文献类型：期刊文献

英文题名：Using a temporal input-output approach to analyze the ripple effect of China's energy consumption

作者：Cheng Yongwei[1];Mu Dong[2];Ren Huanyu[2];Fan Tijun[1];Du Jianbang[3]

机构：[1]East China Univ Sci & Technol, Sch Business, 130 Meilong Rd, Shanghai 200037, Peoples R China;[2]Beijing Jiaotong Univ, Sch Econ & Management, 3 Shangyuan Village, Beijing 100044, Peoples R China;[3]Texas Southern Univ, Dept Environm & Interdisciplinary Sci, 3100 Cleburne St, Houston, TX 77004 USA

年份：2020

卷号：211

外文期刊名：ENERGY

收录：;EI(收录号：20203609148979);WOS:【SSCI(收录号:WOS:000591606400014)，SCI-EXPANDED(收录号:WOS:000591606400014)】；

基金：This work was supported by National Natural Science Foundation of China (71904018, 71972071 and 71772016).

语种：英文

外文关键词：China's economy; Energy consumption forecasting; Temporal input-output approach; Ripple effect; Time curve

摘要：Forecasting energy consumption of economic activities is important for China to cope with climate change and maintain sustainable economic growth. This study proposes a novel temporal input-output approach that not only forecast the energy consumption of various economic sectors, but also reflects the spread process of inter-sectoral ripple effect of energy consumption from a temporal perspective. Using China's 2015 annual input-output table and data of nearly 3500 listed companies in China's A-share market, we plot the ripple time curves depicting actual energy consumption resulting from China's three main final demands, i.e., Investment, Export, and Consumption. The results show that the manufacturing sector, construction sector and electric power/thermal sector have critical impact on the China's energy consumption. Among all final demands, the Export demand and Investment demand are the main factors causing energy consumption. This study improves the input-output approach from the perspective of time in order to make timely and effective forecast for the China's energy consumption based on real-time data about final demands. (C) 2020 Elsevier Ltd. All rights reserved.