Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach

This paper contributes to the existing literature on the methodology of modeling the dynamic of carbon emission performance. Based on the analytical framework of Zhou et al. (Energy Economics, 32, 194–201, 2010), we develop a parametric Malmquist index approach that takes into account statistical noises. Moreover, the fixed-effect panel stochastic frontier model is employed to deal with regional heterogeneity. The proposed approach is applied to analyze the dynamics of carbon emission performance in 30 Chinese provinces during the period of 2000–2010. The main findings are as follows. First, the carbon emission performances of 30 provinces as a whole improved by 4.1% annually during the sample period, which was mainly driven by efficiency change component. Second, the east area shows the best performance with an average Malmquist CO₂ emissions performance index (MCPI) of 1.108, followed by the central area (1.039). Unlike the east and central areas, the west area experienced deterioration in carbon emission performance. More effective environmental policies should be implemented to change the situation. Third, compared with the proposed approach, the nonparametric approach tends to underestimate China's MCPI and gives rise to volatile results.     

Energy efficiency evaluation for regions in China: an application of DEA and Malmquist indices

With the development of economy, the impression of energy and environment is increasing, and improving energy efficiency plays a vital role in the sustainable economic development in China. An application of data envelopment analysis (DEA) and Malmquist indices has been used in this paper to investigate energy utilization efficiency of 30 provinces, autonomous regions, and municipalities (apart from Hong Kong, Macau, Taiwan, and Tibet) in China. The results show that industries in the eastern area have the best average energy efficiency for the period 2006–2009, followed by the central area. The industrial energy overall technical efficiency, industrial energy pure technical efficiency, industrial energy scale efficiency, etc. in 30 different regions of China are examined. By the comparative analysis of energy efficiency, the results show that the energy efficiency of Beijing, Shanghai, Jiangsu, Zhejiang, Guangdong, and Hainan provinces is effective, and the lowest six regions of energy efficiency are Ningxia, Inner Mongolia, Shaanxi, Liaoning, Chongqing, and Jilin, whose energy efficiency is in the level of 0.5 or so. The results mean that the eastern regions are better than the central and western regions according to energy efficiency.     

Energy efficiency and appliance purchases in Europe: Consumer profiles and choice determinants

This study seeks to the following: (1) understand the factors/characteristics typically considered when purchasing electrical appliances, (2) analyse the differences between consumer profiles regarding these and (3) understand the factors driving the consideration of energy efficiency class by purchasers. Results indicate a preference for first considering cost, followed by quality and energy consumption considerations. These are correlated positively with the consideration of energy efficiency class in consumer choices. Also, regression analysis shows environmental attitudes to be negative predictors of energy efficiency class consideration, while specific environmental behaviours were positive predictors. Finally, consumer profiles were identified based on gender, age and whether or not the purchaser was accompanied when decisions were made. Implications for retail employee training and the development of persuasive messages for consumers based on established profiles are discussed.     

The determinants of cost efficiency of hydroelectric generating plants: A random frontier approach

This paper analyses the technical efficiency in the hydroelectric generating plants of a main Portuguese electricity enterprise EDP (Electricity of Portugal) between 1994 and 2004, investigating the role played by increase in competition and regulation. A random cost frontier method is adopted. A translog frontier model is used and the maximum likelihood estimation technique is employed to estimate the empirical model. We estimate the efficiency scores and decompose the exogenous variables into homogeneous and heterogeneous. It is concluded that production and capacity are heterogeneous, signifying that the hydroelectric generating plants are very distinct and therefore any energy policy should take into account this heterogeneity. It is also concluded that competition, rather than regulation, plays the key role in increasing hydroelectric plant efficiency.     

DEA window analysis and Malmquist index to assess energy efficiency and productivity in Jordanian industrial sector

This research evaluates the energy efficiency and productivity growth in the industrial sector over the period of 1999 till 2013 using data envelopment analysis (DEA). Two cases are analyzed; in the first case (GVA), the output is the gross value added, whereas two outputs are considered in the second case (GCO), CO₂ emission and GVA. Five key input factors are considered in both cases. From DEA window analysis, the technical inefficiency (TIE) values are zeros in windows (2001–2005) till (2003–2007), (2007–2011), and (2008–2012), whereas the pure technical inefficiency (PTIE) values are zeros in windows (1999–2003) till (2003–2007). Finally, the scale inefficiency (SIE) values are zeros in windows (2001–2005) till (2003–2007). These results help policy planners on how to better utilize resources and management efficiency over time and guide operational managers when to increase or decrease the scale. Moreover, the averages of inefficiency values in the GVA case are smaller than their corresponding in the GCO case, which indicates the negative effect of CO₂ emission on efficiency. Further, Malmquist index is estimated for three 5-year energy plans. The productivity index is found less than one for the third plan (2009–2013), which indicates a decrease productivity growth. In conclusions, research results provide valuable support when assessing the progress of energy efficiency and productivity in industrial 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.     

