical and horizontal scatter degree, DEA game cross-efficiency, GTWR are employed. • ECP measured by CCR and Game Cross have significant differences. • ECP in China is low, fluctuating greatly in ranking and obvious east-west differentiation. • The same influencing factors exert different impacts in different regions. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization has had a dramatic impact on the ecological environment in China. In this paper, we first measure the urban eco-efficiency of 281 prefecture-level cities in China during 2006–2013 using the super-efficiency data envelopment analysis (SEDEA) model. We then propose a new comprehensive index system to assess urbanization. Finally, we quantitatively explore the relationship between urbanization and urban eco-efficiency based on a spatial econometric analysis. The results showed that China's average urban eco-efficiency and comprehensive level of urbanization of 281 prefecture-level cities had shown increase during 2006–2013. However, distinct spatial disparities exist among different cities. China's urbanization has significant characteristics of spatial agglomeration and spatial convergence during 2006–2013, with a high-to-low spatial distribution from eastern China to western China. Spatial effects play an important role in the changes of urban eco-efficiency in China through spatial spillover effects and regional replication and competition. Evidence from spatial econometric analysis reveals that an N-shaped relationship exists between urbanization and urban eco-efficiency, indicating that with the improvement of urbanization, urban eco-efficiency first increases, then declines and then increases again. The improvement of the level of technology and the formulation of effective environmental policies will promote the increase in urban eco-efficiency. The results provide significant references for urban ecological management and sustainable urban transformation in China. [ABSTRACT FROM AUTHOR]

this paper applies an epsilon-based measure DEA approach to evaluate the regional ecological energy efficiency for 30 regions in China and its three major areas for the period 2007–2015. Based on this, the temporal and spatial disparities of China's regional ecological energy efficiency are investigated. To explore the sources of China's regional ecological energy inefficiency, the overall ecological energy inefficiency is decomposed into several input-specific inefficiencies. And then, the energy saving and pollution abatement potentials of each Chinese region is calculated using the differences between the target values and the actual values of energy consumption and pollution emissions. The empirical results show that China's ecological energy efficiency is relatively low and regional differences are significant for the period 2007–2015. It can be demonstrated that the inefficiency to abate pollution is the main contributor to China's regional ecological energy inefficiency. By calculating the potentials of energy saving and pollution abatement, it can be found that the east area has the lowest potential, followed by the central area, with the west area having the highest potential. [ABSTRACT FROM AUTHOR]

Cities have been one of the most important areas of CO 2 emissions. It is increasingly important to research the effect of urbanization on CO 2 emissions, especially in large emerging and developing economies, due to the indispensable need for understanding the effect of urbanization on CO 2 emissions, evaluating carbon reduction tasks and providing the scientific basis for low-carbon urbanization. Utilizing a balanced panel dataset in the Yangtze River Delta (YRD), China, during the period of 2000–2010, this paper employed data envelopment analysis (DEA) window analysis and a spatial lag panel Tobit model to investigate the effect of urbanization on CO 2 emissions efficiency (the ratio of the target CO 2 emissions to the actual CO 2 emissions). The results show that the average CO 2 emissions efficiency was 0.959 in 2010, and CO 2 emissions efficiency ranged from 0.816 to 1 and exhibited spatial clustering in the region. The larger potential of CO 2 emissions reduction appeared in Zhenjiang and Yangzhou, indicating that more CO 2 emissions reduction tasks should be allocated to these two cities. Urbanization has negative effects on improving CO 2 emissions efficiency, and there is a U-curve relation between CO 2 emissions efficiency and urbanization, indicating that CO 2 emissions efficiency decreases at the early stage of urbanization, then increases when urbanization reach a high level. There is spatial spillover effect among the prefecture-level cities, suggesting that different prefecture-level governments should coordinate with each other to improve CO 2 emissions efficiency in the whole area. Gross domestic product (GDP) per capita also plays a markedly positive role in improving CO 2 emissions efficiency. This research highlights the effect of urbanization on CO 2 emissions efficiency and the importance of improving CO 2 emissions efficiency in developing countries. [ABSTRACT FROM AUTHOR]

