基于统计模型的安徽省碳排放量影响因素分析

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业化程促经济飞速发展,使得能源在社会发展中更加凸显.因
为能源系到一个国家经济命脉重要战略物资因此世界各对能源求越
来越大,能源储备量却越来越少.能源消耗释放二氧起温室效应
当今气候变核心问题.因此目前开展对低碳经济研究
重要的意
2009 哈根球气候上,政府宣布自己减排目由此
也拉低碳经济研究序幕很多献对低碳经济做出研究
是不同国家,省域状况差异.因此,本文模型安徽省
二氧碳排放量及素(、人财富技术水平
进行实证研究,并据分析结果对安徽省低碳减排提相应建议为发展
经济与环境绿色经济提供参考
本文首先采用 WLS 元线性回归法对 1995 2010 安徽省碳排放量
进行实证.发2005 大的差异,于是在
模型中引虚拟变量得到2005 线性回归模型ADF
得到是一的,进步运Johansen 协整现两
素与碳排放量之间在一种长衡稳定的关系.脉响应
碳排放量冲击为明显这与 WLS 模型吻合滞后项
数,环境路径依赖现象
考虑OLS 法对变量估计适合用于同质性
质性回归拟合特性就缺失.因此,本文
入了聚类线性回归模型19852010徽省碳排放量与进行实证
聚类方法引回归模型数据分类后再进行回归
回归参数和观测数据的判断模型拟合好坏模型结
现把观测数据分三类最合适,并类别线性回归数,可以
次看到不类别四种碳排放量的影
最后于以上研究论,低碳经济发展建议化能源
构和能源过能源替代煤炭能源;积极推
升级技术水平的大发展制人
民生活水平,将生活方式引进人的日常生活从底层能源
消耗方式.
关键经济 强度 检验 线性回归
ABSTRACT
With the rapid economic development drived by industrialization, energy has
become more and more important in social development. Because energy is the strategic
material which has a relationship with economic lifeline, the demand for energy is
increasing for countries in the world . But energy storage capacity is less and less. CO2
produced excessively by energy consumption has resulted in the greenhouse effect,
which has become the core of the climate changing problem. Therefore there is great
significance to study how to develop low carbon economy in our country at present.
Our country announced our reduction goal in the Copenhagen conference in 2009.
Since then, our country began to research the low carbon economy. Although there are a
lot of literatures on low carbon economy in our country, situations are very different
during different countries, different provinces. Therefore, this paper mainly establish
models to make an empirical study of carbon emissions and its influencing
factors(population size per capita wealth technology levelindustrial structure) in
Anhui province. Then giving the corresponding policies and suggestions on low carbon
emission reduction according to the results of the analysis can provide a reference for
the development of green economy: economy and environment are harmonious.
This paper mainly uses WLS method and multivariate linear regression method to
establish empirical models of the relationship between carbon emissions and its
influencing factors in Anhui province during 1995-2010. We find that the industrial
structure is abnormal around 2005, so we introduce dummy variables in the model, and
then get two linear regression models with 2005 as the boundary. ADF unit root test
shows that the sequence is first order difference stationary, and Johansen co-integration
test shows that there is a long-term relationship between carbon emission and two
factors. Impulse response analysis shows that carbon emission is more obviously
affected by itself which matches with the result of WLS model. The coefficient of
lagged variable is positive which means that environment quality has a path
dependence.
Then, considering OLS model is more suitably utilized in estimating the mean
value of the variables when the sequence is homogeneous. However, in many real cases,
where the observations are not homogeneous, utilizing the traditional regression, has a
loss of fitting performance of the regression model. In order to improve the goodness of
fit, it is more suitable to utilize the clusterwise regression analysis, in which we embed
the techniques of clustering into regression analysis. Furthermore, the regression
parameters and membership degrees can be estimated simultaneously, and we obtain the
index measuring in the goodness of fit of CWLR model. Model results show that
dividing the data into three categories are most appropriate, and influence factors show
us the four factors how influenced the carbon emissions in each cluster.
Finally, we propose the following suggestions to develop low carbon economic
based on the above conclusions: optimize energy consumption structure and improve
energy utilization efficiency by means of the energy substitution; promote the upgrading
of the industrial structure actively and improve the technical level; control the total
population, improve the living standard of people and by introduce high-technology to
daily life.
Key wordsLow carbon economy, Energy intensity, Co-integration test,
Clusterwise regression analysis
摘要
ABSTRACT
....................................................1
1.1 研究背景 ............................................1
1.1.1 研究背景 ..............................................1
1.1.2 研究 ..............................................1
1.2 国内研究 ........................................2
1.3 研究、内容创新 ....................................3
1.3.1 研究研究内容 ....................................3
1.3.2 创新 ................................................4
1.4 研究方法 ..................................................4
WLS 模型及协整安徽省排放量 .......6
2.1 和数据 ........................................6
2.2 碳排放量及素实证研究 ..............................7
2.2.1 WLS 回归........................................8
2.2.2 关于碳排放量经济构的 VAR 实证 .......10
2.2.3 Johansen 协整响应........................12
聚类回归模型安徽省碳排放量 ............14
3.1 方法介绍及模型 .......................................14
3.2 代最估计 ...................................16
3.3 拟合 .................................................16
3.4 CWLR 模型结..............................................18
3.5 实证 .................................................20
低碳排放建议 ....................................22
4.1 安徽省低碳发展 .......................................22
4.2 发展低碳经济建议 ...................................22
第五章 结及 ..............................................24
5.1 .....................................................24
5.2 .....................................................25
参考 .......................................................26
公开发表的论文 ..........................................30
致谢 ...........................................................31
摘要:

摘要工业化进程促进经济飞速发展,使得能源在社会发展中的地位更加凸显.因为能源关系到一个国家经济命脉的重要战略物资,因此世界各国对能源的需求越来越大,而能源的储备量却越来越少.能源消耗释放的二氧化碳引起温室效应,这已成为当今气候变化的核心问题.因此,目前开展对我国低碳经济的研究具有十分重要的意义.2009年在哥本哈根全球气候大会上,我国政府宣布了自己的减排目标,由此也拉开了我国低碳经济研究的序幕.我国已有很多文献对低碳经济做出研究,但是不同国家,不同省域的状况存在很大差异.因此,本文主要建立模型对安徽省的二氧化碳排放量及其影响因素(人口规模、人均财富、技术水平、产业结构)关系进行实证研究,并根据...

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作者:牛悦 分类:高等教育资料 价格:15积分 属性:32 页 大小:384.46KB 格式:PDF 时间:2024-11-11

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