Energy and GHG emission efficiency in the Chilean manufacturing industry: Sectoral and regional analysis by DEA and Malmquist indexes

Global warming produced mainly by the emission of greenhouse gases is currently a worldwide concern. In the last few decades since the 1950s many of the changes observed in the world climate have been meaningful. This paper presents an analysis of energy efficiency and of greenhouse gas emissions in the Chilean manufacturing industry by region and sector taking into consideration time sequences. Data Envelopment Analysis (DEA) models are used for the analysis. Three ways to handle undesirable outputs are compared, the source of inefficiency in each decision making unit (DMU) is calculated using scale efficiency, and the evolution over time is analyzed using the Malmquist index. The results indicate that the industries located in the Chilean regions of Coquimbo, La Araucania and Aysen were the most efficient while the industries in the regions of Tarapaca, Antofagasta and Biobio were less efficient. The most efficient industrial sectors were those involving communications equipment, base metals, and clothing; the least efficient were those concerned with food and beverages, textiles and nonmetallic minerals. Due to the treatment of the undesirable outputs, differences were found in the efficiency indexes obtained by the three models. This finding suggests using a model better adapted to the characteristics of the outputs in question and the viability of improving industrial practices.     

Environmental efficiency evaluation for Xiangjiang River basin cities based on an improved SBM model and Global Malmquist index

During the past several decades, the economy of China has increased rapidly with a number of energy and environmental problems such as energy shortage, global warming and river pollution. Considering the typical economic development of Xiangjiang River basin at the cost of energy and environment, this paper measures the energy and environmental efficiency of the Xiangjaing River basin cities and takes the further analysis with the total factor productivity. In order to accurately measure the real impact of cities on rivers, we take the water quality of the upstream and downstream of cities as the environmental indicator. An improved slacks-based measure approach is utilized to evaluate the energy and environmental efficiency of 15 trunk streams and tributaries along the Xiangjiang River basin cities during 2008–2014. The empirical results show the efficiencies of trunk streams and tributaries areas were discrepant even in the same city, but their technical change in the same city had significant similarities during the same period.     

Malmquist index measurement for sustainability enhancement in Chinese municipalities and provinces

This study discusses a use of DEA environmental assessment in a time horizon. We use a radial approach to examine a dynamic change of index measures related to China's regional development and industrial pollution prevention. In applying the proposed assessment to a time-series data, we need to examine components that produce a shift of an efficiency frontier in a time horizon. A unique feature of the proposed assessment is that it incorporates a framework of Malmquist index to examine the frontier shift among multiple periods. Here, the frontier shift indicates a progress potential on technology development and/or managerial improvement among observed periods. Thus, it is not an efficiency measure. Rather, the measurement eliminates inefficiency by shifting an organization to an efficiency frontier. In this study, the index is conceptually separated into 6 subcomponents, which are further disaggregated into 12 different elements (6 subcomponents × 2 disposability concepts) under natural and managerial disposability concepts. The proposed index measurement needs to consider a possible occurrence of a frontier crossover among different periods because technology diffusion on production activities usually has a time lag until it becomes really effective. Methodologically, this study conveys the message that DEA is an approximation method, so being not perfect. Therefore, it is necessary for us to use several different approaches (e.g., potential improvement by measuring a frontier shift and efficiency analysis) to obtain reliable empirical evidence. As an application, this study examines the level of sustainability related to 30 municipalities and provinces in China from 2003 to 2014. The following six policy implications are obtained in this study. First, all municipalities and provinces have made a considerable progress on their economies and pollution prevention efforts. Second, the effect of the frontier crossover is limited in China because they attain a high level of their potentials on economic development and pollution prevention. Of course, this effort is within the Chinese boundary, not international, because this study does not compare them with other industrial nations. Third, China needs to allocate its resources to western provinces at a level that it has used for coastal developments. Fourth, the government should reinforce efforts on environmental protection in central and southern regions. Fifth, the government has focused on the sustainability development in urban municipalities and provinces and then has gradually shifted the policy influence toward rural areas. Finally, different empirical results are confirmed by the potential analysis which consists of the Malmquist index measurement and the efficiency analysis. Both approaches need to be examined for future planning on Chinese regional development.     

Energy investment and economic growth : A simplified approach

A model is developed to investigate the effect of energy investment on economic growth under a set of simplifying assumptions. The economy is treated as a two sector aggregate; the energy sector and the rest of the economy, whereas the model describing the energy-economy interaction is linear to the differential changes of the variables, adaptable to structural evolution and requires a modest amount of data for initialization. It can be used in a single stage or an iterative mode to produce outcomes for the short and medium run. The analysis reveals that energy productive investment has had an impact on the rate of formation of the non-energy capital stock and subsequently on economic growth. These effects appear amplified under a regime of increasing energy price.     

Energy efficiency,no: It's exergy efficiency!

