SPECIAL ISSUE PAPER
Analysis of Influencing Factors of Change of Manufacturing Energy Intensity in China Based on WSR System Methodology and VAR Model
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1
School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang, CHINA
2
College of Transport Management, Dalian Maritime University, Dalian, CHINA
3
School of Economics and Management, Nanjing Agricultural University, Nanjing, CHINA
Online publication date: 2017-11-24
Publication date: 2017-11-24
EURASIA J. Math., Sci Tech. Ed 2017;13(12):8039-8050
This article belongs to the special issue "Problems of Application Analysis in Knowledge Management and Science-Mathematics-Education".
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ABSTRACT
Since China’s reform and opening up, although energy intensity of manufacturing industry has showed a trend of decline overly, compared with developed countries, it remains high. The research object of this paper is energy intensity of manufacturing industry, based on Wuli–Shili-Renli system methodology, it builds factors system of energy intensity of manufacturing industry. Based on time series data from 1980 to 2014, it uses VAR model to explore influence law of various factors on manufacturing energy intensity. Impulse response analysis shows that in the short term, the whole society fixed asset investment structure, technological progress, economic development level and structure of property rights have a great influence on energy intensity. With the increase of technological progress rate, per capita GDP, proportion of state-owned enterprises, manufacturing energy intensity starts to reduce; with the increase of proportion of investment in fixed asset of energy intensive industries, manufacturing energy intensity starts to rise. In the long term, energy price, energy consumption structure, FDI and industry structure have a great influence on manufacturing energy intensity. With the increase of proportions of coal consumption and heavy industry, manufacturing energy intensity starts to rise; with the increase of energy price, manufacturing energy intensity starts to reduce. Variance decomposition shows that energy consumption structure, energy price and technological progress have a greater contribution to manufacturing energy intensity, optimizing energy consumption structure, controlling energy price and promoting technological progress are important approaches to reducing manufacturing energy intensity.
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