Frame Work of Data Envelopment Analysis—A Model to Evaluate the Environmental Efficiency of China'S Industrial Sectors

Objective To evaluate the environmental and technical efficiencies of China＇s industrial sectors and provide appropriate advice for policy makers in the context of rapid economic growth and concurrent serious environmental damages caused by industrial pollutants. Methods A data of envelopment analysis （DEA） framework crediting both reduction of pollution outputs and expansion of good outputs was designed as a model to compute environmental efficiency of China＇s regional industrial systems. Results As shown by the geometric mean of environmental efficiency, if other inputs were made constant and good outputs were not to be improved, the air pollution outputs would have the potential to be decreased by about 60% in the whole China. Conclusion Both environmental and technical efficiencies have the potential to be greatly improved in China, which may provide some advice for policy-makers.

Energy Efficiency and Emissions Reduction Potential of China's Industrial Sector

Based on the total-factor energy efficiency framework,this paper calculates China's industrial energy efficiency and CO2 emissions reduction potential from 2000 to 2009 by utilizing the directional distance function and data envelopment analysis.The empirical results show that:China's industrial overall energy efficiency is relatively lower while the emis-sions reduction potential is relatively greater,given the optimum production frontier.Significant indus-trial disparities of energy efficiency and emissions reduction potential exist.Energy efficiency and emis-sions reduction potential significantly show different tendencies of industrial dynamic variation.This paper suggests the Chinese government impose differential carbon taxes,flexibly utilize carbon market mecha-nism,strengthen energy-saving technological R&D,promote the utilization of renewable energy,and strengthen environmental supervision and regulation,so as to improve China's industrial energy efficiency and reduce CO2 emissions.

Industrial Green Spatial Pattern Evolution of Yangtze River Economic Belt in China

We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.

An Empirical Study on Environmental Regulatory Costs &Environmental TFP

This paper examines the cost of environmental regulation and the environmental total factor productivity （TFP） with directional distance function and the Malmquist-Luenberger （ALL） index respectively, using inputs and output data of 36 two-digit industries over the period 1998- 2010. It finds that Chinese industries incur a relatively high environmental regulatory cost and that China has paid a high price fulfilling its promise to emissions mitigation. A comparison between conventional and environmental TFP shows that the two indicators for all industries declined on average, but a hypothesis test reveals insignificant difference between the two. In addition, the rise in environmental TFP is mainly due to technological progress, which is consistent with findings of many researches; analysis demonstrates signs of absolute convergence of environmental TFP.

Operational and investment efficiency of investment trust companies:Do foreign firms outperform domestic firms?

This study examines the efficiency of investment trust companies(ITCs)from 2011 to 2020 using a meta-frontier two-stage network data envelopment analysis(DEA)based on the directional distance function(DDF).We improved the accuracy of the efficiency measurement and added a network-based ranking component to rank the topperforming entities.In the group-specific technology assessment,foreign ITCs excel in investment efficiency.Meanwhile,in the meta-technology assessment,domestic ITCs outperform foreign ITCs in terms of both investment and operational efficiencies.Group-specific technology efficiency scores were found to be lower than or equal to the meta-technology efficiency scores for both the operational and investment stages.Based on the network-based ranking approach,Yuan Ta,a domestic ITC that ranked fourth in the operational stage and first in the investment stage,can be used as a reliable benchmark.This study will enable practitioners to gain a better understanding of the performance of ITCs operating under heterogeneous technologies.

An Empirical Study of China＇s Energy- Intensive Industries＇ Growth Based on Environmental Total Factor Productivity

Using directional distance function and nonparametric data envelopment analys＆, th＆ paper estimates the environmental total factor productivity （ETFP） of energy-intensive industries in China from 1995 to 2010, and performs an empirical analysis on factors affecting ETFP growth after studying the differences of energy-intensive industries ＇ ETFP by industries and provinces. The findings include the following： energy-intensive industries ＇ETFP growth is mainly driven by technical progress; China, at its current development stage, still has the potential to raise the productivity of its energy- intensive industries. By estimating the provincial data, we find that the ETFP growth of different provinces converge at different levels. Further market liberalization, increased FDl flows and reductions in energy intensity will help to improve each province＇s ETFP growth. In addition, increasing investment in energy saving and emissions reduction and improving corporate environmental management capacity can help to reduce a company＇s short-term cost of complying with environmental regulations.

Re-measuring Productivity, Energy and Environmental Factors of China＇s New Industrialization

This paper identifies low-carbon, energy-efficient, and green economic growth as the primary goals of China＇s new industrialization and defines productivity under new industrialization which; unlike conventional productivity, simultaneously satisfies these goals. In contrast to conventional methods for measuring productivity, this paper employs a non-radial, non-angular SBM directional distance function to estimate new industrialization productivity of industrial sectors across 30 Chinese provinces, municipalities and autonomous regions between 1998 and 2008. Our research shows that conventional measurements of productivity overestimate industrial growth in China＇s central and western regions. On the whole, prospects for growth performance of China＇s industrial sectors are not optimistic. The degree of new industrialization is higher in eastern region than in central and western regions, where balancing industrial growth with resources and the environment is a daunting task. This paper＇s conclusions support ＂environmental Kuznets curve＂ and ＂Porter hypothesis＂ but reject ＂pollution asylum hypothesis ＂.