Elevated energy efficiencies seem politically beyond dispute as measures against anthropogenic climate change. Energy efficiencies, however elevated they become, remain within the applied energy system, though. The paper draws attention to the exergo-thermodynamical system change of splitting up energy into exergy and anergy where exergy is the maximum of available technical work drawn from energy. Consequently, it is the elevated exergy efficiency, which deserves the attention of energy engineers helping to reduce greenhouse gas emissions. In this context, hydrogen energy is irreplaceable, hydrogen exergizes energy! It makes more technical work available (=exergy)$(=\mathrm{exergy})$, it avoids exergy destruction and the built-up of huge amounts of useless anergy.     

Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis

This paper proposes the metafrontier non-radial Malmquist CO₂ emission performance index (MNMCPI) for measuring dynamic changes in total-factor CO₂ emission performance over time. The MNMCPI method allows for the incorporation of group heterogeneity and non-radial slack into the previously introduced Malmquist CO₂ emission performance index (MCPI). We derive the MNMCPI by solving several non-radial data envelopment analysis (DEA) models. We decompose the MNMCPI into an efficiency change (EC) index, a best-practice gap change (BPC) index, and a technology gap change (TGC) index, and based on the proposed indices, we examine the dynamic changes in CO₂ emission performance and its decomposition of fossil fuel power plants in China for the 2005–2010 period. The empirical results show a 0.38% increase in total-factor CO₂ emission performance as a whole and a U-shaped MNMCPI curve for the sample period. Because companies owned by the central government lack innovation and technological leadership, the results suggest a missing link in the role of the central government in promoting CO₂ emission performance.     

CO2 emissions reduction of Chinese light manufacturing industries: A novel RAM-based global Malmquist–Luenberger productivity index

Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO₂ emissions reduction in China. In China industry contributes 84.2% of the total CO₂ emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO₂ emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist–Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO₂ emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed.     

Energy efficiency in New Zealand's residential sector: A systemic analysis

This paper examines the complexity arising from the multiple, time varying factors that impact energy efficiency in New Zealand's residential sector. Initial problem structuring involved the analysis of behaviour over time of main variables and incorporated stakeholder analysis using a systems approach. Further, a systems model of the problem situation was developed using a participative group model building process. The analysis of the model revealed a set of feedback loops operating in the system identified as responsible for the complexity of the problem situation relating to energy efficiency. The paper concludes by highlighting some of the main results relating to long-term structural changes suggested by the stakeholders involved in this study to change the behaviour of the system.     

Energy efficiency in Swedish industry: A firm-level data envelopment analysis

This paper assesses energy efficiency in Swedish industry. Using unique firm-level panel data covering the years 2001–2008, the efficiency estimates are obtained for firms in 14 industrial sectors by using data envelopment analysis (DEA). The analysis accounts for multi-output technologies where undesirable outputs are produced alongside with the desirable output. The results show that there was potential to improve energy efficiency in all the sectors and relatively large energy inefficiencies existed in small energy-use industries in the sample period. Also, we assess how the EU ETS, the carbon dioxide (CO₂) tax and the energy tax affect energy efficiency by conducting a second-stage regression analysis. To obtain consistent estimates for the regression model, we apply a modified, input-oriented version of the double bootstrap procedure of Simar and Wilson (2007). The results of the regression analysis reveal that the EU ETS and the CO₂ tax did not have significant influences on energy efficiency in the sample period. However, the energy tax had a positive relation with the energy efficiency.     

A combined sustainability index for electricity efficiency measures

One of the most substantial tools that serve decision makers in their efforts to reduce greenhouse gas emissions includes energy efficiency measures that in most cases benefit from governmental assistance for achieving electricity consumption reduction goals. This paper examines five energy efficiency measures, defining a combined sustainability index. A multi-criteria analysis of five predefined indices was developed (economic, environmental, technology, social and political), providing a combined index for each measure and a tool for identifying the preferred measure within a specific situation, based on its total sustainability score. In this research, a case study was conducted and the preferred measure was found to be municipal street lighting systems, based on its high political and social scores, and its relatively high installation potential. The second choice would be replacement of chillers in the industrial sector, and the least favorable measure is the replacement of water pumps in the water sector. The methodology described brings into account the technological specifications of the measure implemented, and the specific national conditions under which it is implemented.     

Technology gap and China's regional energy efficiency: A parametric metafrontier approach

This paper analyzes the energy efficiency of China's 30 administrative regions during the period from 1997 to 2010. Most existing studies ignored the variation of production technologies among regions in China. Taking this factor into account, we introduce a parametric metafrontier approach based on the Shephard energy distance function. For further analysis, regions in China are divided into three groups using cluster analysis. We find that the regions in group 1 (mainly the regions in the east area of China) not only have the highest energy efficiency score, but also take the lead in terms of technology gap ratio. Meanwhile, due to their backward technology levels, the average energy efficiency score of the regions in group 3 (mainly the regions in the west area of China) is particularly low. Moreover, the pooled estimation, which ignores the technology gap among the groups, tends to underestimate the energy efficiency.