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.     

Eco-efficiency of the world cement industry: A data envelopment analysis

Chemical reactions and the combustion of dirty fuels, such as coal and petroleum coke (petcoke), that are used in cement production processes generate a significant amount of CO₂ emissions. In this paper, we provide an eco-efficiency measure for 21 prototypes of cement industries operating in many countries by applying both a data envelopment analysis (DEA) and a directional distance function approach, which are particularly suitable for models where several production inputs and desirable and undesirable outputs are taken into account. To understand whether this eco-efficiency is due to a rational utilization of inputs or to a real carbon dioxide reduction as a consequence of environmental regulation, we analyze the cases where CO₂ emissions can either be considered as an input or as an undesirable output. Empirical results show that countries where cement industries invest in technologically advanced kilns and adopt alternative fuels and raw materials in their production processes are eco-efficient. This gives a comparative advantage to emerging countries, such as India and China, which are incentivized to modernize their production processes.     

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.     

Energy efficiency measurement of Chinese Yangtze River Delta’s cities transportation: a DEA window analysis approach

In this paper, the transportation energy efficiency of Yangtze River Delta’s 15 cities is studied in the period from 2009 to 2013. To measure transportation’s dynamic performance, the window analysis of data envelopment analysis (DEA) is used to estimate the efficiency in cross-sectional and time-varying data. Capital inputs and labor inputs are selected as the two non-energy inputs, energy consumption as the energy input, passenger volume and freight volume are selected as the two desirable outputs, and carbon dioxide is chosen as the undesirable output. The empirical study shows that Shanghai had the highest transportation energy efficiency, followed by Zhejiang province, and the average efficiency of Jiangsu province was the worst. A regression analysis on the efficiency values and their three influencing factors was carried out. The results show that per capita gross domestic product and the per capita area of paved roads in a city negatively influenced the efficiency values, while the number of public transportation vehicles per 10,000 persons positively influenced the transportation efficiency values. Lastly, some policy recommendations, conclusions, and suggestions for further research are given.     

Do undesirable output and environmental regulation matter in energy efficiency analysis? Evidence from Indian Cement Industry

Energy use in the production of desirable output often results in the generation of undesirable emission with detrimental impact on the environment, and whose disposal is frequently monitored by public authorities. Previous studies, however, paid little attention to undesirable output and environmental regulation related to its disposal while estimating energy use efficiency. Analysis of energy efficiency ignoring undesirable output could result in biased estimates of efficiency. Thus the aim of this paper is to estimate energy use efficiency in the presence of energy related undesirable emission by taking Indian cement industry as a suitable context of my analysis. Depending on the presence and absence of undesirable output and environmental regulation, three measures of efficiency have been estimated at the state level from 2000–01 to 2004–05 by applying Data Envelopment Analysis. Energy efficiency is defined as the ability of the producer to reduce the energy input to the largest extent possible, conditional on the given level of output and non-energy inputs. Empirical results reveal that energy efficiency estimates are biased if only desirable output is considered. Results also demonstrate that environmental regulation has a reinforcing effect on energy use efficiency.     

Decomposing energy productivity change: A distance function approach

By using output distance functions, this paper decomposes energy productivity change into several components: effects of the changes in the ratios of non-energy inputs to energy, energy supply composition, and output composition; technical efficiency change; technological change. We apply this method to decompose energy productivity change in 23 OECD countries between 1980 and 1990. Results show that technological change is the most important source; increase in capital–energy ratio and the growing importance within total energy supply of electricity also contribute to it.     

Multi-regional input–output model and ecological network analysis for regional embodied energy accounting in China

Chinese regions frequently exchange materials, but regional differences in economic development create unbalanced flows of these resources. In this study, we examined energy by assessing embodied energy consumption to describe the energy-flow structure in China's seven regions. Based on multi-regional monetary input–output tables and energy statistical yearbooks for Chinese provinces in 2002 and 2007, we accounted for both direct and indirect energy consumption, respectively, and the integral input and output of the provinces. Most integral inputs of energy flowed from north to south or from east to west, whereas integral output flows were mainly from northeast to southwest. This differed from the direct flows, which were predominantly from north to south and west to east. This demonstrates the importance of calculating both direct and indirect energy flows. Analysis of the distance and direction traveled by the energy consumption centers of gravity showed that the centers for embodied energy consumption and inputs moved southeast because of the movements of the centers of the Eastern region. However, the center for outputs moved northeast because the movement of the Central region. These analyses provide a basis for identifying how regional economic development policies influence the embodied energy consumption and its flows among regions.     

