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SCIENTIA GEOGRAPHICA SINICA  2016, Vol. 36 Issue (11): 1661-1669
中国城镇化影响能源消耗的效应分解及机制探析
中国城镇化影响能源消耗的效应分解及机制探析
程开明1,, 张亚飞1, 陈龙1
浙江工商大学统计与数学学院, 浙江 杭州 310018

作者简介:程开明(1975–),男,湖北广水人,教授,博士生导师,主要从事城市与区域经济分析、空间统计方法及应用研究。E-mail:chengkaim@163.com

摘要

依据2000~2012年的省级面板数据,以空间杜宾模型为基础对全国及东部、中部、西部三大地区城镇化影响能耗强度的实际效应进行分析,利用求偏微分法将影响效应分解为直接效应与间接效应,解析城镇化影响能源消耗的内在机制。分析发现,当前城镇化对能耗强度具有正向促进作用,不同地区的城镇化进程对能耗强度的影响存在显著差异;全国范围内城镇化影响能源强度的总效应中间接效应显著为正,直接效应不明显,而东部、中部及西部三大地区呈现出不同的模式;中国城镇化对能源消耗的影响是规模效应、技术效应、结构效应、阶段性效应及空间效应综合作用的结果。

关键词: 城镇化; 能耗强度; 空间杜宾模型;
Effects Decomposition and Theoretical Mechanism of Urbanization Influencing Energy Consumption in China
Cheng Kaiming1,, Zhang Yafei1, Chen Long1
School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, Zhejiang, China
Abstract

In order to explore effects of urbanization on energy consumption in China, the Spatial Dubin Model is used to analyze the influence of urbanization on energy intensity according to panel data in 2000-2012. After the spatial spillover effect is estimated, the total effects are decomposed to direct effects and indirect effects by partial differentiation. Results show that urbanization is an importance factor on the increase of energy intensity and the influence indicate obvious difference among three regions. Indirect effects of urbanization influencing energy intensity are significantly positive for all provinces. But direct effects are not obvious and present different patterns among three regions. Then theoretical mechanism of urbanization influencing energy consumption is analyzed. The influence of urbanization on energy consumption is the combined action of scale effects, technology effects, structure effects, stage effects and spatial effects. The direct effects of urbanization affecting energy consumption are the result of scale effects, technological effects, structural effects and stage effects, including direct and indirect paths. The indirect effects of urbanization affecting energy consumption are mainly derived from spillover effects between the regions. The results of this article show that urbanization plays an important role in the growth of energy consumption. Nowadays, Chinese government is accelerating the pace of urbanization, which may need more energy demand. Thus, studying the relationship between urbanization and energy consumption is very important to draw up urbanization planning and energy policy. Some recommendations are put forward to promote economic transformation and upgrading, accelerate the construction of ecological civilization. The following research will pay more attention to the nonlinear effects of urbanization on energy intensity and the effects of different types of city on energy consumption, which can provide constructing suggestions for government policy.

Keyword: urbanization; energy intensity; spatial Dubin model;

中国城镇化快速推进,城市在社会经济中的作用日显突出。与此同时,能源消耗总量不断增加,面临的能源问题备受关注[1]。据国际能源署(IEA)统计,2006年中国城市能源消耗占到总能耗的75.15%,城镇居民人均商业化能源消耗量是农村居民的6.8倍[2];2012年中国城镇居民人均生活用能量是农村人均生活用能量的1.38倍[3]。显然,城镇化在能源消耗和温室气体排放中起着举足轻重的地位,对于城镇化影响能源消耗的实际表现及内在机理尤其值得关注和探究,以便确定有效的能耗管理策略。

