A comparative study among fossil fuel power plants in PJM and California ISO by DEA environmental assessment

This study compares among fossil fuel power plants in PJM and California ISO by their unified (operational and environmental) performance. DEA (Data Envelopment Analysis) is used as a methodology. For comparative analysis, DEA incorporates strategic concepts such as natural and managerial disposability into the computational process. This study explores both how to measure Returns to Scale (RTS) under natural disposability and how to measure Damages to Scale (DTS) under managerial disposability. This empirical study obtains two implications on US energy policy. One of the two policy implications is that California ISO outperforms PJM in terms of the three unified efficiency measures. The result implies that strict regulation on undesirable outputs, as found in California, is important in enhancing the performance of US fossil fuel power plants. Thus, it is necessary for federal and local governments to regulate the fossil fuel power plants under the strict implementation of environmental protection. Under such a policy direction, it is possible for US fossil fuel power plants to attain economic prosperity (by enhancing their operational efficiencies) and to satisfy environmental regulation (by enhancing their environmental efficiencies). The other policy implication is that coal-fired and gas-fired power plants in PJM and California ISO need to reduce their operational sizes or introduce technology innovation on desirable and undesirable outputs and/or new management for environmental protection within their operations. Meanwhile, oil-fired power plants may increase their operational sizes if they can introduce technology innovation and new management on undesirable outputs.     

Performance analysis of US coal-fired power plants by measuring three DEA efficiencies

Data Envelopment Analysis (DEA) has been widely used for performance evaluation of many organizations in private and public sectors. This study proposes a new DEA approach to evaluate the operational, environmental and both-unified performance of coal-fired power plants that are currently operating under the US Clean Air Act (CAA). The economic activities of power plants examined by this study are characterized by four inputs, a desirable (good) output and three undesirable (bad) outputs. This study uses Range-Adjusted Measure (RAM) because it can easily incorporate both desirable and undesirable outputs in the unified analytical structure. The output unification proposed in this study has been never investigated in the previous DEA studies even though such a unified measure is essential in guiding policy makers and corporate leaders. Using the proposed DEA approach, this study finds three important policy implications. First, the CAA has been increasingly effective on their environmental protection. The increased environmental performance leads to the enhancement of the unified efficiency. Second, the market liberalization/deregulation was an important business trend in the electric power industry. Such a business trend was legally prepared by US Energy Policy Act (EPAct). According to the level of the market liberalization, the United States is classified into regulated and deregulated states. This study finds that the operational and unified performance of coal-fired power plants in the regulated states outperforms those of the deregulated states because the investment on coal-fired power plants in the regulated states can be utilized as a financial tool under the rate-of-return criterion of regulation. The power plants in the deregulated states do not have such a regulation premium. Finally, plant managers need to balance between their environmental performance and operational efficiency.     

A multiplicative environmental DEA approach to measure efficiency changes in the world's major polluters

We propose a multiplicative environmental data envelopment analysis (ME-DEA) approach to measure the performance of 46 countries that generate most of the world's carbon dioxide (CO₂) emissions. In the model, we combine economic (labour and capital), environmental (freshwater) and energy inputs with a desirable output (GDP) and three undesirable outputs (CO₂, methane and nitrous oxide emissions). We rank each country according to the optimum use of its resources employing a multiplicative extension of environmental DEA models. By computing partial efficiency scores for each input and output separately, we thus identify major sources of inefficiency for all sample countries. Based on the partial efficiency scores obtained from the model, we define aggregate economic, energy and environmental efficiency indexes for 2002, 2007 and 2011, reflecting points in time before and after the official enactment of the Kyoto Protocol. We find that for most countries efficiency scores increase over this period. In addition, there exists a positive relationship between economic and environmental efficiency, although, at the same time, our results suggest that environmental efficiency cannot be realized without first reaching a certain threshold of economic efficiency. We also find support for the Paradox of Plenty, whereby an abundance of natural and energy resources results in their inefficient use.     

