Super-efficiency Slack-based Measure Research Articles

Optimum combination of heterogeneous environmental policy instruments and market for green transformation: Empirical evidence from China's metal sector

Based on the new structural economics view that the combination of effective governments and efficient markets is the fundamental path to high-quality development, this study investigates how heterogeneous environmental policy instruments combine with marketization to improve the total factor energy-environmental efficiency (TFEEE) in China's metal sector. Utilizing the provincial panel data from 2006 to 2019, a super-efficiency slacks-based measure data envelopment analysis (SBM-DEA) integrated with the global Malmquist-Luenberger (GML) index is employed to estimate the energy-environmental efficiency and its dynamic changes. The evaluation results imply a significant increasing trend in the energy-environmental efficiency, but the overall level is rather low with disparities between sub-sectors and different regions. Using a dynamic panel threshold model, the “strong” version of the Porter Hypothesis is validated that command-and-control environmental policy (CEP), market-incentive environmental policy (MEP), and voluntary environmental policy (VEP) have an optimum stringency range to induce TFEEE growth, while the impact modes are drastically diverse. Further study verifies that higher marketization is conducive to triggering the facilitation effect of heterogeneous environmental policy instruments on the TFEEE but with completely different threshold values of marketization, which decrease sequentially corresponding to VEP, CEP, and MEP.

The impact of human capital on green economic efficiency: evidence from 280 prefectural cities in China.

Balancing economic growth with resources and the environment to achieve sustainable development is a key issue in the development of all countries, and researchers are trying to find feasible development paths. The aim of this study is to examine the impact of human capital levels on green economic efficiency (GEE) and the underlying mechanisms in 280 prefecture-level cities in China and covering the 2003-2019 period. In addition, we calculate GEE including undesired outputs based on a super-efficiency slack-based measure (SBM) model, and we construct panel regression and moderating effect models for empirical studies. The results of the baseline regression study show that the improvement in the human capital level contributes to the GEE of prefecture-level cities. Among the control variables, the economic development level, foreign direct investment (FDI), city size, and the science and technology innovation (STI) level positively affect GEE, while industrialization and environmental regulation negatively affect GEE. The study results concerning the mechanism of action indicate that industrial structure upgrading plays a positive moderating role. That is, industrial structure upgrading can strengthen the effect of human capital on GEE, which is further clarified. This study suggests that government policies must favor the cultivation of high-level human capital, especially in the environmental protection industry, and that talent support strategies should be differentiated between regions to promote industrial structure upgrading and human capital matching through green technology development. Modern human capital theory reveals the important role of human capital in improving economic efficiency and provides new ideas for achieving sustainable development. This paper explores the role of human capital in improving the GEE based on the human capital perspective, which is important for research on the pathways to achieve sustainable development.

Spatio-temporal evolution characteristics of eco-efficiency in the Yellow River Basin of China based on the super-efficient SBM model.

It is of great significance to study the trends and internal differences of eco-efficiency in the Yellow River Basin for ecological protection and high-quality development of the Yellow River Basin. According to the characteristics of the Yellow River Basin in China, the eco-efficiency evaluation system was constructed, and the super-efficiency slack-based measure (SBM) model and the super-efficiency SBM model of undesired output were used to calculate the eco-efficiency levels of provinces in the Yellow River Basin from 2005 to 2020, and the variation trend and internal differences were analyzed. The results show that when only the expected output was considered, the eco-efficiency of the Yellow River Basin as a whole and each province showed a fluctuating upward trend, but there were obvious differences. Qinghai Province, Sichuan Province, and Ningxia Autonomous Region had high eco-efficiency, while Shaanxi Province, Shanxi Province, and Inner Mongolia Autonomous Region had low eco-efficiency. Compared with only considering the expected outputs, eco-efficiency of Qinghai Province had improved significantly when considering non-expected outputs. The eco-efficiency of Shandong Province and Henan Province had improved significantly after 2016, while the eco-efficiency of the two provinces had decreased significantly before 2016. The eco-efficiency of Shaanxi, Shanxi, Inner Mongolia, Ningxia, and Gansu had declined to varying degrees. Finally, the reasons for the differences in eco-efficiency in various provinces in the Yellow River Basin were analyzed, and suggestions for improving the eco-efficiency of the Yellow River Basin were put forward.

