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This paper utilizes the slacks-based measure (SBM) undesirable model to analyze the environmental regulation efficiency (ERE) from 2003 to 2013, and uses the Data Envelopment Analysis (DEA) Malmquist productivity index to divide the environmental regulation total factor productivity (ERTFP) into a technical progress index, pure technical efficiency index and a scale efficiency index from the perspective of scale change. The results show that the ERE presents “polarized” effect and the ERTFP has an obvious “agglomeration” effect in China. There is also a very significant “match-up” effect between the ERE and economic development level. In addition, the paper also finds that the technical progress index has the largest contribution to ERTFP, followed by pure technical efficiency index and then the scale efficiency index. The preceding results can provide scientific suggestions for regional environmental departments. [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]

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]

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]

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]

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]

The banking industry plays an essential role in China's economic growth, and the assessment of bank efficiency has attracted increasing interest in the past two decades. Given that the data envelopment analysis cross-efficiency method can provide a more reliable reference set, a large number of studies targeting performance evaluation and its applications adopt this method. Few studies, however, address the issue of the non-uniqueness of weights in cross-efficiency evaluation. Whereas, this paper proposes a cross-efficiency interval considering all weighting schemes along with a VIKOR aggregate model to gauge the universal productive efficiency of 16 major Chinese commercial banks of China and rank them for the period of 2007–14. Specifically, we use the cross-efficiency interval to generate the global performance of each bank based on internal and external assessment while using VIKOR to compare the solution with the attitude index which ranks all of the banks. The results indicate that the cross-efficiency interval can provide more information than the traditional DEA model, that the banking system efficiency of China has been improved during the study period, especially for SOBs; that JSBs are more efficient compared with SOBs; and the efficiency gap narrowed during the study period. [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]

The environmental impact of materials and energy is an important concern when cities and regions produce goods and services. To examine this requires an evaluation tool which can deal with the complex system of resources, energy inputs, products and wastes involved. This paper evaluates the urban material and energy flow efficiencies of 31 cities in China using a combination of the Data Envelopment Analysis model and Principal Component Analysis method. The results show that the urban flow system is composed of several input and output principal components, including energy, materials, urban capital investment, overall output, wastes, and others. In 2010, 16 cities were efficient as judged by the material and energy inputs and outputs. The remaining 15 cities were not efficient, primarily due to product shortfalls and waste excesses. Since 2000, half of the analyzed cities experienced a decline in the urban flow efficiencies, while only six cities showed a positive trend. The reasons include excess inputs of coal, coke, electricity, cement, investment, as well as output shortfalls in terms of overall output, wastes, services, agriculture and transport. We conclude that key priorities for improving urban systems with material and energy flow inefficiency are the use of urban renewable supplies, focus on sustainable endogenous development model, and improvement management of waste output, in order to increase efficiency and sustain economic growth. [ABSTRACT FROM AUTHOR]

Thermal power has accounted for the major part of the electricity generation over recent several decades in China. It plays an important role in supporting China's economic development while it also brings great pressure to the environment protection because of a large amount of pollution generated during its production. In order to solve or alleviate the environmental problem caused by thermal power firms, efficiency evaluation is the first important step. As thermal power firm is a complex system with multiple inputs and multiple outputs, usually including fuzzy data and undesirable outputs in the productions, in this paper, we build an integrated Enhanced Russell measure model based on data envelopment analysis for evaluating the performance of decision making units in the presence of the undesirable outputs in fuzzy circumstance. Then, this new model is applied to analyze the environmental performance and provide the benchmarks for the thermal power firms in China which can guide the decision makers to make suitable future production plans for improving their performance. [ABSTRACT FROM AUTHOR]

Using panel data from 2003 to 2016, this paper estimates the green development efficiency of 34 cities in Northeast China based on the SBM-DEA model and determines whether industrial agglomeration promotes or impedes green development efficiency. The results show the following: (1) The average green development efficiency of Northeast China exhibits a fluctuant upward trend in 2003–2016, and there are significant spatial differences. (2) During the revitalization period, industrial agglomeration hinders green development efficiency. A U-shaped relationship exists between industrial agglomeration and green development. (3) Economic development level and foreign direct investment are positively related to green development efficiency, while industrial structure, energy consumption structure and environmental regulation are negatively related. Economic development level has the greatest positive influence and environmental regulation the strongest negative influence on green development. Several corresponding policy implications are proposed for promoting green development and revitalization. • The average green development efficiency of Northeast China exhibits a fluctuant upward trend. • Significant spatial differences exist in the green development efficiency in Northeast China. • A U-shaped relationship exists between industrial agglomeration and green development. • Economic development has the greatest positive effect on the green development. • Environmental regulation has the strongest negative influence on green development. [ABSTRACT FROM AUTHOR]