On the basis of the fact that China is setting up world's largest electricity network with the extra high voltage (EHV) and ultra high voltage (UHV) as their backbones, creating the foundation for large-scale accession of clean power which may deeply affect regional energy efficiency across the country, this paper attempts to empirically study the joint effects of clean power accessing to power grids on regional total-factor energy efficiency. To complete this job, we first measured the total-factor energy efficiencies of 29 provinces in China over the period 1991–2013, based on one of the data envelopment analysis methods, then, the static panel model considering panel fixed effect with instrument variable (FE-IV), dynamic panel model of system generalized method of moments (SYS-GMM) and panel smooth transition regression (PSTR) were employed, respectively, to investigate separate and joint effect of clean power and its grid-connection with EHV and UHV electricity network. The results show that the joint effect of clean power accessing to EHV and UHV power grid is either not significant or even negative although clean power itself separately promote regional energy efficiency. Thus, while the investment in grid infrastructure continues to increase, the grid-connection mechanism of clean power needs to be optimized therewith. [ABSTRACT FROM AUTHOR]

Rapid economic growth and urbanization in China have resulted in the dual threats of shortage of water and pollution of water. It is increasingly acknowledged that the efficiency of water resource system is influenced by not only the Water Use (WU) process, but also the process of Wastewater Treatment (WT). This paper considers both WU and WT as an integrated two-stage WUWT system to provide more comprehensive efficiency evaluation. In the first stage (WU subsystem), there are two parallel units, economic and social WU sub-minors, which consume water and capital to produce economic and social benefits. Meanwhile, the undesirable wastewater inevitably arises, which is treated in the second stage (WT subsystem). In order to assess the performance of the integrated WUWT system, an extended mixed network structure two-stage Slacks-Based Measure (SBM) Data Envelopment Analysis (DEA) model is developed to measure the detailed efficiencies and spot the weak link of the system. For case study, the provincial panel data during 2006–2015 of China are selected to verify the applicability of the proposed approach. Discussion is made from both time- and region-perspectives: over the ten years, the WU efficiencies are often higher than the WT efficiencies, so more actions should be carried out to improve the process of WT; from 2006 to 2011, social WU efficiencies are often lower than economic WU efficiencies, but the social WU efficiency has been improved after 2012; in terms of the overall efficiencies, the economically and socially developed provinces also have the higher efficiencies. Furthermore, the results demonstrate that the integrated WUWT system is efficient if and only if both WU and WT subsystem are both efficient, and the WU subsystem is efficient if and only if both economic and social WU sub-minors are efficient. [ABSTRACT FROM AUTHOR]

With the rapid economic development of China, the increasing emission of industrial waste gas as well as its poor control efficiency have caused serious air pollution issues and put threats to human health and sustainable development. Under the current development model, China's industrial sectors still remain the dominant economic component. Based on existing academic research in China and abroad, as well as with the help of the Data Envelopment Analysis (DEA) model, this paper adopted 39 industrial sectors of China as Decision Making Units (DMU) and their input-output data from 2003 to 2014 to calculate and evaluate the TFE of waste gas control in different industries of China. By designing an original MATLAB algorithm for optimization solutions of multi-variable constrained nonlinear functions, we found that there were 24 industries (61.5% of total industries) whose waste gas control efficiency at period end was lower than that at period beginning. Although the tobacco industry kept the optimal level, the major sectors with the biggest industrial waste gas emission all had poor waste gas control TFE. Based on the results, we further explained possible reasons for the difference in TFE across different industries from 2003 to 2014, and provided policy recommendations accordingly. [ABSTRACT FROM AUTHOR]

