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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]

Abstract This paper deals with the efficiency of the 28 European Union (EU) Member States for the years 2008, 2010, 2012 and 2014 by employing Data Envelopment Analysis (DEA) and directional distance function to tackle undesirable outputs. Eight parameters are used, namely municipal solid waste (MSW) generation, employment rate, capital formation, gross domestic product (GDP), population density and for the first time sulphur oxide (SOx), nitrogen oxide (NOx) and greenhouse gases (GHG) emissions from the waste sector for the relevant countries. The innovation of this paper lies in the fact that both new parameters are taken into account and that diverse modelling techniques have been employed in terms of the outputs and inputs used. The empirical results obtained were bias corrected in order to get the correct efficiency scores for each country studied. Overall the most efficient countries were shown to be Germany, Ireland and the UK. These results were then reviewed against the recycling rate of each country for the examined time periods. The recycling rate actually depicts the DEA results, namely more efficient countries seem to have a higher recycling rate too. Moreover the DEA efficiency results were contrasted to the overall treatment options used in the countries under consideration. Overall it is noticed that countries employing all four treatment options with high use of more sustainable ones and decrease in the use of landfill are the ones that also proved to be efficient according to DEA. These results resemble the image of a financial crisis hit Europe which tried to take advantage of the more sustainable treatment options in order to achieve a transition to a circular economy, whereas the value of products, materials and resources needs to be maintained in the economy for as long as possible and the generation of waste minimised. This can be a valuable lesson for policy makers in the design and application of national and EU legislations and directives in order to achieve also the targets towards a circular economy driven Europe. Highlights • Employing DEA to assess national waste generation. • Three novel environmental production frameworks designed. • Directional distance function to tackle undesirable outputs. • Comparison of results with treatment options and recycling rates. • Policy implications under a circular economy approach. [ABSTRACT FROM AUTHOR]

Over recent decades, China's economy has continued to develop steadily and rapidly, contributing to a large environmental cost. Therefore, many researchers propose various methods to evaluate environmental efficiency to deal with these serious issues accurately. This paper is the first to evaluate environmental efficiency using a model featuring not only a parallel structure with three component processes (primary, secondary, and tertiary industries) in the first stage but also a sewage treatment process in the second stage. Simultaneously, we propose radial but also nonradial versions of the Environmental Multiple Variable Return to Scale (EMVRS) model. These two models both consider shared inputs as well as shared outputs, and the proportion of the shared inputs and shared outputs utilized in each component process is assumed to be unknown. Additionally, we further analyze the factors influencing environmental efficiency by utilizing the Tobit model. The results when EMVRS is applied to Chinese provinces can be divided into 3 parts: (1) Most provinces do not purify wastewater appropriately contributing to the bad environmental efficiency. (2) The efficiency values of the three industry types are similar or identical to each other in most provinces. (3) The population of people employed negatively impacts environmental efficiency. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of transportation industry brings economic benefits, at the same time, the problem of environmental pollution is becoming more and more serious. The emission of CO 2 intensifies the trend of global warming. How to measure the development of environment and economy is a huge challenge for us. This paper proposes a data envelopment analysis (DEA) method based on slacks-based measure (SBM) to evaluate the environmental and economic performance of the transportation industry from 2015 to 2017. According to the economic region, 30 provinces in China are divided into northeast, east, central and western regions for efficiency analysis. The model can determine the low efficiency decision units and finally put forward improvement suggestions for the low efficiency areas. [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]

Abstract: Agriculture in Scotland is facing immense challenges for the future. Scottish policy now promotes sustainable economic growth, which to many implies both a growth in resource use and the requirement to meet targets for reducing greenhouse gas emissions. Attempts to increase economic gains can be in conflict with environmental aims and the question arises how both objectives can be met simultaneously. This paper examines the relationship between the technical and environmental efficiency of dairy farms in Scotland with respect to greenhouse gas emissions. It estimates the technical efficiency of a sample of dairy farms based on survey data, applying a number of approaches based on the non-parametric Data Envelopment Analysis (DEA) method. The farms’ greenhouse gas emissions are calculated using a variety of sources and were used to estimate environmental efficiency. This paper finds that, within the study sample, farms which are more technically efficient, are bigger or have higher yields are also more efficient in their emissions of GHG emissions. These results suggest that the potential exists for, Scottish dairying to improve its competitiveness and lower greenhouse gas emissions by increasing efficiency, though the extent of the environmental benefits achieved largely depends on how efficiency is increased. [Copyright &y& Elsevier]

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]

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]