一些学者利用国家层面的截面及面板数据,得到城镇化增加能源需求、产生更多温室气体排放即城镇化与能源消耗之间正相关的结论[4,5]。这种正相关性既在发达国家有所体现,譬如西欧国家、美国等,也体现于发展中国家,但在不同收入水平组之间具有显著差异[6]。也有部分文献指出城镇化与能源消耗之间存在负相关性[7,8],抑或城镇化对能源强度的影响方向不明确[9]。一些文献则利用时序数据考察城镇化与能源消耗之间的因果关系[10],验证城镇化对能源消耗长期格兰杰因果关系的存在[11],并揭示了城镇化对能源消耗的短期动态冲击影响[12]。中国城镇化快速推进,能源消耗总量日益增加,很多学者指出两者之间存在密切关系。中国城镇化引致的大规模人口乡城转移及快速经济增长使能源消费量显著增加[13],成为推动能源消耗上升的一个重要因素[14,15],使得城镇化与能源消耗之间具有高度的正相关性[16,17]和长期均衡关系[18],但在地区之间存在显著差异[19]

已有研究大多利用传统计量模型进行分析,假定区域个体之间相互独立,而现实中地区之间往往存在着明显的空间依赖性,解析城镇化对能源消耗的影响效应须考虑到这种空间依赖性,采用空间计量模型开展分析更为合适。少数学者直接用空间计量模型中城镇化水平空间滞后项的估计系数来解释城镇化对能源消耗的空间溢出效应,结论也存在一定的偏误,因为如果被解释变量的空间滞后项回归系数不为零,则不能直接用回归系数来度量空间溢出效应[20],需利用空间回归模型的偏微分方法将解释变量对被解释变量的总效应分解为直接效应、间接效应来加以反映。

为此,本文利用空间杜宾模型测算全国城镇化影响能源消耗的实际效应,将城镇化影响能源消耗的总效应分解为直接效应与间接效应,开展东部、中部、西部三大地区的对比分析,全面解析城镇化影响能源消耗的效应与机制。依据研究结论得到的若干政策启示,对于合理推进新型城镇化,履行中国在碳排放方面的国际承诺,推动经济增长方式转变,具有重要的现实意义。

1 基本模型及数据来源
1.1 基本计量模型

STIRPAT模型被广泛用于探讨经济发展过程中各因素对环境资源要素的影响效应[21],模型基本形式为:

I = a P b E c T d ε (1)

式中,I代表环境或资源冲击,P代表人口因素,E代表经济发展水平,T代表影响I的其他因素,a为模型的系数,bcd为各自变量指数, ε 表示误差项。

现实中影响能源消耗的因素较多,主要包括经济发展水平、城镇化水平、产业结构、技术进步和能源价格等。社会生产是以资源的消耗为基础,人口增长与经济发展本身意味着更多的能源消耗,且随着经济发展、居民消费水平及消费结构的变化推动能源消费结构升级,进而影响能耗强度;作为影响能源消耗的重要变量,城镇化水平提高既可以通过促进经济增长等途径带来规模效应而增加能源的消耗,也可通过技术效应和结构效应来减少能源消耗;根据配弟-克拉克定理,产业发展通常按照农业→工业→服务业的顺序交替占居主导地位[22],不同产业的能耗系数不同,因此产业结构变化也会带来能耗强度的差异;技术进步一方面能够增加单位能源消耗的产出、降低能耗强度,另一方面产生回弹效应使得能源效率下降;对外开放有利于引进外资及国外先进技术,有助于提高生产效率,降低能耗强度;能源价格必然影响到能源的使用,价格上涨可能带来能源效率的提高与节约使用。由于区域能源消耗总量明显受到人口数量、土地面积等条件的影响,为剔除其影响,切实考察上述几个主要因素对能源消耗的影响效应,在此以能源强度为因变量,设定计量模型如下:

Ln ( E it ) = α 1 Ln ( G it ) + α 2 Ln ( U it ) + α 3 Ln ( S it ) + α 4 Ln ( T it ) + α 5 Ln ( R it ) + α 6 Ln ( F it ) + α 7 Ln ( P it ) + b i + c t + ε it (2)

式中,Eit表示i地区t时期的单位生产总值(GDP)能耗,用来衡量能源消耗强度,其中GDP为基年不变价GDP;Git表示i地区t时期的人均GDP,用以衡量经济发展水平;Uit代表i地区t时期城镇化水平,即城镇人口占总人口比重;SitTit分别代表i地区t时期第二产业增加值占GDP的比重、第三产业增加值占GDP的比重,用以衡量产业结构;Rit代表i地区t时期RD经费支出占GDP比重,用以衡量技术进步;Fit表示i地区t时期外商直接投资额占GDP比重,用以衡量对外开放程度;Pit代表能源价格,用i地区t时期原材料、燃料、动力购进价格指数表示。 α 为各自变量的弹性系数,bii地区的个体效应,ctt时期的时期效应, ε it i地区t时期的误差项,服从白噪声分布。

1.2 数据来源

实证分析所使用的数据是2000~2012年中国30个省、直辖市和自治区的面板数据,西藏由于能源数据缺失不纳入分析范围,数据来源于历年《中国统计年鉴》[23]、《中国能源统计年鉴》[24]和《中国人口和就业统计年鉴》[25]

2 城镇化影响能源消耗的效应及分解
2.1 空间计量模型的选择与设定

考虑到不同省份之间的能源强度和城镇化水平可能存在由空间相互作用而导致的空间依赖性,首先利用Moran’s I系数对2000~2012年全国30个省份的能源强度和城镇化水平进行空间自相关检验,其中空间权重矩阵以两地省会中心坐标球面距离的倒数来表示,结果见图1所示。

图1 能源强度和城镇化水平的Moran’s I系数 Fig.1 The coefficient of Moran’s I about energy intensity and urbanization

能源强度和城镇化水平的Moran’s I系数均为正,且都通过1%的显著性水平检验,说明2000~2012年两个指标存在着明显的空间自相关性,即较高城镇化水平省份的周边省份城镇化水平也较高,能源强度较低省份的周边省份能源强度也较低,因此探讨城镇化影响能源消耗的效应时必须考虑空间自相关带来的影响,采用空间计量模型开展分析。

对能源强度和城镇化水平的空间自相关分析显示,因变量、自变量均存在显著的空间自相关,需同时考虑因变量的空间滞后项和自变量的空间滞后项,故采用空间杜宾模型(Spatial Durbin Model, SDM) [26]进行分析。通过拉格朗日检验统计量(LM)和稳健拉格朗日检验统计量(Robust LM)进行空间滞后模型与空间误差模型的选择[27],分别对不存在个体和时期效应的模型、存在个体效应的模型、存在时期效应的模型以及存在个体和时期效应的模型进行估计检验,结果显示,模型中引入个体效应和时间效应的作用是显著的,因此把基本模型定为同时存在个体效应与时期效应的普通面板模型。从LM统计量可以看出时空固定效应模型同时存在因变量空间自相关和误差项空间自相关,所以继续观察Robust LM统计量,验证两种空间效应都存在的结论。

表1 LR、Wald统计量检验 Table 1 LR test and Wald test

以上检验了因变量和误差项的空间自相关性,没有检验自变量的空间效应,进一步通过LR和Wald统计量对空间杜宾模型能否简化为空间滞后模型和空间误差模型的检验来验证自变量空间效应的存在,进而确定空间计量模型的形式。

表1所示,对存在个体效应和时间效应的空间杜宾面板模型进行LR和Wald检验发现,空间杜宾模型不能简化为其他形式,同时经过改进的空间豪斯曼检验发现个体效应与时间效应都应为固定效应。综上,本文将采用存在时空固定效应的空间杜宾面板模型进行实证分析,即:

Ln ( E it ) = ρ W ij Ln ( E it ) + α 1 Ln ( G it ) + α 2 Ln ( U it ) + α 3 Ln ( S it ) + α 4 Ln ( T it ) + α 5 Ln ( R it ) + α 6 Ln ( F it ) + α 7 Ln ( P it ) + β 1 W ij Ln ( G it ) + β 2 W ij Ln ( U it ) + β 3 W ij Ln ( S it ) + β 4 W ij Ln ( T it ) + β 5 W ij Ln ( R it ) + β 6 W ij L n ( F it ) + β 7 W ij Ln ( P it ) + b i + c t + ε it (3)

