期刊
JOURNAL OF CLEANER PRODUCTION
卷 209, 期 -, 页码 680-691出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.10.267
关键词
Green economy; Global Malmquist-Luenberger index; Panel vector autoregression; China
资金
- National Natural Science Foundation of China (NSFC) [71871169, 71373188, U1333115]
Theses on China's low-carbon economy focus on the driving forces of carbon emissions, energy carbon efficiency, and the carbon economy nexus. Meanwhile, comprehensive frameworks that assess China's green economy and also analyze its driving forces are lacking. This paper constructs a green productivity index based on the Global Malmquist-Luenberger productivity index to evaluate the development of the low-carbon economy in China. A panel vector auto-regression model is adopted to further analyze the endogenous interactions and dynamic relationships among aspects of the green economy and its influencing factors. Empirical results show that China has seen a balanced development of green economic growth in 2000-2016, achieved in a series of clear stages. To maintain the sustainable growth of the low-carbon economy in the future, China must rely more on technological progress. This research also makes some important discoveries that have not been found in previous studies: the impact of China's industrial structure and energy consumption structure on the green economy are short term, having a duration of impact of approximately four years. Finally, we provide an assessment of provincial green economy development and describe the corresponding policy implications. (C) 2018 Elsevier Ltd. All rights reserved.
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