Currently, the iron and steel industry (ISI) accounts for more than 16% of China's total energy consumption. Improving energy efficiency (EE) and promoting energy savings in this industry have vital significance for China's further sustainable development. Using provincial panel data from 2000 to 2014 and meta-frontier data envelopment analysis (DEA), this paper investigates EE and the energy-saving potential (EP) of China's ISI by considering regional technology heterogeneities. The results show that (1) from 2001 to 2014, EE in China's ISI achieved significant improvement. Technological progress is the most powerful driving factor, while the declines in scale efficiency and pure technical efficiency are two obstructive factors; (2) the sources of energy inefficiency (EI) show distinct spatial difference characteristics. EI in the eastern region mainly stems from scale inefficiency and pure technical inefficiency, while that in the central and western regions stems from three aspects of scale inefficiency, pure technical inefficiency, and technology gap; and (3) there is considerable EP in China's ISI, which represents nearly 80% of ISI's current total energy consumption. Because the sources of EP vary across regions, the focus of future work for China's regional ISI should also vary. [ABSTRACT FROM AUTHOR]

The increasingly high frequency of heavy air pollution in most regions of China signals the urgent need for the transition to an environmentally friendly production performance by socioeconomic sectors for the sake of people's health and sustainable development. Focusing on CO 2 and major air pollutants, this paper presents a comprehensive environmental efficiency index based on evaluating the environmental efficiency of major socioeconomic sectors, including agriculture, power, industry, residential and transportation, at the province level in China in 2010 based on a slack-based measure DEA model with non-separable bad output and weights determined by the coefficient of variation method. In terms of the environment, 5, 16, 6, 7 and 4 provinces operated along the production frontier for the agricultural, power, industrial, residential and transportation sectors, respectively, in China in 2010, whereas Shanxi, Heilongjiang, Ningxia, Hubei and Yunnan showed lowest efficiency correspondingly. The comprehensive environmental efficiency index varied from 0.3863 to 0.9261 for 30 provinces in China, with a nationwide average of 0.6383 in 2010; Shanghai ranked at the top, and Shanxi was last. Regional disparities in environmental efficiency were identified. A more detailed inefficiency decomposition and benchmarking analysis provided insight for understanding the source of comprehensive environmental inefficiency and, more specifically, the reduction potential for CO 2 and air pollutants. Some specific research and policy implications were uncovered from this work. [ABSTRACT FROM AUTHOR]

Enterprises, which are the entities that must implement emission reduction policies, as well as other regional management bodies exhibit significant differences with respect to certain indicators. Previous studies mainly focus on one-indicator or one-sector evaluation methods, which are overly simple and inadequate for enterprise analysis. To solve this problem, this paper selects three key indicators for enterprise evaluation and proposes an integrated classification approach grouping enterprises into sets. The proposed approach comprises one main model and three sub-models. The sub-models (Emission Model, Data Envelopment Analysis Model and Geo-spatial Model) pre-compute the indexation of emissions, overall efficiency and geo-location conditions as input data for the main model. The main model synthesizes these three sub-models’ inputs and classifies enterprises into different classification sets. For verification, we conduct a case study of 8106 manufacturing enterprises in Shanghai. In the case study, the proportions of enterprises in top set, middle-top set, middle-low set and low set were 19.5%, 47.5%, 29.4% and 3.6%, respectively. The classification approach provides adequate quantitative technical support for flexible policy design and has the potential to promote efficient regional emission reduction, optimize regional industrial structures and distribute enterprises rationally. [ABSTRACT FROM AUTHOR]

Manufacturing industry is the pillar industry in China, making China become the world's manufacturing center. While, the rapid development of manufacturing industry in China not only promotes the economic growth, but also consumes lots of resources and generates too much carbon dioxide. To make a sustainable development, this paper adopts a non-radial DEA model with natural and managerial disposability to examine the energy-environmental performance of China's manufacturing industry during the 2006–2014 period. The energy-environmental performance is evaluated by the unified efficiency under natural and managerial disposability (UENM). Additionally, the investment strategy is confirmed by industrial types of damages to return (DTR). The empirical results indicate that the unified efficiencies of most manufacturing industries present a rising trend in the sample interval. Moreover, the unified efficiency of most manufacturing industries in light industry have a little higher value than the efficiency of those in heavy industry. Besides, the light industry presents more investment effect than the heavy industry, and many industries in heavy industry have little potential for investment in terms of developing the green growth. According to these results, China should increase investment and enhancing the R&D input to improve the unified efficiency of light industry. Policy support need focus on boosting innovation in strategic emerging industries instead of traditional manufacturing industries. Part of industries with excess capacity should be transferred to other countries through outbound investment. [ABSTRACT FROM AUTHOR]

