Structural Analysis and Total Coal Demand Forecast in China
Considering the speedy growth of industrialization and urbanization in China and the continued rise of coal consumption, this paper identifies factors that have impacted coal consumption in 1985–2011. After extracting the core factors, the Bayesian vector autoregressive forecast model is constructed...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2014/612064 |
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| _version_ | 1832559102843158528 |
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| author | Qing Zhu Zhongyu Zhang Rongyao Li Kin Keung Lai Shouyang Wang Jian Chai |
| author_facet | Qing Zhu Zhongyu Zhang Rongyao Li Kin Keung Lai Shouyang Wang Jian Chai |
| author_sort | Qing Zhu |
| collection | DOAJ |
| description | Considering the speedy growth of industrialization and urbanization in China and the continued rise of coal consumption, this paper identifies factors that have impacted coal consumption in 1985–2011. After extracting the core factors, the Bayesian vector autoregressive forecast model is constructed, with variables that include coal consumption, the gross value of industrial output, and the downstream industry output (cement, crude steel, and thermal power). The impulse response function and variance decomposition are applied to portray the dynamic correlations between coal consumption and economic variables. Then for analyzing structural changes of coal consumption, the exponential smoothing model is also established, based on division of seven sectors. The results show that the structure of coal consumption underwent significant changes during the past 30 years. Consumption of both household sector and transport, storage, and post sectors continues to decline; consumption of wholesale and retail trade and hotels and catering services sectors presents a fluctuating and improving trend; and consumption of industry sector is still high. The gross value of industrial output and the downstream industry output have been promoting coal consumption growth for a long time. In 2015 and 2020, total coal demand is expected to reach 2746.27 and 4041.68 million tons of standard coal in China. |
| format | Article |
| id | doaj-art-d9f32c883f584bdb959280057c3c7340 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-d9f32c883f584bdb959280057c3c73402025-02-03T01:30:57ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2014-01-01201410.1155/2014/612064612064Structural Analysis and Total Coal Demand Forecast in ChinaQing Zhu0Zhongyu Zhang1Rongyao Li2Kin Keung Lai3Shouyang Wang4Jian Chai5School of Finance and Economics, Xi’an Jiaotong University, Xi’an 710061, ChinaSchool of Finance and Economics, Xi’an Jiaotong University, Xi’an 710061, ChinaCollege of Economics and Management, Southwest University, Chongqing 400715, ChinaInternational Business School, Shaanxi Normal University, Xi’an 710119, ChinaNational Center for Mathematics and Interdisciplinary Science, Chinese Academy of Sciences, Beijing 100190, ChinaInternational Business School, Shaanxi Normal University, Xi’an 710119, ChinaConsidering the speedy growth of industrialization and urbanization in China and the continued rise of coal consumption, this paper identifies factors that have impacted coal consumption in 1985–2011. After extracting the core factors, the Bayesian vector autoregressive forecast model is constructed, with variables that include coal consumption, the gross value of industrial output, and the downstream industry output (cement, crude steel, and thermal power). The impulse response function and variance decomposition are applied to portray the dynamic correlations between coal consumption and economic variables. Then for analyzing structural changes of coal consumption, the exponential smoothing model is also established, based on division of seven sectors. The results show that the structure of coal consumption underwent significant changes during the past 30 years. Consumption of both household sector and transport, storage, and post sectors continues to decline; consumption of wholesale and retail trade and hotels and catering services sectors presents a fluctuating and improving trend; and consumption of industry sector is still high. The gross value of industrial output and the downstream industry output have been promoting coal consumption growth for a long time. In 2015 and 2020, total coal demand is expected to reach 2746.27 and 4041.68 million tons of standard coal in China.http://dx.doi.org/10.1155/2014/612064 |
| spellingShingle | Qing Zhu Zhongyu Zhang Rongyao Li Kin Keung Lai Shouyang Wang Jian Chai Structural Analysis and Total Coal Demand Forecast in China Discrete Dynamics in Nature and Society |
| title | Structural Analysis and Total Coal Demand Forecast in China |
| title_full | Structural Analysis and Total Coal Demand Forecast in China |
| title_fullStr | Structural Analysis and Total Coal Demand Forecast in China |
| title_full_unstemmed | Structural Analysis and Total Coal Demand Forecast in China |
| title_short | Structural Analysis and Total Coal Demand Forecast in China |
| title_sort | structural analysis and total coal demand forecast in china |
| url | http://dx.doi.org/10.1155/2014/612064 |
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