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MBA论文_中国省域经济增长与产业集聚对二氧化碳排放的影响研究

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文本描述
国内图书分类号:F727 学校代码:10213
国际图书分类号:339密级:公开
管理学硕士学位论文
中国省域经济增长与产业集聚对二氧化碳排放
的影响研究
硕士研究生 : 梁植军
导师 : 王东副教授
申请学位 : 管理学硕士
学科 : 工商管理
所 在 单 位 : 深圳研究生院
答 辩 日 期 : 2018年6月
授予学位单位 : 哈尔滨工业大学
Classified Index:F727
U.D.C:339
Dissertation for the Master Degree in Management
THE INFLUENCE OF ECONOMIC GROWTH AND
INDUSTRIAL AGGLOMERATION ON CARBON
DIOXIDE EMISSION IN CHINA’S PROVINCE
Candidate:Zhijun Liang
Supervisor:Associate Prof. Dong Wang
Academic Degree Applied for:Master of Management
Speciality:Business Administration
Affiliation: Shenzhen Graduate School
Date of Defence:June, 2018
Degree-Conferring-Institution: Harbin Institute of Technology
摘要
I
摘要
自18世纪第二次工业革命以来,能源消耗加快,大气中的二氧化碳浓度快速上升
因此,为了应对气候变化带来影响,在20世纪90年代到21世纪初期期间,联合国政
府间气候变化专门委员会(IPCC)研究发行了多次全球气候变化评估报告。其中2007
年发表的第4次评估报告指出,全球温度升高属于不可争论的事实。中国是国际二氧化
碳排放的大国,目前国际以及中国对于二氧化碳减排的研究都非常重视,如何实现高效
低碳发展,具有重要意义。因此研究中国省区的碳排放的影响因素及其空间关联性对目
前具有比较大的研究意义
结合以往文献的研究以及本文所需要研究的内容,为探究省区二氧化碳排放的影响
因素,本文选取了经济增长、产业集聚、外商直接投资以及能源消耗等变量作为主要研
究自变量,同时选择人口密度、第二产业占比及从业人口占比等作为控制变量,这些变
量的数据获取主要是来自统计年鉴,并已接受相关标准化处理
利用面板数据验证省区之间二氧化碳排放与研究变量之间的影响关系;在面板数据
验证的基础下,再利用空间计量模型测算人均二氧化碳排放以及人均GDP的空间Moran
指数以及莫兰散点图LISA,以检测省区之间的空间关联性。结果发现中国省区之间的
人均二氧化碳和人均GDP存在比较强烈的空间关联性;同时通过空间杜宾计量模型
(SDM)发现,在空间视角下,省区人均二氧化碳排放和人均GDP之间存在“倒U型”
曲线,符合环境库兹涅兹的曲线假设。外商直接投资和二氧化碳排放之间具有负向关系,
利用空间计量模型对目前的二氧化碳泄露和二氧化碳转移进行直观解析,发现一些省级
区域为了降低本省的二氧化碳排放,通过高能耗产业转移的模式将二氧化碳排放转移到
周围的区域,说明目前中国省级污染产业转移、“搭便车”等相关情况很严重,一些经
济发达的省级区域通过产业转移将本省区高能耗和高排放的污染产业转移出去。外商直
接投资对二氧化碳排放的影响系数显著为负,说明外商直接投资的增加会对本区域的二
氧化碳排放起到抑制作用;同时,这种抑制作用在周围的省级区域中也存在。人口密度
对于二氧化碳排放的影响均通过显著性检验,在直接效应中可以发现,人口密度的增加,
会使得二氧化碳排放减少,说明人口密度增加是可以直接降低二氧化碳排放量,但是间
接效应和总的效应都是正向的,从空间角度看,这说明人口的大量增加虽然直接使得本
区域的人均二氧化碳排放减少,但却会导致周围临近区域的人均二氧化碳排放增加。存
在这个效应是非常合理的,这是因为人口总数总体上处于一个平稳的状态,因此短时间
内一个地方人口流入多,则其他地方人口自然相应流出多
关键词:二氧化碳排放;空间关联性;EKC曲线;经济增长
Abstract
II
Abstract
Since the rise of the European industrial revolution in the mid-eighteenth century, the
excessive depletion of fossil fuels has led to an increasing CO2 concentration in the
atmosphere. From the 1990s to the early twenty-first century, the IPCC(Intergovernmental
Panel on Climate Change ) studied and issued a number of global climate change assessment
reports. The fourth assessment report, published in 2007, pointed out that global warming is a
fact that cannot be disputable. As a big country in international carbon dioxide emissions,
China has been paying much attention to the research on carbon dioxide emission reduction. It
is very important to realize the high-efficient low carbon development. Therefore, it is of
great significance to study the influencing factors of carbon emissions and its spatial
correlation among China's provinces.
In order to explore the impact of CO2 emissions in the provinces and districts, combined
with the research on the impact of previous literature on CO2 emissions and the content of this
paper, we selected variables such as economic growth, industrial agglomeration, foreign
direct investment, and energy consumption as the main research variables. At the same time,
choose the population density and the proportion of the secondary industry. The proportion of
the employed population accounts for the control variables, and the data for these variables is
mainly derived from the statistical yearbook. After relevant processing, the models are
estimated.
In this paper, we first use panel data to verify the relationships between carbon dioxide
emissions and research variables among provinces. Based on that, we then use spatial
econometric model to measure the Moran index and the Moran scatter plot LISA of per capita
carbon dioxide emissions and per capita GDP, and to test spatial correlation results among
provinces. It is found that there is strong spatial correlation for per capita carbon dioxide
emissions and per capita GDP. Meanwhile, by using Spatial Dubin model (SDM), we find
that the “inverted U curve” still exists from the spatial perspective, which conforms to the
hypothesis of Environmental Kuznets Curve (EKC). Foreign direct investment still has an
inhibitory effect on carbon dioxide emissions. Through spatial econometric model, we get
more visual analysis about current carbon dioxide leakage and carbon dioxide transfer. It
shows that some provinces try to reduce their carbon dioxide emissions by transferring high
energy-consumption industries to surrounding areas, which illustrates that current
phenomenons of polluting industry transfers at province level and “hitchhiking” as well as
other relevant conditions are very serious. The influence coefficient of foreign direct
investment on carbon dioxide emissions is negative and significant, which indicates that the
introduction of foreign direct investment has an inhibitory effect on carbon dioxide emissions.
A the same time, this effect can also exist in surrounding provinces. The impact of population
density on carbon dioxide emissions is also significant. In the direct effect, we find that the
increase of population density can reduce carbon dioxide emissions directly. But both the
indirect and total effects are positive. It means that although the increase of population density
can reduce the per capita carbon dioxide emissions in local region, the per capita carbon。