DEA window analysis for environmental assessment in a dynamic time shift: Performance assessment of U.S. coal-fired power plants

This study discusses a new use of window analysis for DEA environmental assessment in a time horizon where DEA stands for Data Envelopment Analysis. The data sets on environmental protection are often structured by time series. In applying DEA to environmental assessment, it is necessary for us to examine a frontier shift between different periods because it indicates a technology progress on desirable and undesirable outputs. An important feature of the proposed approach is that it incorporates the concept of natural and managerial disposability into the computational framework of DEA and extends the two disposability concepts in a time horizon. To capture the frontier shift, this study proposes a new type of DEA window analysis for environmental assessment. This study applies the proposed DEA window analysis to a data set on U.S. coal-fired power plants during 1995–2007. The application finds that the coal-fired power plants have gradually paid attention to environmental protections under Clean Air Act (CAA). Consequently, their performance under managerial disposability has increased from 1996 to 2007. This indicates the importance of CAA and regulation on industrial pollutions. Thus, it is necessary for the United States to extend the scope of CAA for controlling the amount of CO₂ emission because current regulation has a limited policy influence on the source of global warming and climate change in our modern society.     

Environmental assessment on coal-fired power plants in U.S. north-east region by DEA non-radial measurement

This study discusses a new use of DEA (Data Envelopment Analysis) environmental assessment to measure unified (operational and environmental) and scale efficiencies among inputs, desirable and undesirable outputs. In particular, the measurement of scale efficiency is discussed by two non-radial models. That is a new methodological contribution. To discuss these efficiency measures, this study first examines a concept of disposability from the perspective of corporate strategies to adapt a regulation change on undesirable outputs. The concept is separated into natural and managerial disposability. After discussing how to measure the degree of scale efficiency within the non-radial approach, this study applies the proposed DEA environmental assessment to measure the performance of coal-fired power plants in the U.S. north-east region. The region has been long producing a large amount of coal from the Appalachian Mountains. The coal mining industry has supported U.S. energy utility and other industries. Because of the long history, the quality of coal became worse and the coal-fired power plants have been producing a large amount of undesirable gases. This study has statistically confirmed that there is a significant difference between the two types (BIT: bituminous coal and SUB: subbituminous coal) of coal-fired power plants in terms of their unified efficiency measures, including their scale efficiencies, under the concept of managerial disposability (the first priority: environment performance and the second priority: operational performance). In contrast, under the natural disposability (the first priority: operational performance and the second priority: environmental performance), this study cannot find such a statistical significance between them. The fact, in which BIT outperforms SUB in terms of their unified and scale efficiencies, suggests the policy implication that these power plants need to shift their coal combustions from SUB to BIT in the United States. Besides the empirical finding, this study cannot confirm the other hypothesis on whether coal-fired power plants with small operation (less than 50% in plant capacity factor) outperform ones with large operation (more than 50% in plant capacity factor), and vice versa, in terms of their unified and scale efficiency measures under natural and managerial disposability. An exception is found in environmental performance under variable returns to scale. The rationale is because their plant operations are frequently monitored by regulatory agencies. As a consequence, this study cannot find such a statistical difference between them on operational performance. This result implies that the regulation on coal-fired power plants has been effective on their unified performance but large power plants may have a potential to improve their environmental performance.     

Environmental assessment for corporate sustainability by resource utilization and technology innovation: DEA radial measurement on Japanese industrial sectors

This study proposes a new use of DEA (Data Envelopment Analysis) radial approach to examine the corporate sustainability of Japanese industrial sectors. The concept of corporate sustainability is measured by its subcomponent measures, including UEN (Unified Efficiency under Natural Disposability), UEM (Unified Efficiency under Managerial Disposability), UENM (Unified Efficiency under Natural and Managerial Disposability), UEI (Unified Efficiency for Intermediate measurement) and UENM(DC) (Unified Efficiency under Natural and Managerial Disposability with Desirable Congestion). Among the five measures, the UEI examines a degree of how each firm can efficiently utilize its resources. The UENM(DC) examines a degree of how the firm can reduce an amount of undesirable outputs by technology innovation and/or managerial change. Such a combined use between UEI and UENM(DC) has been never explored in DEA environmental assessment. The empirical results obtained from the proposed approach have identified two important implications. One of the two implications is that the Japanese energy industry has been long under governmental regulation so that energy firms do not have corporate governance capabilities at the level of other industrial sectors which are competing in a global market. In particular, the implication is applicable to Japanese electric power firms. It is necessary for them to change their corporate governances (e.g., by adding new executive board members who have international experience and/or woman executives, as widely found in American and European energy industries) so that they can pay attention to consumers, not regulatory agencies of the Japanese government. The other implication is that technology innovation can more effectively improve the performance of the energy sector. Employing high efficiency and low carbon generation technologies to achieve desirable fuel mix is essential for improving the corporate sustainability of the Japanese energy sector.     

DEA environmental assessment in time horizon: Radial approach for Malmquist index measurement on petroleum companies

The climate change and various pollutions have been influencing our societies and economies. The environmental assessment, to be discussed in this study, is increasingly important because it serves as an initial step toward pollution prevention. Corporate leaders, policy makers, researchers and individuals who are interested in environmental protection have been paying attention to the assessment so that they can prepare policy suggestions on the global warming and climate change. As a methodology for the assessment, this study proposes a use of Data Environment Analysis (DEA) in a time horizon. Most of data sets on the climate change are sampled in a time series where the performance of organizations fluctuates every moment. In applying the DEA environmental assessment to such a data set, it is necessary for us to classify outputs into desirable (e.g., oil production) and undesirable (e.g., CO₂ emission) categories because all organizations usually produce not only desirable but also undesirable outputs as a result of their economic activities. To unify the two different types of outputs, this study incorporates the concept of natural and managerial disposability into the computational framework of DEA and extends them into a time horizon. For the research purpose, this study incorporates Malmquist index into the proposed DEA environmental assessment to examine an occurrence of a frontier shift among multiple periods. The frontier shift indicates a technology progress and/or managerial innovation during an observed period. The index is further separated into four subcomponents in a time horizon. These subcomponents are differently expressed under the natural and managerial disposability. Thus, eight different subcomponents on the Malmquist index are proposed to measure the frontier shift. As an application, this study uses the proposed DEA approach to examine whether the frontier shift (due to technology progress) occurs or not in the petroleum industry from 2005 to 2009. Our empirical study finds that the industry has not exhibited any major frontier shift under natural disposability, but showing a considerable frontier shift under managerial disposability. In other words, the petroleum firms have improved their environmental performance by eco-technology to reduce an amount of CO₂ emission during the observed annual periods.     

Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention

This study examines the level of simultaneous achievement on economic prosperity and environmental protection, so measuring the level of sustainability by a newly proposed intermediate approach. Conventionally, DEA (Data Envelopment Analysis) for performance evaluation was used to assess various economic activities of organizations that utilized inputs (e.g., the number of employees) to yield desirable outputs (e.g., the number of products). The methodology was usually classified into radial or non-radial category. In an effort of extending it to environmental assessment, DEA needs to incorporate undesirable outputs (e.g., the amount of CO₂) into the computational framework. This type of assessment is referred to as “DEA environmental assessment”. The proposed intermediate approach develops a new type of DEA environmental assessment by combining the analytical features of radial approach with those of non-radial approach. The new approach measures the level of unified inefficiency on each production factor and determines the level of total unified inefficiency from the average of the sum of these inefficiency scores. A rank sum test and a mean test are additionally incorporated into the proposed intermediate approach. Such a combination enhances the statistical capability. As an application, this study examines the level of sustainability related to 30 provinces in China from 2003 to 2014. The application finds four policy implications. First, it is important for China to allocate its resources to western provinces at a level that it has used for coastal developments. Second, the government continues to reinforce the policy making effort on environmental protection by paying attention to central and southern regions. The Chinese industries need to transfer toward “green” energy. The transfer should be efficiently executed for their future developments. Third, the government has focused on the sustainability development in urban provinces and then has gradually shifted the policy influence toward rural areas. Finally, the policy implementation needs a time lag until it becomes effective. The time lag on economic policy is longer than that of environmental policy. The economic policy has historically produced a regional imbalance, often leading to educational and income imbalances, among Chinese provinces.     

Should the US clean air act include CO2 emission control?: Examination by data envelopment analysis

This study proposes a new use of Data Envelopment Analysis (DEA) to measure the operational, environmental and both-unified efficiency measures of US coal-fired power plants. The power plants produce not only desirable outputs (e.g., electricity) but also undesirable outputs (e.g., CO₂ and NO_x) as a result of their plant operations. A Range-Adjusted Measure (RAM) is used as an original non-radial DEA model. Then, it is reformulated for handling undesirable (bad) outputs. The proposed use of DEA models measures the environmental and unified performance of power plants under two variable alternatives (with and without CO₂ emission control) in order to examine both the influence of US Clean Air Act (CAA) on the acid rain causing gases (NO_x and SO₂) and its extension to the CO₂ regulation. This study finds that the acid rain program under the CAA has been effective on the emission control of SO₂ and NO_x produced at US coal-fired power plants. Moreover, additional regulation on CO₂ may enhance their environmental and unified performance. Thus, it is recommended that the US federal and state governments need to expand the legal scope of CAA to the emission control on CO₂ because the gas is considered as a main source of global warming and climate change.     