The unbundling policy reform of power industry has become a worldwide trend since 1980s. There are quite many studies focusing on the efficiency changes of transmission and distribution sectors in European and Latin American countries while few reports on China's issues have been found. This paper employs a nonparametric frontier estimation combined with meta-frontier and bootstrapping method to measure the productive efficiency and changes in the decomposition index for China's 31 grid companies from 2004 to 2013. In addition, it further employs Tobit regression model to analyze the influences of relevant policies and heterogeneity factors, such as natural conditions and economic development. The results indicate that the grouping approach extends the application of non-parametric data envelopment analysis, which may decrease the assumption of homogeneity for the decision making units and provide better efficiency estimates by increasing the credibility of the evaluation results. Overall productive efficiency increased during the whole study period, with technology progress the main contributor to this improvement. Efficiency trends fluctuated with changes in economic development and power supply situation, and the economics and customer density had positive effects on productive efficiency while the influence of clean power proportion is negative. [ABSTRACT FROM AUTHOR]

This paper presents a DEA approach with multiple abatement factors to evaluate CO 2 emission performance and allocate CO 2 emission quotas in Chinese cities. We first consider the difference of marginal abatement costs among cities, and construct the non-radial directional distance function with multiple abatement factors. The total-factor CO 2 emission performance index and its dynamic change index are then proposed to measure CO 2 emission performance. Considering equity and efficiency, we develop a composite index by the hybrid method to allocate emissions quota, which considers CO 2 emissions as well as CO 2 emission performance. Then we conduct an empirical study using inputs and outputs dataset of 71 Chinese cities in 2005–2012. Chinese cities have poor energy efficiency and still have high CO 2 emissions. The eastern region outperforms the central region and the western region performs worst, whereas the dynamic CO 2 emission performance of the central region has the largest increase. The change of CO 2 emission performance is driven mainly by technological advances. As for the CO 2 emission allocation, the composite index method encourages cities to reduce emissions and enhance emission performance through carbon trading market. It also motivates cities with high historical emissions to reduce their emissions by improving technology when they have poor CO 2 emission performance. [ABSTRACT FROM AUTHOR]

Improvement of coal consumption efficiency is very important both for China in solving its problems of energy security and environmental pollution and for the world in addressing the issue of greenhouse gas emissions. Using a total-factor framework, this paper employs a data envelopment analysis (DEA) approach to evaluate the coal consumption efficiency of six energy intensive sub-industries in China in 2015. Coal consumption efficiency is factorized into economic efficiency and environmental efficiency, with sulfur dioxide, nitrogen oxide, and industrial smoke, dust and soot emissions treated as undesirable outputs of energy consumptions. The results show the following. (1) Of the six energy intensive sub-industries studied, two exhibit both DEA-effective coal economic efficiency and coal environmental efficiency. Coal economic efficiency is found to be greater than coal environmental efficiency, indicating that the benefits of economic efficiency have masked the negative effects of the environmental impact. China should therefore pay more attention to the clean utilization of coal. (2) Low environmental efficiency mainly resulted from the joint effects of pure technical efficiency and scale efficiency; therefore, enterprises in these industries must engage in management efforts to improve their ability to manage large enterprises. (3) The energy intensive industries characterized by coal environmental efficiency that failed to achieve pure technological effectiveness all exhibited input redundancy or output inadequacy of varying degrees while showing a potential for energy conservation and emissions reductions. [ABSTRACT FROM AUTHOR]