Eco-efficiency has been receiving increasing attention across the world. This paper proposes an extended data envelopment analysis model, which combines global benchmark technology, directional distance function and a bootstrapping approach to investigate the dynamic trends of regional eco-efficiency in China from 2003 to 2014. Moreover, a developed slacks-based measure is utilized to decompose the performance fluctuations into resource, environmental and economic efficiency. Then, the key factors responsible for the changes in eco-efficiency are explored using the global Malmquist–Luenberger index. The empirical results demonstrate an upward trend of eco-efficiency in China. During the study period this trend was high in eastern and northern areas but low in northwestern areas. However, it should be noted that some eco-efficient regions still consume much land, water and energy and emit much environmental pollutants in absolute terms. The whole of China performs well on the economic front, while resource and environmental performances are not encouraging, particularly on environmental efficiency. The eastern and northern regions have experienced the greatest advances in both resource and environmental efficiency, while the undeveloped areas have not shown much progress, which further widens the gaps between developed areas and undeveloped areas. The decomposition of productivity growth indicates that technical progress is the decisive factor in promoting China's eco-efficiency, while decreasing management level is the major obstacle hampering the improvement in eco-efficiency. [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]

This paper develops a theoretical background of the inverse DEA with pollution generating technology that is capable of dealing with undesirable outputs. Interaction between input, desirable output, undesirable output and environmental efficiency is investigated for industrial sector of Iranian provinces. Five scenarios are designed to perform this aim and construct a gradual planning scheme for short to long run CO 2 reduction. The following results are found. There exit a high potential of saving capital in short and mid and long-run from 80% to 150% in total. Province P8 and P5 are found as the most effective provinces in terms of saving inputs (labor and capital) in proposed scenarios. No labor reduction is suggested for a short run or for a long run in total, approximately 7%–160% extra labor is needed in the planning period. Some provinces face with infeasibility problem in the planning scheme especially in period on CO 2 reduction. The tightest scenario in terms of CO 2 reduction requires both extra labor and capital while reducing undesirable output and expanding desirable output. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) has been widely applied to evaluate performance in the power generation industry. Nevertheless, most studies view the production system as a “black box”. Few studies attempt to deal with the case of China's thermal power generation industry in the framework of network DEA. Separating the overall power generation process into two internal stages: the production stage and the pollutant abatement stage, with the pollutant emissions as intermediate products, this paper employs a network slacks-based measure (SBM) model to research the production efficiency and environmental efficiency of China's coal-fired power generation industry from 2006 to 2010, under two different tax policies. These two tax policies are the pollution tax policy to negatively penalize for emissions of pollutants and the tax deductions or exemptions policy to positively encourage environmental protection. The empirical results show that the effect of compulsory measures was better than that of self-motivation measures for China's environmental protection in this observation period. Another important finding is that the year 2008 was a turning point in the five years. Statistical analysis shows that the effects of the two different policies were statistically independent. [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]

There is great interest in measuring energy efficiency of China's industry using data envelopment analysis (DEA) approaches. This paper proposes a new exponential transformation of undesirable outputs into desirable outputs as part of a DEA approach for calculating environmental efficiency by using all kinds of classic models. Different from the existing transformations, the exponential model should provide a more flexible way to deal with undesirable outputs, allowing the user to adjust the slope and distribution of the transformation function by setting a parameter. A strategy for maximizing the standard variance among the undesirable outputs after transformation is employed in this paper to determine the optimal parameter value for the exponential model. This paper empirically examines the energy performance of sectors in Chinese industry from 2010 to 2014 using the proposed DEA model and the results show that most sectors in Chinese industry have not performed well, especially the sectors concerned with energy extraction. Based on the results of the efficiency evaluation, this paper calculates how can each sector achieve efficiency improvement through energy conservation and emission reduction, and propose specific improvement target values for each sector accordingly. Image 106227 • Alternative approach is constructed to deal with undesirable output in DEA models. • A new transformation is provided to reflect the exponential relationship between desirable and undesirable outputs. • The slope and distribution of data under the new transformation function are controllable. • The new presented approach is applied to measure the performance of 38 industries in China. [ABSTRACT FROM AUTHOR]

