Elsevier

Applied Energy

Volume 112, December 2013, Pages 1403-1415
Applied Energy

China’s regional energy and environmental efficiency: A Range-Adjusted Measure based analysis

https://doi.org/10.1016/j.apenergy.2013.04.021Get rights and content

Highlights

  • We measured China’s regional integrated energy and environmental efficiency using RAM-DEA approach.

  • The concepts of natural and managerial disposability are incorporated in evaluation.

  • The types of returns and damages to scale of different Chinese regions are identified.

  • China’s production efficiency slightly decreased and its emission efficiency slightly increased during 2006–2010.

  • Most Chinese regions are recommended to rely on technology innovation for further integrated efficiency improvement.

Abstract

Energy and environmental efficiency evaluation has recently attracted increasing interest in China. In this study, we utilize the Range-Adjusted Measure (RAM) based nonparametric approach to evaluate the regional energy and environmental efficiency of China over the period of 2006–2010. The desirable/good and undesirable/bad outputs, as well as the energy and non-energy inputs are considered in the efficiency evaluation so as to characterize the energy consumption, economic production, and CO2 emission process of different China’s regions. In addition, the economic concepts of natural disposability and managerial disposability are incorporated in the evaluation instead of the strong and weak disposability in conventional environmental efficiency evaluation. Therefore, the types of returns to scale and damages to scale of different China’s regions are measured and correspondingly the strategy and policy implications are proposed for guiding the future improvement of regional energy and environmental efficiency. This study finds that: (i) Beijing, Shanghai, and Guangdong had the highest integrated energy and environmental efficiency during the study period, which could be seen as the benchmarks of inefficient China’s regions. (ii) On average, east China had the highest integrated efficiency under natural disposability, and west China had the highest integrated efficiency under managerial disposability. (iii) During 2006–2010, the average production efficiency of China slightly decreased and the average emission efficiency of China slightly increased. (iv) Among China’s 30 regions, 19 regions exhibited decreasing returns to scale, 4 regions shown increasing returns to scale, and 7 regions have mixed returns to scale types under natural disposability in our study period. In addition, under managerial disposability, there are 18, 3 and 9 regions respectively exhibited increasing, decreasing and mixed damages to scale types over time. (v) For most Chinese regions, it is not recommended to simply increase or maintain their current scales of production, but alternatively, they should pay more attentions on technology innovation of energy utilization efficiency improvement, since up to 2010, China still had large energy conservation and emission reduction potentials.

Introduction

In recent years, energy performance and environmental performance evaluation issues has attracted increasing interest since they are considered a crucial approach to save energy, reduce greenhouse gas emissions, protect environment and mitigate global climate change. Despite the major energy performance improvements achieved by China during the last two decades, the rapid development of economy has substantially increased China’s primary energy consumption and leaded to serious environmental problems due to the yearly increasing emissions of CO2 and other pollutants [1]. In addition, since different regions of China have different energy consumption structures, different economic growth modes, and different energy saving and environment protection policies, the regional energy and environmental performance of China may vary significantly across different regions. Hence, it is meaningful to evaluate China’s regional energy and environmental efficiency, which can assist the energy and environmental policy making for Chinese government both at the national and regional levels.

The evaluation of energy and environmental performance is often in the form of energy or environmental efficiency indices which can be constructed through mathematics programming methods such as conventional data envelopment analysis (DEA) models [2], [3], non-radial DEA models [4], Range-Adjusted Measure based DEA (RAM-DEA) models [5], and directional distance function (DDF) models [6], [7].

At the macro-economy level, DEA approach has recently been widely applied to studying the energy and environmental efficiency for it provides an appropriate method to deal with multiple inputs and outputs in examining relative efficiency [3]. For instance, Hu and Wang [8] proposed a total-factor energy efficiency evaluation DEA model and measured the energy efficiency of 29 regions in China. Zhou et al. [9] developed several environmental DEA technologies and measured the carbon emission efficiency of eight world regions. Yeh et al. [10] calculated the technical efficiency of energy utilization in Chinese mainland and Taiwan by using the traditional BCC model [11]. Wang et al. [12] developed a mixed energy economic-environmental efficiency model to measure the environmental efficiency, economic efficiency, and economic-environmental efficiency of 28 provinces in China for the period of 2001–2007. Bian and Yang [13] proposed several DEA models to simultaneously measure resource and environmental efficiency and applied their models in efficiency evaluation of 30 Chinese provinces. Shi et al. [14] presented three extended DEA model to calculate the energy and environmental overall technical efficiency, pure technical efficiency, and scale efficiency of 28 administrative regions in China. Wang et al. [4] established several DEA window analysis models to measure the energy and environmental efficiency of 29 administrative regions of China using cross-sectional and time-varying data and proposed a dynamic evaluation result.