How does agricultural production agglomeration affect green total factor productivity?: empirical evidence from China

Economic growth in agriculture is often accompanied by environmental pollution. To overcome this dilemma, agricultural green total factor productivity is essential. The role of agricultural production agglomeration has been studied extensively; however, there is no apparent association between agricultural production agglomeration and agricultural green total factor productivity. We use the non-angular and non-radial super-efficiency slacks-based measure model and the global Malmquist-Luenberger productivity model to assess the agricultural green total factor productivity in 30 Chinese provinces from 2001 to 2019. In addition, we investigate the evolutionary trend, influence relationship, and internal mechanism between agricultural production agglomeration and agricultural green total factor productivity. The results show an inverted U-shaped relationship between agricultural production agglomeration and agricultural green total factor productivity. Heterogeneity analysis finds that this role is more pronounced in provinces located inthe Yangtze River economic zone with strong fiscal support for agriculture and high levels of regional economic development. Regarding the mechanism analysis, enhancing green technology progress and the quality of rural human capital leads to an increase in agricultural green total factor productivity. Therefore, this study provides a new perspective on global carbon emission reduction and a theoretical and practical reference for realizing global agricultural green development.

Identifying the evolution of ecological poverty alleviation efficiency and its influencing factors: evidence from counties in Northeast China.

Ecological poverty alleviation (EPA) is an effective strategy to address the vicious circle of poverty and environmental destruction in poor areas. However, it remains controversial whether this strategy has really succeeded in this respect. Previous research investigated the impact of a certain factor on EPA, and only few studies integrated them to explore their differential effects, thereby overlooking the complexity of EPA. Therefore, this study quantified the overall efficiency of the EPA strategies of 28 poor counties in three provinces of Northeast China from 2005 to 2018 by using a super-efficiency slacks-based measure model. This model can take into account undesirable outputs; as such, it has significant advantages in measuring the coordination among economic and social development and environmental protection. The Tobit model was used to explore the factors influencing EPA efficiency. The results show that, first, the majority of counties investigated had an EPA efficiency below the overall national average. Second, as for the factors influencing EPA efficiency, it was found that (1) GDP per capita and investment in environmental governance favored EPA efficiency, as they are conducive to stimulating regional consumption dynamics and achieving green economic development; (2) science and technology expenditure and urbanization were not conducive to EPA efficiency; and (3) industrial structure and trade had insignificant effects on EPA efficiency, due to the small scale of industry and the inadequacy of the policy system. This study assessed EPA efficiency from a holistic perspective, and addressed the controversies over EPA's influencing factors, thereby providing an effective method to conduct regional EPA assessment and improve EPA performance in poor regions of China.

Achieving co-benefits by implementing the low-carbon city pilot policy in China: Effectiveness and efficiency

Cities are the main emitters of CO2 and air pollutants, and the main drivers of addressing climate change. The implementation of the low-carbon city pilot (LCCP) policy has achieved carbon emission reduction, but further research is needed to determine whether the synergistic reduction of CO2 and PM2.5 can be effectively implemented, and the efficiency of the synergistic reduction can be improved. Panel data belonging to 279 Chinese cities are selected. We assess the effectiveness and efficiency of the implementation of the LCCP policy to achieve co-benefits of CO2 and PM2.5 emission reduction, using the time-varying difference-in-differences model. We evaluate the synergistic emission reduction efficiency and its decomposition by the super-efficiency slack-based measure model with CO2 and PM2.5 as undesirable outputs. The results show that the LCCP policy reduces 3.55% of CO2 and 2.18% of PM2.5 respectively, and enhances the effectiveness of coordinated emission reduction governance. The LCCP policy also improves the synergistic emission reduction efficiency, moves the input–output model towards the “optimal production frontier”. We form policy recommendations for encouraging technological innovation and optimal resource allocation to achieve “net zero emissions”. Most importantly, policymakers should incorporate synergistic emission reduction efficiency into the process of policy evaluation, and establish a low-carbon economic development model tailored to local conditions.

