基于BP结构突变的中国能源强度及因素分解研究
Analysis on structural break based on BP method and factor decomposition of energy intensity in China
查看参考文献21篇
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文摘
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能源是人类生存和发展的物质基础,是中国经济可持续发展的关键。中国能源消耗量虽在逐年降低,但仍是世界上能源消耗量最大的国家。伴随常规能源的日益枯竭,能源安全问题成为中国经济可持续发展的瓶颈,因此,降低能源强度迫在眉睫。系统研究中国能源强度下降原因并进行因素分解有助于深入把握能源变动规律,具有重要的现实意义和应用价值。文章运用BP结构突变模型对1980—2015年能源强度突变点检验,建立LMDI分解模型,将能源强度分解为部门能源强度、运输线路单位长度能耗、运输线路产出能耗、人均生活用能、城市化、人均收入效应、产业结构、能源结构八个因素,分析能源强度各阶段动因变化特征。计算结果表明,受经济发展及国家政策冲击,能源强度在1980—2015年样本期间存在1991年、2002年和2008年三次结构突变,形成四阶段不同增长趋势。能源强度在样本期间呈整体下降趋势,能源强度各阶段主要影响因素不同,但是部门能源强度和能源结构对中国能源强度作用最大,人均生活用能、人均收入效应和产业结构中的交通运输仓储及邮电通信业对能源强度影响显著;在样本期内,各影响因素作用方向转变导致能源强度阶段特征不同。针对中国能源强度的阶段特征,提出开发推广可再生能源技术以调整能源结构;促进应用低碳节能产品以降低生活用能;推动增加第三产业比重以提高人均收入水平;加快建设运输节能技术以降低交通运输业能源强度等对策建议。 |
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其他语种文摘
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Energy is the material basis for human survival and development,it is the key to sustainable development of China's economy,and it also reveals the performance of social progress. Although energy consumption in China is decreasing,China is still the largest energy consumption country in the world. With the decline of conventional energy sources,energy security becomes the bottleneck of sustainable development China's economy. Therefore,energy intensity needs to be reduced urgently. It is significant to study the reasons of energy intensity decline; by using factor decomposing,it is helpful to find rules of energy changes. The structural breaks of energy intensity in China from 1980 to 2015 were examined by using BP method and LMDI decomposition model to study the reasons for the decline of different stages. In this paper,energy intensity was decomposed into eight factors,namely energy intensity in sectors,energy consumption per unit length of transportation routes,energy consumption of transportation output,per capita living energy consumption,urbanization,per capita income effect,industrial structure,and energy structure. The experimental results showed that three structural breaks existed from 1980 to 2015 due to the economic development and national policy shocks. And the structural breaks took place in 1991,2002 and 2008,which divided the time series of energy intensity in China into four stages. In addition,energy intensity showed a decreasing trend during the sample period and the main factors of the reduction in energy intensity were energy intensity in each sector and energy consumption structure. Meanwhile,per capita living energy,per capita income effect, and transportation industry had significant impact on energy intensity. Taking into account of the contribution of each factor to energy intensity,we put forward several suggestions. The renewable energy technologies need to be developed and popularized to adjust the energy consumption structure. What's more,low-carbon energy saving products should be applied to reduce the living energy consumption. Besides the per capita income needs to be increased by increasing the proportion of the tertiary industry. Energy saving way of transportation should be developed to reduce the energy intensity of transportation industry. |
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来源
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中国人口·资源与环境
,2018,28(2):28-35 【核心库】
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DOI
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10.12062/cpre.20170716
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关键词
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能源强度
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BP结构突变
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因素分解
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能源结构
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地址
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南京航空航天大学经济与管理学院, 江苏, 南京, 211106
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1002-2104 |
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学科
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社会科学总论 |
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基金
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国家自然科学基金项目
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国家教育部人文社会科学研究项目
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江苏省高校社会科学重点项目
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江苏省社会科学基金项目
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文献收藏号
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CSCD:6193119
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参考文献 共
21
共2页
|
|
1.