Methodological comparison among radial,non-radial and intermediate approaches for DEA environmental assessment

This study compares three DEA approaches for environmental assessment, all of which are designed to examine the level of simultaneous achievement on economic prosperity and environmental protection, so measuring the degree of sustainability development. DEA, standing for Data Envelopment Analysis, has been widely applied for performance assessment in the past five decades. A new type of applications is referred to as “DEA environmental assessment” and it measures the performance of many organizations that utilize inputs to produce not only desirable outputs (e.g., electricity) but also undesirable outputs (e.g., CO₂). In the previous studies, DEA-based performance evaluation for environment assessment is methodologically classified into radial or non-radial category. Recently, a new “intermediate” approach, analytically locating between the radial and non-radial measures, has been proposed as the third alternative. A use of the intermediate approach has several unique features, all of which cannot be found in the radial and non-radial ones. The new approach measures the degree of unified inefficiency on each production factor and determines the level of total unified inefficiency from the average of the sum of these inefficiency scores. This study discusses the analytical features by comparing the intermediate approach with the radial and non-radial ones. The methodological comparison attempts to convey a message that DEA is indeed an important methodology, but not perfect. Rather, it is an approximation approach to examine the performance of various organizations. Many DEA applications on energy and environment often suffer from a methodological bias, implying that different approaches produce different empirical results. Thus, in guiding a large policy issue such as the global warming and climate change, it is necessary for us to compare several different approaches (e.g., models and concepts) to derive a reliable empirical suggestion. The importance of such a message is applicable to not only DEA but also the other types of empirical research in natural and social sciences. Therefore, this study discusses the methodological bias issue from the practicality of the three DEA approaches in assessing various concerns on energy and environment.     

Linear programming models for measuring economy-wide energy efficiency performance

Data envelopment analysis (DEA) has recently gained popularity in energy efficiency analysis. A common feature of the previously proposed DEA models for measuring energy efficiency performance is that they treat energy consumption as an input within a production framework without considering undesirable outputs. However, energy use results in the generation of undesirable outputs as by-products of producing desirable outputs. Within a joint production framework of both desirable and undesirable outputs, this paper presents several DEA-type linear programming models for measuring economy-wide energy efficiency performance. In addition to considering undesirable outputs, our models treat different energy sources as different inputs so that changes in energy mix could be accounted for in evaluating energy efficiency. The proposed models are applied to measure the energy efficiency performances of 21 OECD countries and the results obtained are presented.     

DEA environmental assessment in a time horizon: Malmquist index on fuel mix,electricity and CO2 of industrial nations

Climate change and global warming become a major policy issue in the world. Economic activities produce not only desirable outputs (e.g., electricity) but also undesirable outputs (e.g., CO₂ emission). The important policy issue is how each nation can balance between economic development and environmental protection to attain a sustainable society. In attaining the sustainable society, environmental assessment is increasingly important because it can serve as an initial step toward the green growth of each nation. For the purpose, this study proposes a new use of DEA (Data Environment Analysis) for environmental assessment in a time horizon. The proposed use of DEA incorporates Malmquist index to examine the degree of a frontier shift among multiple periods. The frontier shift indicates a technology progress and/or managerial innovation during an observed period. The index is conceptually separated into six subcomponents, which are further divided into twelve different subcomponents (six subcomponents × two disposability concepts) under the natural and managerial disposability. In the index measurement, it is necessary for us to consider a frontier crossover among different periods because technology innovation usually has a time lag until it really appears. As an empirical application, this study utilizes the proposed approach to identify the relationship among fuel mix, electricity and CO₂ of ten industrial nations. This study finds three important empirical findings. First, there is a time lag in technology innovation on electricity generation and CO₂ emission reduction. Consequently, it is necessary to consider the existence of a frontier crossover in assessing the electric power industry. Second, nuclear generation, as found in France, as well as hydro and renewable energy, as found in Netherlands, are important for the development of a sustainable society although the former is associated with a very high level of risk and the latter has a limited generation capacity. Finally, the electric power industry has been making a corporate effort to reduce the amount of CO₂ emission by utilizing nuclear and renewable energy.     

