Energy, Environment and Transitional Green Growth in China

The transitional growth experience China is undergoing, with its emphasis on reducing the energy intensity of the economy while maintaining satisfactory rates of economic growth, is one of the most important research topics concerned with the performance of China’s economy. The Nankai research group on efficiency and productivity, located in the College of Economic and Social Development at Nankai University, is one of the first research teams engaged in the study of the efficiency and green productivity growth of China’s economy. Since 2006 the Nankai research group, which includes scholars in industrial economics, regional economics and green logistics, has achieved fruitful research outcomes. A measurement framework for China’s green growth experience has been proposed, including an appropriate GDP growth rate and measures of energy saving, low pollution and low carbon emissions. Such green growth can be achieved through economic reform and innovation oriented to improve China’s efficiency and productivity, inclusive of its economic resources and its energy use and composition, and its conventional GDP and its emissions and other environmental impacts.

Problems such as climate change, environmental pollution and depletion of natural resources pave the way of sustainable development. Past two decades have seen the development of numerous indicators for sustainable development to support policy analysis and decision making. Recently, composite indicators have evolved as a popular analytical tool for sustainability assessment. The construction of composite sustainability indicators involves not only the determination of underlying indicators but also their weighting and aggregation. This chapter provides a systematic and up-to-date review of recent methodological developments in constructing composite sustainability indicators, which range from normalization methods to aggregation models. The pros and cons of each method/model have been discussed. Other fundamental aspects, e.g. the principles of selecting aggregation function and robustness analysis, are also discussed.

The generation of unintended residuals in the production of intended outputs is the key factor behind our serious problems with pollution. The way this joint production is modelled is therefore of crucial importance for our understanding and empirical efforts to modify economic activities in order to reduce harmful residuals. The materials balance tells us that residuals stem from the use of material inputs. The modelling of joint production must therefore reflect this. A multi-equation model building on the factorially determined multi-output model of classical production theory can theoretically satisfy the materials balance. Potentially complex technical relationships are simplified to express each of the intended outputs and the unintended residuals as functions of the same set of inputs. End-of-pipe abatement activity is introduced for a production unit. Introducing direct environmental regulation of the amount of pollutants generated, an optimal private solution based on profit maximisation is derived. Serious problems with the single-equation models that have dominated the literature studying efficiency of production of intended and unintended outputs the last decades are revealed. An important result is that a functional trade-off between desirable and undesirable outputs for given resources, as exhibited by single-equation models, is not compatible with the materials balance and efficiency requirements on production relations. Multi-equation models without this functional trade-off should therefore replace single equation models. Extending the chosen multi-equation model to allow for inefficiency, three efficiency measures are introduced: desirable output efficiency, residuals efficiency, and abatement efficiency. All measures can be estimated separately using the non-parametric DEA model.

A large number of studies on environmental productivity have appeared across various sub-disciplines of economics as well as in other related disciplines such as operations research and engineering. In these studies, the production units of interest are usually plants or firms, sectors or industries, regions, and countries. To our knowledge, however, only one previous study considers environmental performance of consumer durables. This is somewhat surprising because, during their use phase, consumer durables such as passenger cars and home appliances are in fact production units that consume energy and resources to provide services for consumers, and hence are also contributors to various environmental pollutants. This chapter aims to develop an environmental productivity index specially designed for consumer durables. To this end, we first analyze the particular features of consumer durables compared to conventional production units. Based on these features, we elaborate how to model the production activity during the use phase of consumer durables; and then we present an overview of the existing approaches to measuring environmental productivity change and describe how they can be applied in the current context. Finally, we use a unique Finnish data set of passenger cars to illustrate the interpretation of the proposed index.

The paper is an attempt to explain the reasons for the power shortages that occurred in the 2000s in China. Firstly, by examining the relationship between power demand and installed capacity, the study excludes the possibility of underinvestment. Secondly, performance evaluation shows that the average efficiency values are 85% from Data Envelopment Analysis (DEA) and 73% from Stochastic Frontier Analysis (SFA), with Total Factor Productivity (TFP) increased by 2.23% (DEA) or 0.97% (SFA) annually. Taking the estimated results of efficiency levels as well as TFP change into consideration, it is difficult to reach the conclusion that low performance is the major cause of power shortage. Finally, by resorting to business leaders and existing literature, we find that in order to reduce operation losses due to the mismatch between high market-oriented coal price and low government-guided electric price, thermal power had to reduce the need for coal by artificially lowering the utilisation rate despite urgent power demands from the market, which eventually leads to the phenomenon of power supply shortage.