Since Färe and Grosskopf [15] and Zhou and Ang [16] incorporated undesirable outputs in measuring efficiency, many researchers have considered undesirable outputs in energy efficiency evaluation. Here, we point out that most of the previous researches are built upon the concept of weak and strong disposability in environmental performance evaluation [17]. If we consider X as an input vector and G as a desirable output vector, then, production technology can be considered as P: X  P(X), where the set P(X) denotes that the output vector G is producible by the input vector X. The weak disposability on G can be specified by G  P(X)  θG  P(X) for all 0  θ  1, and the strong disposability on G can be specified by GGP(X)GP(X). However, this concept, associated with radial DEA model, is not sufficient, since the weak disposability assumes that all the decision making units (DMUs) yield a unified abatement on input factors for using only one efficiency score [18]. In addition, the previous researches never measured the returns to scale and damages to scale under the energy and environmental efficiency evaluation framework. Therefore, in this study, following Sueyoshi and Goto [19], [20], [21], we evaluate the regional energy and environmental efficiency of China by applying Range-Adjusted Measure based DEA models. The RAM-DEA models are non-radial models and they measure the energy and environmental efficiency by slacks, therefore, the evaluation framework in this study is different from the previous ones and not only the regional efficiency levels for China are measured, but the types of returns to scale and damages to scale for each region are explored, which is considered more meaningful for policy-making regarding how to improve the effect of energy conservation, greenhouse gas emission reduction, and environment protection for each region of China.

The rest of this paper is organized as follows: Section 2 proposes the RAM-DEA model and several indicators for integrated energy and environmental efficiency measurement under natural disposability and managerial disposability, respectively. The related approaches for determining returns to scale and damages to scale are also presented in Section 2. In Section 3, the regional energy and environmental efficiency, the types of returns and damages to scale, as well as the RAM-DEA based energy conservations and CO2 emissions reduction potentials for China’s 30 regions during 2006–2010 are evaluated and analyzed. Furthermore, the strategies and policy implications for integrated energy and environmental efficiency improvement are also discussed in Section 3. Section 4 concludes this paper.

Section snippets

Methodology

In this study, we apply the Range-Adjusted Measure based DEA (RAM-DEA) models, which is first proposed by Cooper et al. [22] and then further developed by Sueyoshi and Goto [20] in environmental strategy, to measure China’s regional energy and environmental efficiency. Since the RAM-DEA models can easily combine both energy performance and environmental performance for each DMU under a unified treatment, this non-radial method is considered to be more appropriate than the traditional radial DEA

Empirical studies

In this section, we first describe the regions and areas of China, the input and output variables selected, and the associated data for integrated energy and environmental efficiency measurement. Then, the RAM-DEA models are applied and the indicators of IEND, PE, IEMD, and EE are calculated and analyzed for China’s 30 regions. In addition, the types of returns to scale and damages to scale, as well as the energy saving potential and CO2 emissions reduction potential for each of these regions

Conclusions

In recent years, increasing studies have focused on the measurement of energy efficiency or environmental efficiency applying DEA based approaches. In this paper, we applied the RAM-DEA approach to evaluate the integrated energy and environmental efficiency and determine the types of returns to scale and damages to scale, under the economic concepts of natural disposability and managerial disposability, respectively, for China’s 30 regions during the period of 2006–2010. Then, we proposed

Acknowledgements

We gratefully acknowledge the financial support from the National Natural Science Foundation of China (71101011 and 71020107026), the China Postdoctoral Science Foundation (20110490298 and 2012T50049), and the National Basic Research Program of China (2012CB95570004).

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