In the recent years, fintech industry of the fourth industrial revolution has grown multifold, which raised the concerns of scholars over the excessive usage of electricity. This paper places contribution to the existing literature by analyzing the impact of fintech industry on environmental efficiency across selected EU countries. We also utilized indicators like high-tech industry and e-commerce along with fintech industry to better understand the relationship between fourth industrial revolution and environmental efficiency. This study used Data Envelopment Analysis (DEA) to evaluate environmental efficiency using two different techniques i.e., Slack-Base Measure (SBM) and Epsilon-Based Measure (EBM). Method of Moments Quantile (MMQ) regression is employed as a basic regression technique, while instrumental variables Generalized method of Moments (IV-GMM) is used for robust analysis. The results show that, the overall environmental efficiency of EU countries have improved over the years. As the indicators of the fourth industrial revolution, fintech industry and e-commerce exert a positive effect and improve environmental efficiency; however, high-tech industry reduces environmental efficiency. The results further show that, economic growth and green finance investment promote environmental efficiency, while industrialization and R&D deteriorates it. The results can be of special interest for the policy makers of technological world. [ABSTRACT FROM AUTHOR]

• DEA was applied to assess the environmental efficiency of EU countries. • Fixed environmental cost allocation is considered at the EU level. • Three novel decision goals are proposed. • Policy measures at EU and each member are recommended. Reasonably measure the environmental efficiency is a significant step towards a greener European Union (EU). This paper proposes several data envelopment analysis (DEA) approaches to evaluate the environmental efficiency of EU countries, considering the allocation of fixed environmental costs and three different decision objectives for each member state. Empirical results for the 28 EU member states from 2013 to 2019 show that the efficiency scores of each member remained broadly stable. Spearman's analysis indicates that the efficiency ranking under economic priority and win–win policy is significantly positively correlated, and the ranking under environment priority is significantly negatively correlated with the rankings under the other two policies. The EU as a whole is most efficient under a win–win strategy, but there are significant differences among member states. Member states that joined the EU earlier have higher efficiency values under economic priority. These results can help the EU and Member states understand strengths and weaknesses and implement appropriate policy measures. [ABSTRACT FROM AUTHOR]

As a main method for achieving environmental protection, improvement of environmental efficiency is vitally important for reducing environmental risk and level of ecological scarcity. Thus, quantitative analysis of environmental efficiency is not only an important premise for understanding the situation of regional environmental protection, but also a prerequisite for designing and adjusting relevant policies. In this paper, we treat the undesirable output in an economic activity by a linear monotonic decreasing transformation approach. We employ data envelopment analysis (DEA) technique to evaluate environmental efficiency in 30 provinces of China during the period 2001–2010, and conduct hypothesis tests on these environmental efficiencies. Furthermore, we investigate the horizontal differences of environmental efficiency in six regions of China and the vertical differences among different years. The results show that our empirical tests have a high statistical reliability that provides support for prompting environmental policies in different parts of China. [ABSTRACT FROM AUTHOR]

As environmental problems become more and more serious all over the world, environmental efficiency evaluation has drawn increasing interests of many scholars and governments’ decision makers. Data envelopment analysis (DEA) as a non-parametric approach for evaluating the relative efficiency of a group of decision making units (DMUs) has been widely extended and applied in many areas. Among various DEA models, enhanced Russell measure (ERM) model can measure the inefficiencies from input orientation and output orientation simultaneously. In this paper, we proposed a new non-orientation DEA approach based on enhanced Russell measure for measuring the environmental efficiency of a DMU and meanwhile, provided the closest target for the evaluated DMU to efficient with less effort. At last, our approach was applied to a practical example about thermal power enterprises. The results show that our model can provide a much easier way for the inefficient enterprises to improve their efficiencies than the enhanced Russell measure method. Moreover, the provided benchmarks for enterprises through our model can be used to further rank the efficient ones. [ABSTRACT FROM AUTHOR]

Abstract: With the implementation of the strategic policy and the construction of Wanjiang demonstration area recently, the government cares more about the natural environment. To protect the environment of this demonstration area, a quantitative analysis of environmental efficiency and its influencing factors is needed. In this paper, we measure the environmental efficiency of the demonstration area, and then analyze the total factor productivity of the area by Malmquist productivity index through data envelopment analysis (DEA) approach. Through the index and its decomposition, we are able to reveal the changing trend of the environmental efficiency. Moreover, we apply Bayesian estimation approach to analyze the influencing factors of the efficiency and discuss the relationship between these factors and the environmental efficiency. Results show that the efficiency of Wanjiang demonstration area bares a significant difference among constituent cities. Each area should devise proper environmental policy according to its particular circumstance. [Copyright &y& Elsevier]