The Chinese central government has adopted a nationwide administrative allocation policy to reduce carbon and sulfur emissions. Using the ZSG-DEA (Zero-Sum Gain Data Envelopment Analysis) approach, this paper evaluates and compares the emission efficiencies of China’s provincial CO₂ and SO₂, and provides a reallocation scheme. The results show that the administrative allocation leads to an increasing gap of provincial emissions-reduction ability; provinces with higher efficiencies have difficulty achieving their administrative targets, whereas provinces with lower efficiencies can more easily achieve their targets. Additionally, the administrative allocation scheme ignores the difference in efficiencies, whereas the ZSG allocation scheme of this paper emphasizes the Pareto optimality of economic, environmental, and energy factors while comprehensively considering fairness and efficiency.

In China’s electricity generation process, fighting against the rising CO₂ emissions becomes increasingly an urgent and great challenge. Based on an endogenously non-parametric directional distance function (DDF), this paper investigates the carbon productivity changes (i.e., pure efficiency change, scale efficiency change and best practice gap change) and shadow prices of CO₂ emissions in the electric power industry sector of China’s 30 provinces from 2011 to 2015. The main findings of carbon productivity evaluation include: (i) only China’s western area experiences carbon productivity growth during the entire study period; (ii) the primary driving force for carbon productivity increase can be attributed to technical progress both among areas and among regions, while the lack of catch-up effect drags carbon productivity growth. Moreover, the main findings of shadow prices estimation include: (i) in general, the CO₂ emissions abatement cost of China’s power industry sector increases during the 12th Five Year Plan period (2011–2015) with a range of 494–965 yuan/ton of CO₂; (ii) although the beta convergence shows the negative correlation between initial shadow price and its growth rate, there is significant shadow prices heterogeneity among areas and regions, which provides a necessity and possibility in emission abatement cost savings through the regional carbon emissions trading in power industry sector of China.

This research introduces the context-dependent total-factor energy efficiency (CD-TFEE) and applies it to find the frontier levels of China’s regions in 2014. In this empirical example, CD-TFEE generates different results from the context-dependent data envelopment analysis (CD-DEA) proposed by Seiford and Zhu (Omega, 31(5):397–408, 2003). China’s regions in 2014 can be categorized into five levels of TFEE frontiers, and almost two-thirds of Chinese regions can target the domestic benchmarks to improve their energy efficiency.

In the past several years, the Chinese government has been pursuing “green” economic growth. This is an issue of policy making because undesirable outputs (e.g., pollution) are unavoidable during the production process. The existence of undesirable outputs complicates the analysis of firms’ behavior. This paper adopts Kuosmanen’s (2005) production frontier to study whether the government’s policy objective has been realized in the past decade. Incorporating both desirable and undesirable outputs in the study of 294 cities from 2003 to 2014 in China, the “true” picture of the productive performance of these cities is uncovered. First, the manufacturing sector was highly environmental inefficient in 2003. It became more environmentally friendly over time but was stagnant after 2010. In contrast, the sector was also very technically inefficient in the production of desirable goods but was improving over the whole studied period. Second, the gap between environmentally friendly and unfriendly cities, in desirable and undesirable goods, has been narrowing over time. Third, eastern provinces were more environmentally friendly and western provinces were lagging behind during 2003–2014. The western provinces were outperformed by other provinces over time. In conclusion, although the Chinese government has done much to improve environmental protection, our results show that more has to be done.

The purpose of the paper is to measure the simultaneous efficiencies of environmental and fossil fuel using the stochastic frontier cost function for OECD countries. As the stochastic frontier cost function is to minimize the cost, we use it to minimize pollutant. The empirical test reports that the change of fossil fuel is more sensitive than that of income in terms of the effect of CO₂ emission. The annual average efficiency of fossil fuel in OECD for 1996–2009 is 0.825, while the annual average efficiency of CO₂ is 0.750, in which the possibility of reducing the emission of CO₂ is higher than that of fossil fuel. The empirical test indicates that improving the efficiency of fossil fuel makes environmental efficiencies higher.

