基于统计模型的安徽省碳排放量影响因素分析

VIP免费

3.0 牛悦 2024-11-11 5 4 384.46KB 32 页 15积分

侵权投诉

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，并根据分析结果对安徽省低碳减排提出相应的建议，为发展

经济与环境和谐的绿色经济提供参考．

本文首先采用 WLS 法和多元线性回归法对 1995 年－2010 年安徽省碳排放量

与影响因素进行实证分析．发现产业结构在2005 年前后存在较大的差异，于是在

模型中引入虚拟变量，得到以2005 年为分界点的两个线性回归模型．通过ADF

单位根检验得到序列是一阶差分平稳的，进一步运用Johansen 协整检验，发现两

个影响因素与碳排放量之间存在一种长期均衡稳定的关系．脉冲响应分析显示，

碳排放量受自身的冲击效果最为明显，这与 WLS 模型显示的结果相吻合：滞后项

系数为正数，说明环境质量存在路径依赖现象．

其次，考虑到OLS 法对变量均值的估计，比较适合用于同质性的序列．但是

对于一组具有异质性的序列做回归，拟合效果的特性就会有所缺失．因此，本文

引入了聚类线性回归模型对1985年－2010年安徽省碳排放量与影响因素进行实证

分析，即将聚类分析的方法引入到回归模型中，把数据分类后再分别进行回归．同

时，给出回归参数和观测数据的隶属度，判断模型的拟合程度的好坏．模型结果

发现把观测数据分为三类最为合适，并给出了每个类别的线性回归系数，可以依

次看到不同类别中四种影响因素对碳排放量的影响程度．

最后，基于以上研究结论，提出低碳经济发展的政策建议：优化能源消费结

构和提高能源利用效率，通过能源替代，改变以煤炭为主的能源结构；积极推进

产业结构优化升级，提高技术水平，促进第三产业的大力发展；控制人口总量，

提高人民生活水平，将高科技的生活方式引进人们的日常生活，从底层改变能源

消耗方式．

关键词：低碳经济能源强度协整检验聚类线性回归

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 level、industrial 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 words：Low carbon economy, Energy intensity, Co-integration test,

Clusterwise regression analysis

中文摘要

ABSTRACT

第一章引论 ....................................................1

1.1 研究背景及意义 ............................................1

1.1.1 研究背景 ..............................................1

1.1.2 研究意义 ..............................................1

1.2 国内外相关研究成果 ........................................2

1.3 研究思路、内容及创新点 ....................................3

1.3.1 研究思路与研究内容 ....................................3

1.3.2 创新点 ................................................4

1.4 研究方法 ..................................................4

第二章基于WLS 模型及协整检验的安徽省碳排放量影响因素分析 .......6

2.1 指标选取和数据说明 ........................................6

2.2 碳排放量及其影响因素实证研究 ..............................7

2.2.1 WLS 回归结果分析........................................8

2.2.2 关于碳排放量和经济增长、产业结构的 VAR 实证分析 .......10

2.2.3 Johansen 协整检验、脉冲响应分析........................12

第三章基于聚类回归模型的安徽省碳排放量影响因素分析 ............14

3.1 方法介绍及模型构建 .......................................14

3.2 迭代最小二乘估计的算法 ...................................16

3.3 拟合检验 .................................................16

3.4 CWLR 模型结果..............................................18

3.5 实证分析 .................................................20

第四章低碳排放下的政策建议 ....................................22

4.1 安徽省低碳发展现状 .......................................22

4.2 发展低碳经济的政策建议 ...................................22

第五章总结及展望 ..............................................24

5.1 总结 .....................................................24

5.2 展望 .....................................................25

参考文献 .......................................................26

在读期间公开发表的论文 ..........................................30

致谢 ...........................................................31

文档加载中……请稍候！
如果长时间未打开，您也可以点击刷新试试。

下载文档到电脑，查找使用更方便

15 积分 4人已下载

立即下载 VIP免费下载

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...

展开>> 收起<<

基于统计模型的安徽省碳排放量影响因素分析.pdf

共32页,预览4页

还剩页未读，继续阅读

基于统计模型的安徽省碳排放量影响因素分析

相关推荐

开通VIP享超值会员特权

作者详情

相关内容

推荐作者

热门标签

举报选择: