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.

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.

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.

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.