Tourism Ecological Efficiency and Sustainable Development in the Hanjiang River Basin: A Super-Efficiency Slacks-Based Measure Model Study

The Hanjiang River is one of the major tributaries of the Yangtze River, and the Hanjiang River Basin serves as an important link connecting the western and eastern regions of China. As a significant tourist destination, the development of the tourism industry in the Hanjiang River Basin is of great significance for promoting local economic, social, and environmental sustainability. The study of the spatiotemporal evolution of the ecological efficiency of tourism in the Hanjiang River Basin is beneficial for optimizing the investment of tourism resource elements and promoting ecological protection and high-quality development in the area. In this paper, we used the Super-Efficiency Slacks-Based Measure Model to calculate the tourism ecological efficiency of 12 cities in the Hanjiang River Basin from 2010 to 2019 and measured its spatiotemporal evolution and spatial agglomeration using ArcGIS software. The results show that during the study period, the ecological efficiency of tourism in the Hanjiang River Basin presented a phased characteristic of first rising and then falling over time and a heterogeneity characteristic of decreasing in a downward-middle-upward staircase pattern spatially. In addition, the distribution of tourism ecological efficiency exhibited obvious spatial clustering and dependence, with significant low-level homogenization phenomena, which requires strengthening cooperation and coordination among neighboring cities to achieve more efficient resource utilization and higher-quality tourism product development.

The Effect of Place-Based Policy on Urban Land Green Use Efficiency: Evidence from the Pilot Free-Trade Zone Establishment in China

The improvement of urban land green use efficiency is significant in promoting sustainable development. As an important place-based policy in China, the pilot free-trade zone establishment has exerted a profound impact on urban economy and society. Meanwhile, the issue of whether the pilot free-trade zone can improve urban land green use efficiency or not is missing from prior literature, which is the concern of this study. Specifically, based on the super-efficiency slacks-based measure model, we first measure urban land green use efficiency of 279 cities in China from 2011 to 2019 and then use the multi-period difference-in-differences method to investigate the causal effect of the pilot free-trade zone establishment on urban land green use efficiency. The results show that the pilot free-trade zone significantly improved urban land green use efficiency, especially in the eastern cities, the coastal cities, and the cities with a high economic development level. Further, there exists a spatial spillover effect of the pilot free-trade zone on urban land green use efficiency. This study has implications for optimal allocation of urban land in the deployment of place-based policies, serving economic structural upgrading and a carbon neutrality vision.

Study on the Evaluation of the Development Efficiency of Smart Mine Construction and the Influencing Factors Based on the US-SBM Model

Taking the panel data of 13 provinces (autonomous regions and municipalities directly under the central government) in Shanxi and Xinjiang from 2011 to 2020 as the research object, we establish an evaluation index system for assessing smart mine construction development efficiency combined with the global reference method. The non-desired output super-efficiency slacks-based measure and the kernel density model were used to measure the development efficiency of smart mine construction and spatial structure evolution characteristics. This study explores the internal and external factors affecting the efficiency in various regions using the Tobit regression model. After conducting the analysis, the study obtained four main findings: (1) the development efficiency is influenced by the level of technology, and the overall level is low; (2) there are spatially heterogeneous and agglomerative characteristics, with large differences in regional distribution; (3) personnel is the main factor causing the phenomenon of severe redundancy in the region; and (4) the level of regional economic development, industrial structure, and the degree of government intervention are the main external factors that have a positive impact.

Understanding the overall difference, distribution dynamics and convergence trends of green innovation efficiency in China’s eight urban agglomerations

Based on adopting the global super-efficiency slacks-based measure (GSSBM) model to calculate green innovation efficiency (GIE), this paper systematically investigates GIE’s overall difference, distribution dynamics and convergence trends in eight national urban agglomerations (UAs) of China from 2004 to2018 by combining the methods of Dagum Gini Coefficient (DGC), Kernel Density Estimation (KDE), Variation Coefficient (VC), fixed-effect model (FEM) and spatial Durbin model (SDM). The results show that: (1) the average GIE of eight UAs was 0.632 during 2004–2018, which is generally low and has substantial potential for improvement, and seven of them achieved positive growth with an annual average growth rate of 2.70%. (2) The overall difference of GIE within eight UAs was significant with the inter-UA difference as the main contributor. (3) The distribution curves of GIE in eight UAs were distinct in terms of location, form, ductility and polarization trend. (4) Besides five UAs presenting significant σ convergence characteristics, all eight UAs displayed significant absolute or conditional β convergence trends with different speeds and cycles. The findings of this paper can provide important insights on the promotion of green innovation-driven development for UAs in China.