Recently, performance evaluation of coal-fired power generation with high pollution based on data envelopment analysis (DEA) method has become an advanced research hotspot in China. Instead of a single process in previous studies, we divide the production system of coal-fired power plants into the production process and pollutants abatement process, with pollutant intermediates as the link to connect the two processes in the current paper. Then we present a new two-stage network DEA model to evaluate the performance of China's coal-fired power generation by improving the link constraint that different with traditional network DEA approaches. Meanwhile, we conduct an empirical study to verify the applicability of the proposed approach and find that the proposed model is more effective than the previous models in evaluating the inefficiencies of coal-fired power generation. The empirical results also show that: the inefficiencies of the pollutants abatement process bring poor performance of the regional coal-fired power plants; and the efficiency results vary greatly among different areas of China, efficiency is best in the west area but the worst in the northeast area. Finally, some appropriate propositions are present in order to create better conditions for China's sustainable development. [ABSTRACT FROM AUTHOR]

Because industrial sectors in China are energy-intensive, improving energy efficiency and promoting energy savings in these sectors are of great importance for the further sustainable development of China’s economy. Using a proposed meta-frontier data envelopment analysis (DEA), this paper analyzes the total-factor energy efficiency and energy savings potential in China’s provincial industrial sectors for the years 2000–2014 from three perspectives, namely, the technology gap, management, and scale. The results indicate that (1) driven by technological progress, energy efficiency during the sample period was greatly improved, though the expansion of technology gaps between regions and the decline in scale efficiency represented two significant handicaps; (2) the current energy efficiency in China’s industrial sectors remains extremely low, indicating that there is considerable potential for energy efficiency improvement and energy savings; and (3) the sources of energy inefficiency and energy savings potential in China’s industrial sectors exhibit spatially distinct characteristics. Accordingly, it is determined that most of China’s eastern provinces should focus on improving scale and management efficiency, whereas most of its central and western provinces should concentrate on three factors: narrowing the regional technology gap, improving management efficiency, and optimizing the industrial scale. [ABSTRACT FROM AUTHOR]

Sustainability has been a global consensus for the governments worldwide to address serious environmental issues. However, there is a lack of data envelopment analysis (DEA) studies evaluating the performance of government in promoting various sustainability sub-systems. To do this evaluation work, our study proposes new parallel-series network DEA models with alternative network structures of incorporating intermediate products. Particularly, this study develops a new methodological framework to evaluate various inefficiency sources. The framework contains an extended method of network meta/group frontier approach and a new concept of efficiency Foster-Greer-Thorbecke indicator. Empirically, this study considers the case of Chinese government-sustainability system from 2010 to 2017. Such work cannot be found in the existing studies. The main findings are summarized as follows. First, China has succeeded in realizing an overall improved efficiency during the examined periods. The importance of various divisions changes over time. Second, the occurrence of method heterogeneity and significant linkage inefficiency implies that the modelers should incorporate intermediate products in a well-suited way. Finally, inland provinces show higher technology gap inefficiency as for economy division. To improve the performance, inland provinces should promote their human capital and adopt advanced technology. This paper proposes new parallel-series network DEA models with alternative network structures of incorporating intermediate products. Particularly, this study proposes a unified framework to analyze the relationship between network structures and inefficiency sources through the use of meta/group-frontier approach. To identify the main technology diffusion that maybe further cause the inefficiency value, this study applies the FGT indicators to the productivity and efficiency field for the first time. The FGT indicators can be used to explore the structure of technology inequality and identify barriers to technology diffusion. [Display omitted] • We propose a new approach for modelling the parallel-series network structure. • This study applies new frontier framework to identify sources of inefficiency. • There has been growing trends in Chinese government-sustainability system. • Managerial inefficiency had a negative annual growth rate of −6.01%. • Inland provinces showed higher technology gap inefficiency for economy division. [ABSTRACT FROM AUTHOR]