A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case

This paper contributes to the current literature by proposing an alternative parametric metafrontier productivity approach called the deterministic parametric metafrontier Luenberger Productivity Indicator (DPMLPI) for measuring environmentally sensitive productivity growth incorporating technological heterogeneities. The Luenberger productivity indicator is constructed based on a quadratic output directional distance function with undesirable outputs, and then combined with the deterministic metafrontier to develop DPMLPI. The DPMLPI can be decomposed into efficiency change, technological change and productivity growth gap. The productivity growth gap can be further divided into efficiency change gap and technological change gap. The parametric linear programming technique is used to estimate parameters and construct the metafrontier. An empirical study for the Korean fossil fuel power industry at the plant-level is conducted for the 2003–2011 period. The results show a 0.15% increase in environmentally-sensitive productivity growth, which is mainly driven by environmental technological change. The oil-fired power plants show higher levels than the coal-fired ones of environmentally sensitive productivity growth and technological change performance. Some related policy implications are also proposed for the Korean fossil-fuel power sector.     

Measuring eco-efficiency based on green indicators and potentials in energy saving and undesirable output abatement

Nowadays, majority of organizations are seeking to achieve sustainable development with respect to “green” concept. One of the main criteria for assessing green performance is eco-efficiency. To identify all aspects of the eco-efficiency, inputs should be divided into energy and non-energy and outputs should be divided into good and bad outputs. To deal with this issue, a data envelopment analysis (DEA) model is developed to divide inputs into both energy and non-energy and outputs into both desirable (good) and undesirable (bad) outputs. Likewise, variables are separated into both discretionary and non-discretionary factors. Accordingly, a bounded adjusted measure (BAM) based on green indicators is developed to calculate the eco-efficiency of decision making units (DMUs). Besides, energy saving potentials and undesirable output abatement potentials are calculated to show correlation coefficient between energy consumption and undesirable output. Finally, proposed model is validated by assessing the eco-efficiency of some selected members of organization for economic cooperation and development (OECD). Australia, Finland, Ireland, New Zealand, and Switzerland are recognized as eco-efficient countries and the rest of countries are inefficient in terms of the eco-efficiency. High and positive Spearman correlation coefficient between energy consumption and undesirable outputs addresses that the more use of energy inputs, the more undesirable outputs.     

Undesirable congestion under natural disposability and desirable congestion under managerial disposability in U.S. electric power industry measured by DEA environmental assessment

This study discusses a new use of DEA environmental assessment to measure a possible occurrence of desirable congestion, or eco-technology innovation, in electric power plants. The phenomenon is compared with an occurrence of undesirable congestion in this study. The identification of undesirable congestion is important to avoid a cost increase and a shortage of generation. However, the identification of desirable congestion is much more important than that of undesirable congestion from the perspective of environmental assessment. This study looks for a sustainable economic growth by identifying eco-technology innovation that can be effectively used to reduce the amount of air pollution so that electric power companies satisfy a governmental standard on environmental protection. The proposed approach is applied to evaluate the performance of coal-fired power plants in the United States. This study finds two policy implications. First, power plants operated by bituminous coal (i.e., black coal) outperform those with sub-bituminous coal (i.e., brawn coal). The result implies that power plants with sub-bituminous coal should be replaced by bituminous coal. Second, the undesirable congestion, due to a line limit between points of power generation and consumption, may occur on most of coal-fired power plants. In contrast, desirable congestion, due to eco-technology innovation, may occur on a limited number of power plants. Thus, the identification of desirable congestion assists us in selecting which technology, or the type of power plant, should be invested to facilitate eco-technology innovation and its related engineering management for a future sustainable economic growth.     

Investment strategy for sustainable society by development of regional economies and prevention of industrial pollutions in Japanese manufacturing sectors