The Effect of Environmental Regulation on the Efficiency of the Green Economy: The Intermediary Role of the Aggregation of Innovative Elements.

Green development is the only way to realize harmonious coexistence between people and nature, so it is of great significance to create a benchmark for high-quality development. Based on the panel data of 30 provinces (except Tibet, Hong Kong, Macao, and Taiwan) in China from 2009 to 2020, the super-efficiency slacks-based measure model was used to calculate the green economic efficiency of various regions in China, and a related statistical model was used to verify the influence of different types of environmental regulation policies on green economic efficiency and the intermediary effect of innovation factor agglomeration. The results show that: (1) during the inspection period, the influence of public-participation environmental regulation on the efficiency of the green economy presents an "inverted U" trend, while command-control and market-incentive environmental regulation policies inhibit the improvement of green economic efficiency; (2) the agglomeration of innovative elements plays a significant intermediary role in the transmission path of environmental regulation affecting green economic efficiency, but the intermediary effects of different types of environmental regulation are slightly different. Finally, we discuss environmental regulation and innovative elements, and some corresponding suggestions are put forward.

The improvement of energy-consuming right trading policy on the efficiency of urban green development

As a measure to promote the reform of China’s ecological civilization system, the energy-consuming right trading policy has great potential to reduce pollutant emissions and achieve green development in China. Based on the panel data of 254 cities in China from 2005 to 2019, this paper uses difference-in-differences (DID) model and super-efficiency slacks-based measure (Super-SBM) to investigate the impact of energy-consuming right trading policy on the efficiency of urban green development. The findings are as follows. i) The energy-consuming right trading policy can significantly promote the efficiency of urban green development. The conclusion still holds after a series of robustness tests. ii) The energy-consuming right trading policy can improve the efficiency of urban green development by promoting green technology innovation. This finding supports the Porter Hypothesis. iii) Heterogeneity analysis shows that the energy-consuming right trading policy can significantly improve the green development efficiency of cities in the eastern region. On the contrary, there is no significant effect on the green development efficiency of cities in the central and western regions. The government should expand the scope of energy-consuming right trading policy implementation according to local conditions. At the same time, the government should also stimulate enterprises to innovate green technologies and maximize the effect of the energyconsuming right trading policy on the efficiency of green development.

Spatio-Temporal Evolution, Spillover Effects of Land Resource Use Efficiency in Urban Built-Up Area: A Further Analysis Based on Economic Agglomeration

The Chinese “New Normal” economic model is a national strategy for adapting to sustainable development and offers important implications for the development of new economies. The “New Normal” economic model aims at improving the use efficiency of land resources in the framework of sustainable development. A discussion of the spatio-temporal evolution of land resource use efficiency (LRUE) in urban built-up areas can help in better assessing LRUE. In this paper, the super-efficiency slack-based measure (Super-SBM) method and spatial econometric models are used to study 281 prefecture-level cities in China between 2004 and 2020. Further, this paper explores the relationship between economic agglomeration and LRUE, which is of great value in managing land resources. The results show that there is a spatial spillover in LRUE and a U-shaped relationship between it and economic agglomeration.

The impact and transmission mechanisms of financial agglomeration on eco-efficiency: Evidence from the organization for economic co-operation and development economies

Whether financial agglomeration is conducive to eco-efficiency is of great importance for countries to better pursue cleaner production, low carbon emission reduction, and sustainable development paths. This paper focuses on 38 Organization for Economic Co-operation and Development (OECD) members. Based on the scientific accounting of green eco-efficiency by the super-efficiency slack-based measure (SBM) model, the relationship between financial agglomeration and eco-efficiency is thoroughly investigated by combining the spatial Durbin model (SDM), the mediating effects model, and the panel threshold regression (PTR) model, bridging the knowledge gap. Empirical results reveal that (1) Financial agglomeration has strong positive externalities for eco-efficiency in the home country and its neighbors, with the trickle-down effect playing a key role. (2) Financial agglomeration can indirectly promote cleaner production and eco-efficiency by strengthening technological innovation and upgrading industrial structure, with the latter being more strongly mediated. (3) The effect of financial agglomeration in enhancing eco-efficiency has clear stage differences. The low-level financial agglomeration will impede the improvement of green eco-efficiency while the high-level will support it, which is in line with the Environmental Kuznets Curve theory and the law of economic development. The research broadens the theoretical underpinnings of financial agglomeration and eco-efficiency and provides guidance and implications for OECD members and other emerging economies on how to optimize the spatial allocation of financial resources, promote eco-efficiency, and advance green sustainable development.