At present, PM 2.5 is still one of the most serious air pollution issues in China. By empirically testing the actual inhibitory effect of China's total factor energy efficiency progress on PM 2.5 , this paper can provide a new evaluation index for energy conservation in China and help Chinese cities understand the beneficial environmental effect of total factor productivity (TFP) progress under the constraint of energy consumption to point out an effective path of energy conservation and emission reduction that is highly in line with China's current high-quality development strategy. Based on the panel data of 105 key environmental protection cities in China, this paper evaluates total factor energy efficiency with range directional model (RDM) and global Malmquist (GM) productivity index based on data envelopment analysis (DEA); it then uses spatial econometric models to test the impact of energy efficiency progress on PM 2.5 concentration. The efficiency evaluation results show that the total factor energy efficiency of 105 key environmental protection cities has increased by an average of 35.9% from 2004 to 2015, with an average annual progress rate of 2.2%. Compared with Eastern and Central China, the progress of energy efficiency in the western region during 2004–2015 is relatively lagged. The average energy efficiency progress rate of higher administrative hierarchy cities and super cities with more than 10 million permanent residents is much higher than that of other cities. The results of GM index decomposition show that technological progress is the main driving force of energy efficiency progress. The spatial econometric analysis results show that there is a significant positive spatial autocorrelation in the concentration of PM 2.5 in sample cities, and the energy efficiency progress can significantly inhibit the PM 2.5 pollution in local and adjacent cities. The influence of each explanatory variable on PM 2.5 concentration is mainly composed of the spatial spillover effect. Image 1 • DEA-based RDM and Global Malmquist index are used to evaluate energy efficiency. • The energy efficiency of 105 cities has increased by an average of 35.9% in 12 years. • Technological progress is the main driving force of energy efficiency progress. • Energy efficiency progress can significantly reduce PM2.5 concentration. • The impact of each factor on PM2.5 is mainly composed of spatial spillover effects. [ABSTRACT FROM AUTHOR]

The impact of technical change on economic growth is closely related to the structure of input factors, and guiding technical change towards energy-saving can achieve the dual goals of economic growth and energy conservation. Based on the provincial panel data of 2006–2016, this paper first uses the slacks-based measure model and the bootstrap data envelopment analysis (bootstrap-DEA) to calculate the biased technical change (BTC) index and its factor bias of China's iron and steel industry (ISI). Next, the influencing factors of BTC are examined using panel regression analysis. The results corrected by bootstrap-DEA show that the level of ISI's BTC in China is 1.0110, with a contribution rate of 20.75% to green total factor productivity. Moreover, China's ISI experienced a labor-saving, energy-saving, and capital-using technical change during 2006–2016. In two-factor comparisons, technical change biased towards saving labor in labor-capital and labor-energy, and towards saving energy in energy-capital. The results of regression analysis show that improving energy efficiency, promoting urbanization, expanding production scale and optimizing industrial structure effectively promote BTC and improving energy efficiency is the primary pathway; however, excessive capital deepening has a significant negative correlation with BTC. Based on these results, this paper proposes policy recommendations for ISI's green development. • Biased technical change of iron and steel industry is increasingly significant. • Technical change biases towards labor-saving, energy-saving and capital-using. • An energy-saving technical change exists in the iron and steel industry of most provinces. • Energy efficiency can significantly promote the biased technical change. [ABSTRACT FROM AUTHOR]

