4.7 Article

Energy efficiency in China's industry sectors: A non-parametric production frontier approach analysis

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 200, Issue -, Pages 880-889

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.07.277

Keywords

Energy productivity; Decision mechanisms; Non-parametric production frontier approach; China's industry sector

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There is increasing recognition of the importance of energy productivity in China due to the considerable growth in industrial energy consumption in the past several decades. Energy productivity improvements should be approached through changes in factors such as efficiency, technology use and factor substitution. Thus, the aim of this study is to decompose the energy productivity rate of change in a non parametric framework. We combine data envelopment analysis (DEA) and the Malmquist index, using a data set of 35 two-digit industries in China from 1998 to 2011. The conclusions highlight three key points. First, the dynamic DEA reveals that technical progress is the primary source of energy productivity improvement. Technical efficiency plays a promoting role. The contribution from factor substitution is the least. Second, regarding change, from 1998 to 2003, the positive effect of technology progress was very prominent; however, technological efficiency played a small role and may have even impeded progress. From 2007 to 2010, technology progress had insufficient power; however, the role of efficiency improvement was obvious. The dynamic changes between technology progress and efficiency improvement result in a wide range of technological innovations and efficiency improvements in the entire industry. Third, factor substitution has a prominent positive contribution in light industrial sectors but hinders the improvement of energy productivity in heavy industrial sectors. The most efficient industry is telecommunications equipment, computer and other electronic equipment. This study concludes that China should raise the relative cost of energy consumption and optimize energy allocations and other production factors. (C) 2018 Elsevier Ltd. All rights reserved.

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