Evaluating the environmental efficiency of the U.S.airline industry using a directional distance function DEA approach

This study applies a directional distance function(DDF)data envelopment analysis(DEA)model to measure the environmental efficiency of 12 U.S.airlines 2013–2016 by considering flight delay and greenhouse gas(GHG)emissions as joint undesirable outputs.First,the environmental efficiency of airlines is compared using the CCR DEA(without flight delay)and DDF DEA(with flight delay).We find that several airlines experienced substantial changes in environmental efficiency scores when flight delay is considered.Secondly,a tobit regression is used to explore whether the environmental factors of fleet age,ownership type,freight traffic,market share,and carrier type affect airlines’environmental efficiency.The results demonstrate that all of these factors significantly influence airline performance.

A nonparametric distance function approach with endogenous direction for estimating marginal abatement costs of CO_(2) emissions

The directional distance function(DDF)framework has been widely used to estimate the marginal abatement cost(MAC)of CO_(2)emissions to support decision-making in environmental sustainability and climate change issues.In the use of DDF,an important task is mapping evaluated entities towards a realistic production technology frontier.This study develops a new nonparametric approach for estimating the MAC of CO_(2)emissions.The approach incorporates the optimal endogenous direction into an enhanced environmental production technology and has three advantages.First,it avoids the arbitrariness in mapping directions.Second,it captures the heterogeneity in optimization paths across different decision-making units(DMUs).Third,it generates more reliable benchmarks for estimating MAC by constructing an environmental technology frontier that is consistent with the material balance principle.We apply the approach to study China's thermal power industry and find clear heterogeneity in MACs and optimization paths at the province level.The results on the optimal endogenous directions show that the DMUs prefer to increase both desirable output and CO_(2)emissions when CO_(2)emissions are unregulated.Comparisons with other approaches reveal that arbitrarily mapping exogenous directions and technology representations are likely to generate distorted and unrealistic MACs.

Reducing the stray light of holographic gratings by shifting the substrate a short distance in the direction parallel or perpendicular to the exposure interference fringes

This research proposes a simple and practical method to make low-stray-light gratings, where the substrate shifts about a 1 mm distance in the direction parallel or perpendicular to the exposure interference fringes. When the substrate shifts, a reference grating next to the substrate is used to adjust in real time the phase of the exposure interference fringes relative to the substrate. Shifting eliminates the exposure defects and therefore decreases the stray light of gratings. Several gratings are successfully made by using this method, which have straighter grooves,smoother surfaces, and lower stray light than gratings made in conventional interference lithography.

Dynamic changes and convergence of China's regional green productivity:A dynamic spatial econometric analysis

Low-carbon economic development is at the heart of the post-pandemic green recovery scheme worldwide.It requires economic recovery without compromising on the environment,implying a critical role that green productivity plays in achieving the carbon neutrality goal.Green productivity measures the quality of economic growth with consideration for energy consumption and environmental pollution.This study employs the slacks-based measure directional distance function(SBM-DDF)approach and the Malmquist-Luenberger(ML)index to calculate green productivity and its components of 30 provinces in China between 2001 and 2018.Using a spatial panel data model,we empirically analyzed the conditionalβ-convergence of China's green productivity.We found that overall,since 2001,China's green productivity has demonstrated a continuous upward trend.When taking into account spatial factors,China's green productivity demonstrates a significant conditionalβ-convergence.In terms of regional effects,the results indicate that the green productivity of the eastern and western regions demonstrates club convergence,implying a more balanced green economic development.Moreover,the convergence rate of China's green productivity increases with the addition of environmental regulation variable,and so the corresponding convergence time decreases.It indicates that environmental regulations help to facilitate the convergence of China's green productivity,narrowing the gap between the regional green economic development.The findings provide guideline for achieving a low-carbon development and carbon neutrality from a regional green productivity perspective.

Behavior pattern extraction by trajectory analysis

Trajectory clustering and behavior pattern extraction are the foundations of research into activity perception of objects in motion. In this paper, a new framework is proposed to extract behavior patterns through trajectory analysis. Firstly, we introduce directional trimmed mean distance （DTMD）, a novel method used to measure similarity between trajectories. DTMD has the attributes of anti-noise, self-adaptation and the capability to determine the direction for each trajectory. Secondly, we use a hierarchical clustering algorithm to cluster trajectories. We design a length-weighted linkage rule to enhance the accuracy of trajectory clustering and reduce problems associated with incomplete trajectories. Thirdly, the motion model parameters are estimated for each trajectory＇s classification, and behavior patterns for trajectories are extracted. Finally, the difference between normal and abnormal behaviors can be distinguished.

An Analysis of Energy and Environment Efficiency of China＇s Iron and Steel Industry

Due to heavy energy consumption and low technical efficiency, China＇s iron and steel industry is trapped in the dilemma ＂large but not strong＂. This situation not only exerts enormous pressure on energy security but also on increased carbon emission and environmental pollution. The contribution of this study is to calculate the energy and environment efficiency of China＇s iron and steel industry and to analyze the factors affecting this efficiency. An index of energy and environment efficiency is introduced based on Directional Slacks-based Distance Measure Model. This index is adopted to measure the energy and environment efficiency of China＇s iron and steel industry using 2,382 firm observations during 2001 to 2005. In addition, Hierarchy Linear Model （HLM） is applied to analyze the factors which can influence the efficiency with both firm-level and province-level data. The conclusions are as follows： The energy and environment efficiency of China＇s iron and steel industry did not have a significant change during the research period. A firm＇s age, size, ownership, product category and the economy of its province have significant influence on its energy and environment efficiency.