The construction sector is an important industry in China's economic development and energy consumption, and research on its energy efficiency has attracted increasing attention from researchers. Currently, the traditional data envelopment analysis (DEA) model ignores the competition among regions, resulting in inaccurate estimation of efficiency. This paper employed traditional DEA, cross-efficiency DEA and game cross-efficiency DEA approaches to measure the energy efficiency of the construction industry in 30 of China's provinces from 2005 to 2016. The temporal trend and spatial distribution characteristics of energy efficiency determined through the game cross-efficiency method were then depicted by clustering analysis. Finally, the spatial heterogeneity of energy efficiency was analysed in detail. The results indicated that the efficiency calculated using the game cross-efficiency DEA model considering the competitive relationship was lower than the traditionally calculated efficiency and higher than the efficiency calculated using cross-efficiency DEA. Moreover, during the period of study, the energy efficiency showed a holistic growth trend with volatility. Clustering analysis demonstrated that the energy efficiency of eastern China was significantly higher than that of central and western China. Additionally, the spatial gaps in China's construction industry narrowed, while the spatial agglomerations strengthened. This paper also found a significant positive agglomeration in the energy efficiency of the construction sector in neighbouring provinces of China in the space dimension. In conclusion, province-specific policies based upon temporal and spatial heterogeneity were proposed to improve the energy efficiency of the construction industry in China. • Game cross-efficiency is first used in construction sector. • Provincial energy efficiencies of construction sector are examined in 2005–2016. • Spatial distribution characteristics of energy efficiency are depicted. • Energy efficiency is assessed in four agglomeration areas. • Positive spatial agglomeration exists in energy efficiency of construction sector. [ABSTRACT FROM AUTHOR]

China's economy is currently moving from a stage of high-speed growth to a stage of high-quality development. Agricultural green total factor productivity is of great significance for promoting the high-quality development of the economy. Based on the panel data of China's provincial agriculture, this paper uses the Super-SBM model to calculate China's agricultural green total factor productivity based on carbon emissions. On this basis, this paper uses the nuclear density estimation method to investigate its dynamic evolution trend and the panel data model to empirically study the influencing factors of China's agricultural green total factor productivity. The results show that China's agricultural carbon emissions show an inverted-"U" trend, but the overall growth rate shows a gradual declining trend. The main concentration areas are transferred from the eastern region to the central region, and agricultural fertilizer is the main source of such emissions. China's agricultural green total factor productivity overall shows a fluctuating growth trend, and the differences between provinces show an increasing trend. Agricultural factor endowments and regional characteristics affect China's agricultural green total factor productivity, and there are regional differences in these effects. An important way to improve China's agricultural green total factor productivity and promote the coordinated development of agricultural regions and the high-quality development of the economy is by promoting clean agricultural production, strengthening the research and development of agricultural science and technology, expanding the agricultural opening-up level, and promoting the deep integration of industrialization and agricultural modernization. Image 1 [ABSTRACT FROM AUTHOR]

In this paper, we comprehensively consider the environment and economic performance by employing non-radial distance function to study the regional eco-efficiency of China's Non-ferrous Metals Industry (NMI) during 2000–2016, from the perspective of total-factor through Data Envelopment Analysis (DEA)-Malmquist analysis framework. The change of regional technology gap ratio and the source of regional eco-inefficiency is also explored. Moreover, this paper analyzes the evolution of regional eco-efficiency and the main factors that contribute to changes in eco-efficiency. The results indicate that: First, the eco-efficiency of China's NMI has improved and has shown a certain degree of regional heterogeneity. Second, the main source of eco-inefficiency is management inefficiency in eastern China. The central, western and northeastern China all showed an increasing trend of technology gap inefficiency and a declining trend of management inefficiency during the sample period. Third, eastern China is regarded as a technology leader. The improvement of eco-efficiency in the central and northeastern China is mainly due to the promotion of technological progress, while the western region relies on the improvement of technical efficiency. The study suggests that strengthening scientific and technological research, promoting inter-regional technical exchanges are particularly important for eco-efficiency improvement and regional coordinated development in China's NMI. [ABSTRACT FROM AUTHOR]