The greenhouse effect has caused a deterioration of the ecological environment and global climate change, and therefore investigating new green energy performances has become an important issue of the 21st century in order to establish the causal relationship. This study utilizes the meta-frontier dynamic SBM-DEA model to analyze the technology gap ratio and to evaluate the energy efficiency and energy performance in the Organization for Economic Co-operation and Development (OECD). The findings show that the efficiencies of renewable energy are different by geography and culture for the 34 countries of OECD in the period 2008–2012. Meta-frontier efficiency (MFE) presents significant differences among the top 10 countries and bottom 10 countries when examining renewable energy performance; the top 10 countries are Canada, United States, Norway, Japan, France, Germany, Sweden, Spain, Italy, and Austria. Countries with better overall values of energy environmental efficiency are Britain, Netherlands, Belgium, Ireland, Luxembourg, Estonia, and Iceland, while the relatively poor countries are Greece, Sweden, Slovenia, Turkey, and Poland. This study finds that South-Eastern Europe has relatively poor overall performance and technology efficiency, due to historical, scientific, technical, and economic factors, whereas North Western Europe (NWE) is better than South Eastern Europe (SEE) in overall performance and technology efficiency. The Americas region exhibits larger energy consumption, and so its technical gap ratio is higher than the averages of the other groups, and it has the best overall performance.

This paper constructs the influencing factors system of industrial technological progress bias in China using the mediating effect model, through introducing the two indexes of factor price distortion and technological innovation pattern. The result shows that at present, the direction of technological progress of China’s industry is capital biased, which will adversely affect the income distribution and industrial upgrading. In recent years, the factor price of China’s industry has a negative distortion, and the degree of distortion has not been effectively curbed. Technological progress bias and the distortion degree of factor price are both affected by industry factor intensity. The distortion of factor price leads to the bias of technological progress towards the capital through direct or indirect effects, in which the mediating effect of technology innovation accounts for 23% of the total effect. The introduction of technology innovation mode will increase the capital biased technological progress. Therefore, it is necessary to actively promote the reform of marketization of factors and enhance the ability of independent innovation to optimize the direction of China’s industrial technological progress.

Focusing on the perspective of environmental innovation, this paper first chooses a panel dataset of China’s 30 provinces during 2000–2012 to calculate indicators of environmental R&D and traditional R&D. Furthermore, we examine the relationship between environmental innovation and green transformation of Chinese economic growth pattern by employing the system GMM approach, and conduct a comparative analysis with traditional innovation. The empirical results show that environmental innovation is an essential impetus to promote economic green transformation, but traditional innovation impedes the process of green transformation. The possible reason is that traditional innovation mainly aims at expanding the scale of production and leads to great amount of energy consumption and serious environmental damage. While environmental innovation is able to achieve cleaner production and enhanced productivity simultaneously and eventually to promote economy to transform to the clean and high-end field. Finally, we derive our conclusions and draw some policy implications.

The United Nations Commission on Sustainable Development argues that the full picture of sustainable development should consist of four dimensions: economic, environmental, social, and institutional. Since regions within a country should set up a similar institutional framework, this study analyzes China’s regional sustainable development from the perspectives of economic, environmental, and social dimensions. Based on the dataset obtained from China Statistics Yearbook and consisting of 30 regions of China for the period 2006–2009, the empirical results show that the optimal values for the origins of FDI are different in the various regions of China as well as optimal energy consumptions. Other findings note that: (1) the eastern region should only target FDI from non-overseas Chinese regions; (2) the middle region is the appropriate place to invest capital from overseas Chinese regions; and (3) China should diminish energy consumption countrywide, especially in the eastern and middle regions.

Exports contribute significantly to both income creation and pollution generation in China. Using a global input-output model, this paper examines domestic value-added and 8 types of air pollutant emissions generated by export production in China during the period of 1995–2009. The results show that both value-added and emissions created by exports of China increased significantly in the study period. In 2009, the share of value-added exports in Chinese GDP accounted for 32.3%. Meanwhile, emissions embodied in exports accounted 22–35% of total production emissions in China for 8 types of air pollutants. Although pollution intensities of value-added exports (the ratio of emissions to value-added created in the production of exports) in China were continuously declining for all pollutants in the study period, they were much greater than those of other major exporting countries. Based on a structural decomposition analysis, we find that the gaps in pollution intensities of value-added exports between China and other major exporting countries mainly result from differences in direct emissions intensity and input structure of production, whereas differences in export structure generally reduces the gaps in pollution intensities of value-added exports.