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.     

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.     

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.     

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.     

DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation

This study discusses a new DEA (Data Envelopment Analysis) approach to measure the unified (operational and environmental) efficiency of energy firms. It is widely known that they produce not only desirable (good) outputs (e.g., electricity) but also undesirable (bad) outputs (e.g., CO₂) as a result of their plant operations. The proposed approach incorporates an output separation (desirable and undesirable outputs) for the performance evaluation of energy firms. In addition to the output separation, this study separates inputs into energy and non-energy inputs. Consequently, the proposed approach incorporates not only the output separation but also the input separation within a computational framework of DEA non-radial measurement. This study compares the proposed approach with other previous DEA approaches used for the performance evaluation of energy firms. After the methodological comparison, this study applies the proposed approach for measuring the unified efficiency of Japanese fossil fuel power generation. This empirical study confirms that the implementation of Kyoto Protocol (2005) has not been effective on the unified efficiency of Japanese fossil fuel power generation during the observed period (2004-2008). Although the empirical result is inconsistent with the current Japanese environmental policy under Kyoto Protocol, it contains policy implications for guiding the future direction of Japanese environmental policy on the electric power industry.     

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.     

Assessment of operational and environmental performance of the thermal power plants in Turkey by using data envelopment analysis

In this study, efficiency analyses of the eleven lignite-fired, one hard coal-fired and three natural gas-fired state-owned thermal power plants used for electricity generation were conducted through data envelopment analysis (DEA). Two efficiency indexes, operational and environmental performance, were defined and pursued. In the calculation of the operational performance, main production indicators were used as input, and fuel cost per actual production (Y) was used as output (Model 1). On the other hand, in the calculation of the environmental performance, gases emitted to the environment were used as output (Model 2). Data envelopment analysis (DEA) is the main instrument for the measurement of relative performances of the decision making units with multiple inputs and outputs. Constant returns to scale (CRS or CCR) and variable returns to scale (VRS or BCC) type DEA models were used in the analyses. The relationship between efficiency scores and input/output factors was investigated. Employing the obtained results, the power plants were evaluated with respect to both the cost of electricity generation and the environmental effects.     

Unified efficiency measurement of coal-fired power plants in China considering group heterogeneity and technological gaps

China's coal-fired power generation has accounted for a large proportion of the power supply for a long time and the resulting environmental pollution and waste of resources have hindered the sustainable development of the power industry. To solve this problem, this study combines the concept of natural and managerial disposability with the non-concave meta-frontier method to determine the unified efficiency measurement of 251 coal-fired power plants in China from 2012 to 2014 and to investigate the sources of inefficiency in different areas. The results show that although the unified efficiency of China's coal-fired power plants improved significantly during 2012–2014, much room for improvement remains in terms of power generation and environmental performance. Due to the advanced technology of coal-fired power plants, the eastern area has the highest unified efficiency in terms of natural and managerial disposability. The western region has the lowest operational performance and the northeast region has the lowest environmental performance. The decomposition of the sources of inefficiency indicates that the inefficiency of coal-fired power plants in eastern China is mainly caused by management factors, whereas the inefficiency in northeastern China is due to a lag in technology. In the central and western areas, technical inefficiency and management inefficiency both account for a considerable proportion in their sources of inefficiency. Therefore, these regions need to improve both the management (e.g., reasonable allocation of utilization hours) and technology (e.g., clean coal technology) aspects to improve the unified performance of coal-fired power plants.     

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.     

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.     

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.     

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.     

Can environmental investment and expenditure enhance financial performance of US electric utility firms under the clean air act amendment of 1990?

This study investigates the causality from environmental investment (as a long-term effort) and expenditure (as a short-term effort) to financial performance in the US electric utility industry. The industry is one of the large air polluters in the United States. This empirical study finds that the environmental expenditure under the US Clean Air Act has had a negative impact from 1989 to 2001. The negative impact has become much effective after the implementation of the Title IV Program (1995) of the US Clean Air Act. This study cannot find the influence of environmental investment on financial performance by a statistical test although it indicates a positive impact. In the United States, fossil-fueled power plants such as coal-fired ones still produce a large portion of electricity. The generation structure is inconsistent with the betterment in the US environmental protection and imposes a financial burden to electric utility firms.     

The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants

Different from previous efficiency researches, which normally assume a uniform disposability for all undesirable outputs in a production process, this paper proposes a model that distinguishes weak and strong disposability assumptions among various undesirable outputs based on their respective technical features. The paper illustrates the approach using a research sample covering 582 base-load Chinese coal-fired power plants in 2002. The final results show that imposing the technically correct disposability features on undesirable outputs makes a significant difference to the final efficiency evaluation. This suggests the necessity of properly distinguishing disposability features among undesirable outputs in a production process in efficiency models.     

Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs

The industry in China has been developing extensively in the last few decades. Large investments in China's industry may cause congestion because congestion is a widely observed economic phenomenon in such a scenario. In order to know the performance and allocate resources well, it is necessary for the Chinese government to measure congestion of the industry. Many scholars have studied this topic by means of data envelopment analysis (DEA). However, previous studies only pay attention to the framework of desirable outputs. In fact, undesirable outputs often accompany desirable outputs in production. Thus, in this study, a new approach for measuring congestion with undesirable outputs is proposed and applied to analyzing congestion of the industry in 31 administrative regions of China. The results show that five regions have congestion in their industry in 2010. Besides, the regions located in the east of the country perform the best in ecological efficiency, followed by regions in central and west China. Based on these findings, this paper proposes some political schemes to improve regional industrial efficiency.     

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.     

Marginal Rate of Transformation and Rate of Substitution measured by DEA environmental assessment: Comparison among European and North American nations

This study discusses the new use of DEA (Data Envelopment Analysis) environmental assessment to measure MRT (Marginal Rate of Transformation) and RS (Rate of Substitution) among production factors (e.g., inputs, desirable and undesirable outputs). To measure the degree on MRT and RS, this study first examines a concept of disposability from the perspective of economic strategies to combat various environmental issues. The strategies are extendable to a policy change for pollution prevention. The underlying concept is separated into natural and managerial disposability. Under managerial disposability, it is possible for us to measure an occurrence of desirable congestion, or eco-technology innovation. Considering the disposability concept, this study discusses how to measure the type and magnitude of MRT and RS. A problem of the MRT & RS measurement is that these measures usually become unstable (e.g., very large or small in these magnitudes) because DEA does not assume any functional form for economic activities. To overcome such a difficulty, this study equips DEA environmental assessment with multiplier restriction by utilizing a unique feature on a proposed data treatment. The multiplier restriction in DEA has been never explored in previous works on environmental assessment. In an application, this study finds three important economic concerns on Europe and North America. First, Western Europe outperforms Eastern Europe and North America in their unified efficiency measures under managerial disposability. This study statistically confirms a difference between Western and Eastern Europe, but not between Western Europe and North America. This result exhibits that Eastern Europe is not yet well developed at the level of the other two regions. Second, Eastern Europe has exhibited MRT estimates that are different from Western Europe and North America. The nations in Eastern Europe have an economic potential for industrial developments because the level of their industrial pollutions is less than that of the other two regions. The potential is also found in their MRT estimates. Finally, an interesting difference can be found in the RS estimate between Eastern Europe and Western Europe from 2008 to 2012. They have statistically exhibited a difference between the two regimes, but not with North America. This is because most nations in both Western Europe and North America have already attained a high level of economic successes so that they have a limited industrial potential under current production technology and eco-technology. The situation of the two regions will be changed along with new technology development. In contrast, Eastern Europe is different from the other two regions in terms of attaining such a level of social sustainability because of limited capital accumulation and limited opportunity for technology innovation.     

Energy efficiency,CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis

This paper proposes a meta-frontier non-radial directional distance function to model energy and CO₂ emission performance in electricity generation. This approach allows for the consideration of the group heterogeneity of electricity generation, non-radial slacks, and undesirable outputs simultaneously. We extend several standardized indices to measure total-factor energy efficiency, CO₂ emission performance, and technology gaps in electricity generation. We estimate the potential reductions in energy use and CO₂ emissions under different technology assumptions. We conduct an empirical analysis of fossil fuel electricity generation in Korea by using the proposed approach. The results indicate that coal-fired power plants show higher levels of total-factor energy efficiency and CO₂ emission performance than oil-fired ones. Under the meta-frontier technology assumption, coal-fired power plants show a smaller technology gap than oil-fired ones. This suggests that the Korean government should promote technological innovation to reduce technology gaps for oil-fired plants, thereby improving energy and CO₂ emission performance and meeting emission reduction targets in the electricity generation industry.     

The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach

Shadow prices are widely employed in guiding environmental policies. This paper contributes to the literature by developing a novel partial frontier approach for estimating shadow prices. The proposed method is advanced in handling outliers, and provides a precise estimation of the marginal rate of substitution along the production frontier. To cope with the different disposability characteristics of undesirable emissions, SO₂ is treated as an environmental input that is strongly disposable. Because most different undesirable outputs are jointly reduced, this study is the first to use directional derivatives instead of partial derivatives and proposes a new separation method that separates individual directional shadow price from the cost of joint reduction of multiple undesirable outputs. We apply the proposed method to a sample of 93 coal-fired power plants covering six years. The estimated average shadow prices of CO₂ and SO₂ are 69 $/tonne and 2525 $/tonne under the newly developed partial frontiers. When assuming some undesirable output to be strongly disposable, both shadow prices fall (20.32 $/tonne and 1018.23 $/tonne). The present paper suggests the estimated shadow prices will be much different across different levels of disposability. The cost of joint reduction is calculated as 91.05 $/unit given the current production level, which leads to a directional shadow price for the two undesirable outputs of 91.32 $/tonne and 1250.06 $/tonne. The estimated shadow prices for both undesirable outputs dispersed widely under the partial frontiers. Spatial distribution of estimated shadow prices shows that coastal provinces and municipalities have higher CO₂ shadow prices but lower SO₂ shadow prices, whereas the northeast provinces are the opposite. The CO₂ shadow price is comparatively stable over the study period while the SO₂ shadow price fluctuates. Policy implications are discussed.     

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.