Fiscal Expenditure Efficiency Measurement and Its Convergence Analysis on Aging Undertakings in China: Based on a Global Super-Efficiency Slacks-Based Measure Model

As the aging of China’s population continues to intensify as well as deepen, and fiscal support continues to increase, improving the efficiency of fiscal expenditure on aging undertakings has become the key to actively responding to the national strategy of sustainable population aging. This paper uses a global super-efficiency slacks-based measure model to measure the efficiency of fiscal expenditure on aging undertakings in China from 2011 to 2020. The results show, firstly, that the efficiency values are generally increasing. The eastern region’s fiscal expenditure efficiency has output deficiencies overall; all western, central, except Anhui, and northeast, except Jilin, provinces have input redundancies and output shortages. Secondly, the relatively effective provinces in terms of aging undertakings are mainly concentrated in the eastern coastal region; the number of effective provinces in the northeast is gradually increasing. Thirdly, excluding the eastern region, the efficiency values for all regions show a convergence trend; when controlling for region-specific influencing factors, the efficiency values of each region will converge to their respective steady-state levels. It is concluded that the trend in the fiscal management of aging undertakings in China is positive, and the levels of fiscal management as well as technology are higher in the east, lower in the west, less stable in the central, and more progressive in the northeast.

Temporal-Spatial Evolution and Trend Prediction of the Supply Efficiency of Primary Medical Health Service-An Empirical Study Based on Central and Western Regions of China.

China has established a comprehensive primary medical health service system, but the development of primary medical health services in the central and western regions is still unbalanced and insufficient. Based on data from 2010 to 2019, this paper constructs a super efficiency Slack-Based Measure model to calculate the supply efficiency of primary medical health services in 20 provinces and cities in central and western China. Using Kernel density estimation and Markov chain analysis, this paper further analyzes the spatial-temporal evolution of the supply efficiency of primary medical health services in central and western China, and also predicts the future development distribution through the limiting distribution of Markov chain to provide a theoretical basis for promoting the sinking of high-quality medical resources to the primary level. The results show that firstly, during the observation period, the center of the Kernel density curve moves to the left, and the main peak value decreases continuously. The main diagonal elements of the traditional Markov transition probability matrix are 0.7872, 0.5172, 0.8353, and 0.7368 respectively, which are significantly larger than other elements. Secondly, when adjacent to low state and high state, it will develop into convergence distributions of 0.7251 and 0.8243. The supply efficiency of primary medical health services in central and western China has the characteristics of high (Ningxia) and low (Shaanxi) aggregation respectively, but the aggregation trend is weakened. Thirdly, the supply efficiency of health services has the stability of keeping its own state unchanged, but the transition of state can still occur. The long-term development of the current trend cannot break the distribution characteristics of the high and low clusters, the efficiency will show a downward trend in the next 10-20 years, and still the problem of uneven long-term development emerges.

Spatiotemporal Differentiation and Influencing Factors of Green Technology Innovation Efficiency in the Construction Industry: A Case Study of Chengdu–Chongqing Urban Agglomeration

In order to support the green and low-carbon transformation of China’s construction industry and accomplish the dual carbon objective, it is vital to accelerate green technology innovation. Therefore, this paper takes the Chengdu–Chongqing urban agglomeration of China as the study area, using the super-efficiency slacks-based measure (SBM)model and the gravity model to assess the efficiency of green technology innovation in the construction industry, utilizing geographical detectors to investigate the drivers of green technology innovation in the construction industry further. Additionally, we consider each influencing factor’s level of impact on the efficiency of green technology innovation in the construction sector both under the single factor and double factor scenarios. The findings indicate that there is a considerable difference in the efficiency of green technology innovation in the Chengdu–Chongqing metropolitan agglomeration’s construction industry, and the trend is upward. In addition, the research area exhibited spatially heterogeneous characteristics in terms of the efficiency of green technology innovation in the construction industry, and the spatial spillover effect was significantly limited by distance. Further research revealed that environmental legislation, economic development, public environmental concern, urbanization level, and foreign direct investment were the primary driving factors of green technology innovation efficiency in the construction sector, and industrial size was the potential driving factor. The spatial and temporal differentiation of the green technology innovation efficiency in the construction industry was also more affected by the interaction between the dominating factor and the prospective factor than by either factor acting alone. The research’s findings are useful in advancing the green and low-carbon transformation of the construction sector in the Chengdu–Chongqing metropolitan agglomeration by offering theoretical support and decision-making reference.

Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors

Investigating urban green innovation efficiency (UGIE) is imperative because it is correlated with the development of an ecological civilization and an innovative country. Spatiotemporal evolution and influencing factors of UGIE are two important scientific problems that are worth exploring. This study presents an indicator system for UGIE that includes input, expected output, and unexpected output, and employs a super-efficiency slacks-based measure (super-SBM) to calculate UGIE in 284 cities at or above the prefecture level in China from 2005 to 2020. Then, we adopted spatial auto-correlation to identify its spatial differences among these cities and Geodetector to evaluate its influencing factors. The results are as follows: (1) The overall UGIE tended to rise, except in northeastern China, megacities, and super large-sized cities. (2) The UGIE of Chinese cities exhibited remarkable spatial differences and auto-correlation, and the “low-low” type enjoyed the most local spatial auto-correlations. (3) Sociocultural factors represented by the number of collections in public libraries became the most important factors affecting the UGIE in China.

Spatio-temporal variations, spatial spillover, and driving factors of carbon emission efficiency in RCEP members under the background of carbon neutrality.

Improving carbon emission efficiency (CEE) has emerged as a critical way for Regional Comprehensive Economic Partnership (RCEP) members to promote carbon reduction in the context of climate change mitigation and carbon neutrality. The super-efficiency slacks-based measure (SBM) model, which considers non-desired outputs, is adopted to comprehensively assess the current state and trend of CEE in 15 RCEP countries from a spatio-temporal dynamic perspective, and the global Malmquist-Luenberger (GML) index is coupled to quantify the spatial and temporal differences and dynamic changes. Following that, taking into account the spatial characteristics of CEE, the extended STIRPAT model and the spatial Durbin model are combined to further investigate the primary influencing factors of CEE. It is found that (1) the CEE of RCEP members is generally poor and unevenly distributed in temporal and spatial dimensions, with significant room for improvement and an overall positive spatial autocorrelation; (2) CEE varies considerably among RCEP members, with developed countries far outstripping developing countries in terms of both the current status and trend of CEE; (3) on a dynamic level, the GML index exhibits W-shaped fluctuations, with technological progress acting as the dominant force; and (4) in terms of spillover effects, affluence and economic agglomeration inhibit CEE enhancement, whereas technology level and investment capacity facilitate it. The findings will be useful in developing carbon-neutral plans for various countries as well as coordinated sustainable development for RCEP regions.

Spatial - temporal evolution and driving factors of carbon emission efficiency of cities in the Yellow River Basin

Carbon attainment and carbon neutrality are inherent requirements for promoting high-quality development, and the carbon emission efficiency of cities in the Yellow River Basin(YRB) directly affects the high-quality development of the Yellow River Basin. In this paper,we measures the carbon emission efficiency of 61 cities in the YRB from 2004 to 2018 using the super-efficiency Slack-Based Measure model (super-efficient SBM model), and explores the spatial and temporal heterogeneity and spillover effects of the new carbon emission efficiency values by combining empirical orthogonal functions and spatial autoregressive models. The results show that: (1) The spatial pattern of cities in the YRB has changed from “pretty high in the centre and low in the surroundings” to “agglomeration in high-value zones as well as dispersion in low-value zones”. (2) GDP per capita and government involvement are positively related to carbon emission efficiency, while GDP per capita squared, energy intensity and industrial structure are negatively correlated with carbon emission efficiency. (3) Reducing the proportion of fossil energy consumption, strengthening government regulation and optimising​ industrial structure are effective ways to improving the efficiency of carbon emissions in the YRB.