Improving the express industry's environmental efficiency is of practical significance to green and sustainable economic development. The development of internet may help achieve this goal. However, previous studies have not provided a consistent result about the relationship between internet development and the express industry's environmental efficiency. This paper provides a deeper understanding of this relationship by analyzing the threshold effects from the perspectives of road network density, openness to international trade and competition, and e-commerce level. Based on Chinese provincial data from 2012 to 2017, we first use a range directional data envelopment analysis model to evaluate the express industry environmental efficiency. Then, a threshold model is constructed to analyze the threshold effects in the relationship between internet development and environmental efficiency. The results show that: (1) The impact of internet development on the express industry's environmental efficiency shows a single threshold effect as road network density increases, which indicates that internet development significantly improves that environmental efficiency when the road network density is above a threshold value. (2) The impact of internet development on express industry environmental performance shows a dual-threshold effect as the degree of openness increases. (3) There is also a dual-threshold effect in this relationship as the proportion of e-commerce business transactions increases, but this effect is not significant. Based on these results, suggestions are given for the express industry to improve its environmental efficiency in China. [ABSTRACT FROM AUTHOR]

Abstract: Recently, environmental pollution has attracted a lot of attention domestically and internationally. It is known that energy utilization is a major source of China’s environmental pollution. Measuring environmental efficiency of energy utilization in Chinese provinces first, the paper then offers decision supports for relevant departments in order to achieve sustainable development of energy and environment in China. This research chooses CO2 emission as a substitute variable for environmental effects of energy utilization and puts it into the study framework based on total-factor production theory to measure the environmental efficiency of energy utilization of each province and three major regions. On the basis of the above results this research further measures the cost of environmental regulation for each province. Provincial panel data during the period of 2000–2007 are used to carry out empirical study. The analysis indicates that the environmental efficiency of energy utilization in Chinese provinces varies greatly from each other, meaning that both economic output and CO2 emissions need considerable improvement. In addition, the results of empirical study also show that the environmental efficiency of energy utilization in China is quite low. Therefore, to ensure sustainable development of China’s energy, economy and environment, we should resort to advanced technology as the support to promote the efficient and clean utilization of energy resources. Besides, most Chinese provinces have spent quite a lot on environmental regulation, implying that in these provinces development of the economy and the environment are not in harmony. The contributions of this research are as follows: it constructs the models for measuring environmental efficiency of energy utilization in Chinese provinces; it introduces the idea of “environmental regulation” into research system and measures the environmental regulation cost of each Chinese province. [Copyright &y& Elsevier]

Abstract: In this paper, the environmental efficiencies of 39 industrial sectors are measured using a non-radical, non-oriented slacks-based measure (SBM) model that considers the environmental impact of each industry. The economic efficiency of each industrial sector is measured using traditional data envelope analysis (DEA) methods and the differences between environmental efficiency and economic efficiency are analyzed using the transverse analysis method. A total of 39 industrial sectors are examined within three main industrial sectors (mining, manufacturing, and supply). Using the longitudinal analysis method, the environmental efficiencies of the three main industrial sectors from 2002 to 2009 are analyzed using the average value of their sub-industries’ environmental efficiencies. The time regression equation of the three industrial fields’ environmental efficiencies is examined using a regression analysis method. Based on these results, tactics for enhancing the environmental efficiency of Chinese industries are suggested in accordance with the characteristics of each industrial sector’s environmental efficiency. [Copyright &y& Elsevier]

By-production (BP) technologies, modeled as an intersection of intended production technologies (production efficiency) and nature's residual-generation technologies (environmental efficiency), was applied in this paper to estimate the regional eco-efficiency in China during 2008–2017. This model is firstly formulated by directional-distance-function (DDF) and Färe-Grosskopf-Lovell (FGL), and then modified by bootstrap sensitivity analysis. The empirical results demonstrate that: (i) BP technologies based on the multiple production relations tend to produce lower efficiency scores than conventional model based on a single production relation. Moreover, BP-FGL can be a better choice for the measurement of efficiency index; (ii) The low economic development level is not necessarily associated with low environmental efficiency. Most of the eastern provinces had superior production efficiencies while inferior environmental efficiencies compared with inland provinces; (iii) At the regional level, a greater improvement in environmental efficiency than in production efficiency can be observed, and the gaps on the latter had widened over time among these regions; (iv) The great efficiency gaps between production efficiency and environmental efficiency appeared in the North Coast and Northwest, which are disadvantage to the inter-regional coordinated development. The results indicate that promoting production performance is crucial to improve the eco-efficiency for sustainable development in China. Image 10492 • BP technologies based on multiple production relation is applied. • Most of the eastern provinces have superior production efficiency. • Some western provinces perform well in environmental efficiency. • A greater improvement in environmental efficiency than in production efficiency. • Great efficiency gaps appeared in North Coast and Northwest regions. [ABSTRACT FROM AUTHOR]