Applying bottom-up analysis to identify the system boundaries of non-energy use data in international energy statistics

Data on the non-energy use of fossil fuels in energy statistics are subject to major uncertainties. We apply a simple bottom-up methodology to recalculate non-energy use for the entire world and for the 50 countries with the highest consumption of fossil fuels for non-energy purposes. We quantify worldwide non-energy use in the year 2000 to be 24±2 exajoules (EJ), thereby accounting for 6% of the global total primary energy supply (TPES). Our bottom-up estimates are in line with data from international energy statistics for the entire world and for 14 individual countries. Our estimates exceed official non-energy use data for 22 countries, whereas they are lower than official data in the case of 14 countries. Inconsistent system boundaries of non-energy use data in international energy statistics can explain parts of the observed deviations. We regard our bottom-up methodology as reliable albeit being attached with uncertainties. We recommend its use for energy statisticians and greenhouse gas (GHG) inventory makers to generate a shortlist of countries, for which efforts should be made to clarify and improve the quality of non-energy use data in national and international energy statistics.     

Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector

In this paper, we analyze the technical efficiency and CO₂ reduction potentials of German power and heat plants, using a non-parametric sequential Data Envelopment Analysis. We apply a metafrontier framework to evaluate plant-level efficiency in the transformation of inputs into desirable (energy) and undesirable (CO₂ emissions) outputs, taking into account different fossil fuel generation technologies. We use a unique data set of coal-, lignite-, gas- and biomass-fired power plants from 2003 through 2010 that provides an unbalanced panel of 1459 observations; the results are also checked against a balanced panel with a smaller number of observations. Although we find intra-group differences within energy generation technology, natural gas fired power plants clearly have the highest efficiency. Furthermore, the analysis points to significant savings potentials for CO₂ and fuel-input, and derives policy conclusions for the ongoing electricity sector reformation.     

Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs

This paper presents an efficiency assessment of selected OECD countries using a Slacks Based Model with undesirable or bad outputs (SBM-Undesirable). In this research, SBM-Undesirable is used first in a two-stage approach to assess the relative efficiency of OECD countries using the most frequent indicators adopted by the literature on energy efficiency. Besides, in the second stage, GLMM–MCMC methods are combined with SBM-Undesirable results as part of an attempt to produce a model for energy performance with effective predictive ability. The results reveal different impacts of contextual variables, such as economic blocks and capital–labor ratio, on energy efficiency levels.     

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.     

The threshold effects of energy efficiency on the elasticity of substitution between energy and non-energy factors

Considerable efforts have been made to estimate the relationship between energy and non-energy inputs in the production process. However, it remains controversial whether energy and non-energy inputs are complements or substitutes. Empirical analysis is conflicting on this issue. This study seeks to explore an alternative way to explain these conflicting results by examining the issue from the perspective of energy efficiency. This study is based on time series data for capital, labor, and energy from 28 Chinese provinces, covering 1985 to 2012. The results show that capital and energy are substitutes in all of the provinces, whereas labor and energy are complements in most of the provinces. Using the threshold effect model, we discover evidence of a threshold point based on the amount of energy efficiency activity in a province. This point separates the substitution behavior of provinces between energy and non-energy inputs. Low-energy efficiency provinces do not substitute as readily as high-energy efficiency provinces. The findings imply that the energy-saving technologies should be applied in provinces with comparatively higher energy intensity because they have more energy conservation potential.     

Energy consumption,energy R&D and real GDP in OECD countries with and without oil reserves

The objective of the study is to shed light on the contributions of energy consumption and energy R&D on economic growth. We examine two sets of causal relationship between (1) capital stock, energy consumption and real GDP and (2) capital stock, energy R&D and real GDP using panel-based fully-modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) for 20 OECD countries over the period of 1980–2010. Since different countries may respond differently to energy consumption and energy R&D, the sample is further divided into two groups: OECD countries with oil reserves and without oil reserves. Similarly, energy consumption and energy R&D are also further divided into fossil fuel energy and renewable energy. The results show that the role of energy R&D should not be overlooked and fossil fuel R&D is found to drive economic growth more than fossil fuel consumption. The findings also show that while capital stock and fossil fuels are the key factors driving economic growth, renewable energy promotes real output, specifically in the countries without oil reserves.     