Balezentis A. The energy intensity in Lithuania during 1995-2009: a LMDI approach.
Energy policy,2011,39(11):7322-7334
|
被引
3
次
|
|
|
|
|
2.
阚大学. 我国城市化对能源强度的影响-基于空间计量经济学的分析.
当代财经,2010(3):83-88
|
被引
4
次
|
|
|
|
|
3.
张成龙. 1997—2007年中国能源强度变化的因素分解.
清华大学学报(自然科学版),2013,53(5):688-693
|
被引
3
次
|
|
|
|
|
4.
Andres L. Energy intensity in road freight transport of heavy goods vehicles in Spain.
Energy policy,2015,85:309-321
|
被引
2
次
|
|
|
|
|
5.
张伟. 基于LMDI的我国工业能源强度变动的因素分解:对我国1994-2007年工业部门数据的实证分析.
管理评论,2012,24(9):28-36,95
|
被引
1
次
|
|
|
|
|
6.
郑若娟. 中国制造业真实能源强度变化的主导因素-基于LMDI分解法的分析.
经济管理,2011(10):23-32
|
被引
3
次
|
|
|
|
|
7.
Chow G. Tests of equality between sets of coefficients in two linear regressions.
Econometrica,1960,28(3):591-605
|
被引
45
次
|
|
|
|
|
8.
Bai J. Estimating and testing linear models with multiple structural changes.
Econometrica,1998,66(1):47-78
|
被引
45
次
|
|
|
|
|
9.
Bai J. Likelihood ratio tests for multiple structure changes.
Journal of econometrics,1999,91(2):299-323
|
被引
9
次
|
|
|
|
|
10.
Ang B W. Handling zero values in the Logarithmic Mean Divisia index decomposition approach.
Energy policy,2007,35(1):238-246
|
被引
35
次
|
|
|
|
|
11.
Wu L. Driving forces behind the stagnancy of China's energy: related CO_2 emissions from 1996 to 1999: the relative importance of structural change,intensity change and scale change.
Energy policy,2005,33(3):319-335
|
被引
18
次
|
|
|
|
|
12.
Ang B W. A new energy decomposition method: perfect in decomposition and consistent in aggregation.
Energy,2001,26(6):537-548
|
被引
56
次
|
|
|
|
|
13.
刘源. 基于LMDI分解的厦门市碳排放强度影响因素分析.
生态学报,2014,34(9):2378-2387
|
被引
19
次
|
|
|
|
|
14.
Tan Z. Examining the driving forces for improving China's CO_2 emission intensity using the Decomposing Method.
Applied energy,2011,88(12):4496-4504
|
被引
1
次
|
|
|
|
|
15.
Sadorsky P. Do urbanization and industrialization affect energy intensity in developing countries?.
Energy economics,2013,37:52-59
|
被引
13
次
|
|
|
|
|
16.
林伯强. 中国城市化阶段的碳排放:影响因素和减排策略.
经济研究,2010(8):66-78
|
被引
86
次
|
|
|
|
|
17.
Jaffe A. Geographic localization of knowledge spillovers as evidenced by patent citations.
Quarterly journal of economics,1993,108(3):577-598
|
被引
107
次
|
|
|
|
|
18.
李标. 城镇化、工业化、信息化与中国的能源强度.
中国人口·资源与环境,2015,25(8):69-76
|
被引
9
次
|
|
|
|
|
19.
宁自军. 基于LMDI模型的浙江省能源强度变动影响因素分析.
统计与信息论坛,2013,28(2):80-83
|
被引
2
次
|
|
|
|
|
20.
李国璋. 中国能源强度变动的区域因素分析-基于LMDI分析方法.
财经研究,2008,34(8):52-62
|
被引
11
次
|
|
|
|
|
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