Industrial convergence is one of the important strategies to promote China's sustainable development, and its development is phased. In order to better explore the heterogeneous effect of industrial convergence on regional metabolism in different stages, we takes the convergence of manufacturing and producer services in 26 provinces of China as the research object, and for the first time attempt to empirically test the impact of industrial convergence at different stages on metabolic efficiency. In this paper, we measure metabolic efficiency using emergy analysis and index data envelopment analysis (Index-DEA) and measure the convergence degree of the two industries using the coupling evaluation model. Then, we analyze the effects of industrial convergence on metabolic efficiency using the Tobit model. The results show that industrial convergence can significantly promote the metabolic efficiency of China. Specifically, in the emerging industry convergence zone, industry convergence has a significant promoting effect on the advancement of metabolic efficiency, while in the mature industry convergence zone, industry convergence has no effect on metabolic efficiency. Moreover, this paper considers six other factors that affect regional metabolism. In addition to government interaction, the other five factors have an impact on metabolism efficiency. Finally, special issues are briefly discussed. The results provide important insights for policy makers to better promote industrial convergence and improve regional metabolism. • Consider the two stages of industrial convergence. • Analyze six factors that affect regional metabolism. • Found the heterogeneous effect of industrial convergence on regional metabolism. • Provide an excellent comprehensive evaluation tool for the government's management. [ABSTRACT FROM AUTHOR]

As the second largest economic entity in the world, China plays an important role in controlling global carbon dioxide (CO 2 ) emissions. The land transportation sector (including railway transportation and road transportation) has been the most important source of emissions in China and the average CO 2 emissions of land transportation were 529.31 million tons during the period 2009–2012. In this study, a parallel Slack-Based Measure Data Envelopment Analysis model is proposed, which is used for evaluating the overall efficiency of the land transportation sector and individual efficiencies of the railway transportation and highway transportation subsectors at the same time, considering CO 2 emissions. The empirical results lead to three conclusions: (a) only Anhui province is efficient each year during 2009–2012. (b) The environmental efficiency of the Eastern area in China is the best, followed by the Central area, with the Western area being the worst. (c) The performance of railway transportation is better than that of highway transportation. These three conclusions lead to policy suggestions to promote highway transportation technological innovation and narrow the regional imbalances in land transportation. This paper makes two main contributions: the model advances improvements to methods used in the Data Envelopment Analysis technique, and also provides governments with a practical and yet easy-to-adopt perspective to implement land transportation performance measurement that aids in decision making. [ABSTRACT FROM AUTHOR]

China's economic has got remarkable achievements during the past 30 years, which has brought tremendous pressure on natural resources and serious environmental pollution at the same time. In this paper, we aim to make environmental efficiency analysis of China's regional industry. Data envelopment analysis (DEA) method is incorporated and the slacks-based measure (SBM) model considering undesirable outputs is introduced to measure the environmental efficiency of different regions. Big data theory is introduced in the collection and selection of the input and output data of the regions. Further, we evaluate the environmental efficiencies of China's industry using data from 2008 to 2012. The results show that apart from several developed provinces, the environmental efficiencies of China's industry are generally low. And the environmental efficiencies of the regions did not show any increasing trend through the past 5 years. Additionally, lager differences exist in environmental efficiencies between the regions in China. Finally, we suggest the Chinese government to focus on the low environmental efficiencies and the unbalanced development of its regional industry. [ABSTRACT FROM AUTHOR]

China's economic reform and opening policy has resulted in China's rapid growth, especially in terms of economy. The growth, however, is mainly based on huge consumption of natural resources, and that consumption should be reduced by significant amounts to protect global ecosystems. Emerged in 1980s, “big data” has developed very quickly in recent years, bringing new perspectives and opportunities for all kinds of academic fields, especially in DEA since it is a research highly based on data. In this paper, we propose a SBM-DEA model based on natural resource input orientation to evaluate the efficiency of natural resource utilization for 26 provincial regions in mainland China from 2005 to 2012. A DEA-based approach is developed to allocate a reduced total of natural resources among the 26 provincial regions. Drawing support from the developments of “big data”, we use each provincial region's previously observed production data to characterize its own production technology, which allows a better analysis of how the production will change after allocations of natural resources are reduced. Our empirical study shows that most provincial regions perform well in terms of efficiency in utilizing natural resources, but that is based on huge consumption of natural resources. From an area perspective, the eastern area of China achieved the highest average efficiency value, followed by the central and western areas. Our study also indicates that the most effective allocation of the natural resources requires about half of the 26 provincial regions to reduce their natural resource consumption while the remaining ones can maintain their original consumption. [ABSTRACT FROM AUTHOR]