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Sustainability 2016, 8(9), 871; doi:10.3390/su8090871

Coal Consumption Reduction in Shandong Province: A Dynamic Vector Autoregression Model

1
Department of Economics and Management, Yuncheng University, Yuncheng 044000, China
2
School of Economic & Management, Northwest University, Xi’an 710127, China
*
Author to whom correspondence should be addressed.
Academic Editor: Giuseppe Ioppolo
Received: 29 May 2016 / Revised: 21 August 2016 / Accepted: 23 August 2016 / Published: 31 August 2016
(This article belongs to the Section Economic, Business and Management Aspects of Sustainability)
View Full-Text   |   Download PDF [1557 KB, uploaded 31 August 2016]   |  

Abstract

Coal consumption and carbon dioxide emissions from coal combustion in China are attracting increasing attention worldwide. Between 1990 and 2013, the coal consumption in Shandong Province increased by approximately 5.29 times. Meanwhile, the proportion of coal consumption of Shandong Province to China rose from 7.6% to 10.8%, and to the world, it rose from 1.8% to 5.5%. Identifying the drivers of coal consumption in Shandong Province is vital for developing effective environmental policies. This paper uses the Vector Autoregression model to analyze the influencing factors of coal consumption in Shandong Province. The results show that industrialization plays a dominant role in increasing coal consumption. Conversely, coal efficiency is the key factor to curtailing coal consumption. Although there is a rebound effect of coal efficiency in the short term, from a long-term perspective, coal efficiency will reduce coal consumption gradually. Both economic growth and urbanization have a significant effect on coal consumption in Shandong Province. In addition, the substitution effect of oil to coal has not yet met expectations. These findings are important for relevant authorities in Shandong in developing appropriate policies to halt the growth of coal consumption. View Full-Text
Keywords: coal consumption; STIRPAT model; vector autoregression model; impulse response functions; Shandong Province coal consumption; STIRPAT model; vector autoregression model; impulse response functions; Shandong Province
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Deng, C.; Dong, J.-F. Coal Consumption Reduction in Shandong Province: A Dynamic Vector Autoregression Model. Sustainability 2016, 8, 871.

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