A balance between industrial pollution prevention and economic growth becomes a world-wide issue to develop a sustainable society in many industrial nations. To discuss the issue, this study proposes a new use of DEA environmental assessment to determine how to effectively allocate capital for developing regional industries. The amount of capital is used to invest for technology innovation for both local economic growth and environmental protection. In this study, the proposed approach separates outputs into desirable and undesirable categories. Inputs are also separated into two categories, one of which indicates an amount of investment on capital assets. The other category is used for production activities. The proposed approach unifies them by two disposability concepts. This study has evaluated the performance of manufacturing industries in 47 prefectures (local government units in Japan) by Unified Efficiency under Natural disposability (UEN), Unified Efficiency under Managerial disposability (UEM) and Unified Efficiency under Natural and Managerial disposability (UENM). The UENM is further separated into its two cases: with and without a possible occurrence on desirable congestion, or technology innovation, on undesirable outputs. This study has empirically confirmed that Japanese manufacturing industries need to make their efforts to reduce greenhouse gas emissions and air pollution substances by investing in technology innovation. Furthermore, most of economic activities are currently located at metropolitan regions (e.g., Tokyo) in Japan. To develop a sustainable society, Japan needs to allocate capital into regions with a high level of investment effectiveness by shifting the manufacturing industries from the metropolitan regions to much promising local areas identified in this study. Such a shift, along with technology innovation, makes it possible to reduce air pollutions in the entire Japan by balancing economic growth and pollution prevention. This empirical study confirms that the proposed approach is useful in both guiding regional planning and developing a sustainable society. It is easily envisioned that the proposed approach is useful for not only Japan but also the other industrial and developing nations.     

The effectiveness of environmental authoritarianism: Evidence from China's administrative inquiry for environmental protection

In order to improve China's environmental quality, the central government has strengthened the environmental responsibility of local governments, and adopted supervision tools such as environmental protection inquiries and inspections to promote local governments to be more proactive in environmental issues. In this paper, the global non-radial direction distance function (NDDF) and difference-in-difference (DID) method are used to analyze the impact of the environmental protection inquiry on energy-environmental efficiency. Specifically, taking energy, capital, and labor as input factors, regional GDP as desirable output, and sulfur dioxide, dust, and wastewater emissions as undesirable outputs, the unified energy-environmental efficiency index (UEEI) of each city has been estimated with the global NDDF method. The results show that UEEI in the eastern and central regions are relatively high, while that in the north and northeast regions are relatively low. On this basis, the impact of environmental protection inquiry on UEEI of each city is analyzed with the DID method. The results show that the environmental protection inquiry can significantly improve the energy-environmental efficiency of atmospheric pollutants, but the effect on energy-environmental efficiency of wastewater emission is not significant.     

Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model

Data envelopment analysis (DEA) has gained much popularity in performance measurement of power industry. This paper presents a slack-based measure approach to investigating the relationship between fossil fuel consumption and the environmental regulation of China's thermal power generation. We first calculate the total-factor energy efficiency without considering environmental constraints. An environmental performance indicator is proposed through decomposing the total-factor energy efficiency. The proposed approach is then employed to examine whether environmental regulation affects the energy efficiency of China's thermal power generation. We find that the environmental efficiency plays a significant role in affecting energy performance of China's thermal generation sector. Decreasing the discharge of major pollutants can improve both energy performance and environmental efficiency. Besides, we also have three main findings: (1) The energy efficiency and environmental efficiency were relatively low. (2) The energy and environmental efficiency scores show great variations among provinces. (3) Both energy efficiency and environmental efficiency are of obvious geographical characteristics. According to our findings, we suggest some policy implications.     

Environmental efficiency evaluation based on data envelopment analysis: A review

The paper aims to investigate the achievements of the theoretical and practical basis of environmental policy analysis in order to study their works and point out the future possible research direction. It sorts out researches about environmental efficiency assessment and reviews the works about the theory and application of efficiency analysis around the world. It is suggested that environmental efficiency evaluation theory under small samples and DEA method with undesirable outputs will further extend the research on environmental efficiency evaluation. Also, this review confirms that more studies in methods and their applications in this area are in urgent need.     

Environmental efficiency of the Indian cement industry: An interstate analysis

Coal combustion, for the production of cement, generates considerable amount of environmentally detrimental carbon dioxide as an undesirable by-product. Thus, this paper aims at measuring environmental efficiency within a joint production framework of both desirable and undesirable output using Data Envelopment Analysis and Directional Distance Function. Carbon dioxide is considered as an input in one context and as an undesirable output in the other with the environmental efficiency being defined accordingly. Using 3 digit sate level data from the Annual Survey of Industries for the years 2000–2001 through 2004–2005, the proposed models are applied to estimate environmental efficiency of Indian cement industry. Empirical results show that there is enough potential for the industry to improve its environmental efficiency with efficiency being varied across states. Results also show that Indian cement industry, if faced with environmental regulation, has the potential to expand desirable output and contract undesirable output with the given inputs. However, regulation has a potential cost in terms of lower feasible expansion of desirable output as compared to unregulated scenario.