Estimates of energy and non-energy elasticities in selected Asian manufacturing sectors: Policy implications

This paper presents the results of a study of the demand elasticities for energy and non-energy inputs in the food processing and textile industries in Bangladesh, the Philippines and Thailand. Estimates of substitution elasticities in production were derived by fitting data to a translog cost function for the period 1970–1980 for Bangladesh, 1970–1978 for the Philippines, and 1974–1977 for Thailand. The results varied according to the industries studied and across countries. They were compared with those of several developing and industrialized countries, and substitutability among inputs was found to be greater in the manufacturing sector of the developing countries studies than in those of industrialized countries. The generally high elasticities between labour and energy have implications for relative input pricing and use in developing countries.     

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.     

Energy returns in agriculture,with specific reference to developing countries

Quantitative data are presented for energy inputs and outputs for selected crops in India using either bullock-operated or tractor-operated farms. It is shown that large ratios are obtained for the energ outputs divided by the energy inputs. Preferred allocation of energy resources to the agricultural sector i recommended.     

Efficiency analysis of Chinese industry: A directional distance function approach

Two efficiency measures of Chinese industry were estimated at the provincial level from 1994 to 2002, using a directional output distance function. One is a traditional efficiency measure that considers only desirable output, while the other considers both desirable and undesirable outputs simultaneously. A comparison of the two measures revealed that efficiency levels are biased only if desirable output is considered. Five coastal provinces/municipalities that have attracted a large amount of foreign direct investment are found to be the most efficient when only desirable output is considered, and also when both desirable and undesirable outputs are considered. However, omitting undesirable output tends to lead to an overestimate of industrial efficiency levels in Shandong, Sichuan, and Hebei provinces. We also found that a province's industrial structure has significant effects on its efficiency levels.     

Energy efficiency developments in the Dutch energy-intensive manufacturing industry, 1980–2003

We studied energy efficiency trends in the Dutch manufacturing industry between 1995 and 2003 using indicators based on publicly available physical production and specific energy consumption data. We estimated annual primary energy efficiency improvements in this period at 1.3% on average, with the individual sub-sectors ranging between −0.1% and 1.5%. Energy efficiency developments with respect to electricity, fuels/heat and non-energy use have been monitored separately and are shown to differ significantly (for the sum of the sectors studied: 1.9% for electricity, 2.6% for fuels/heat and −0.1% for non-energy use). We combined our results with those from a previous, similar study for 1980–1995 and show that over the full time period, efficiency improvements of 1% per year have been achieved on average. Based on comparison with other sources and a detailed uncertainty analysis, we conclude that we developed a reliable top-down monitoring framework for studying energy efficiency trends of the manufacturing industry that can also be applied in other countries where similar data are available. We also showed that substantial differences exist between energy consumption data available from energy statistics and according to the Long Term Agreement monitoring reports, stressing the need for ongoing independent checks of available energy consumption data to avoid problems in future evaluations of energy efficiency policies.     

The non-energy intensive manufacturing sector.: An energy analysis relating to the Netherlands

This paper focuses on an area that has been neglected in energy analysis: the non-energy intensive industries. Using data at the 3-digit level for the Dutch manufacturing industry, we analyzed the performance of the sector with respect to its energy intensity, value added, value of production and energy costs. We found that energy consumption has increased by 30% between 1988 and 1999 while there has not been a decrease on energy intensity. A decomposition analysis was performed in order to separate structural, production and intensity effects. We found that structural changes played a minor role and that in fact, intensity effects added further energy requirements to those induced by output growth. The results of our study highlight the need for policy-makers and scientists to increase their attention to the non-energy intensive sector and encourage industries in these sectors to adopt energy-efficient technologies and management practices.     

CO2 emissions,energy consumption and economic growth in BRIC countries

This paper examines dynamic causal relationships between pollutant emissions, energy consumption and output for a panel of BRIC countries over the period 1971–2005, except for Russia (1990–2005). In long-run equilibrium energy consumption has a positive and statistically significant impact on emissions, while real output exhibits the inverted U-shape pattern associated with the Environmental Kuznets Curve (EKC) hypothesis with the threshold income of 5.393 (in logarithms). In the short term, changes in emissions are driven mostly by the error correction term and short term energy consumption shocks, as opposed to short term output shocks for each country. Short-term deviations from the long term equilibrium take from 0.770 years (Russia) to 5.848 years (Brazil) to correct. The panel causality results indicate there are energy consumption–emissions bidirectional strong causality and energy consumption–output bidirectional long-run causality, along with unidirectional both strong and short-run causalities from emissions and energy consumption, respectively, to output. Overall, in order to reduce emissions and not to adversely affect economic growth, increasing both energy supply investment and energy efficiency, and stepping up energy conservation policies to reduce unnecessary wastage of energy can be initiated for energy-dependent BRIC countries.