式中,Wij为空间权重矩阵,代表两个地区间的空间联系,以省会中心坐标球面距离的倒数表示。 W ij Ln ( E it ) 为因变量空间滞后项, ρ 为滞后项系数; α 为自变量的弹性系数, β 为自变量的空间滞后项系数;bii地区的个体效应,ctt时期的时期效应, ε it i地区t时期的误差项,服从白噪声分布。

2.2 空间杜宾模型估计结果

采用时空固定效应的空间面板杜宾模型对全国及东部、中部、西部地区城镇化影响能源消耗的效应开展空间计量分析,结果见表2所示。

表2 全国及三大地区空间杜宾模型参数估计结果 Table 2 Parameter estimations of spatial Dubin model

表2可看出,全国范围内经济发展对能源强度产生显著的负向影响,意味着经济发展水平越高能源强度越低,但这种效应主要位于东部地区,中部、西部地区不显著;第二产业比重、第三产业比重都对能源强度具有显著的正向影响,说明第二、第三产业比重的提高导致能源强度上升,且在东部、中部及西部表现出较强的一致性;全国技术进步对能源强度的影响不很显著,但在东部地区两者表现出显著的正向关联性;外商直接投资对能源强度的正向影响不显著,地区之间具有较大差异;能源价格对能源强度总体具有负向影响,主要表现在东部地区。

从城镇化水平的系数可看到,全国、东部和中部地区的城镇化对能耗强度存在着显著为正的直接影响,西部地区的城镇化对能耗强度也存在着正向影响但不显著。在城镇化发展的不同阶段,城镇化所伴生的各种问题往往对能源消耗产生非线性的影响[29],两者之间可能表现出正向关联性[4,5],也可能是负相关[6,7],抑或影响效应不明确[8]。对于像中国这样发展中的人口大国,经济快速增长推动城镇化进程,城镇化水平上升提高了整体能源消耗水平[29]。虽说城镇化对能源消耗具有双刃剑的作用,即城镇化水平提高既可以通过促进经济增长导致经济规模扩大、人们生活水平提高,增加能源消费,也可通过带动技术进步等技术效应或者提高第三产业比重等结构效应而减少能源消耗[30],但当前中国城镇化进程带来的规模效应远大于技术效应,加之第三产业比重偏低且存在内部行业结构不合理等问题,产业结构效应并不突出,所以快速城镇化进程对中国能源消费总量和能耗强度总体上仍处于正向影响阶段。

从空间溢出的角度来看,代表全国及东部、中部及西部地区能耗强度空间溢出效应[W×Ln(E)]的系数估计值分别为-1.961 5、-1.172 1、-0.957 6、-1.150 7,均显著为负,说明全国和东部、中部、西部三大地区的能源强度都呈现出一定的空间收敛效应,效应上全国要高于东部、中部、西部地区。全国范围内经济发展、城镇化、第二产业比重、技术进步等变量空间溢出系数通过5%水平下的显著性检验,第三产业比重、外商直接投资和能源价格等变量的空间溢出系数未通过显著性检验,但东部、中部及西部地区之间表现出较大的差异。

2.3 直接效应与间接效应的分解

由于空间杜宾模型中同时包含因变量和自变量的空间滞后项,参数经济含义较为复杂,可进一步分解出直接效应、间接效应来详细地反映自变量对因变量的实际影响。所有区域自变量的变动对本区域因变量的影响称为总效应,总效应包括直接效应与间接效应。直接效应反映了本区域解释变量对本区域被解释变量的影响,间接效应反映相邻区域解释变量的变动对本区域被解释变量的影响,即空间溢出效应。本文通过 “求偏微分法” [20],利用R软件的空间面板模型程序包,计算得到空间杜宾模型下的直接效应、间接效应和总效应的具体数值见表3。

表3 全国及三大地区空间杜宾模型的效应分解 Table 3 Effect decomposition of spatial Dubin model

1) 直接效应。从直接效应来看,全国范围内城镇化水平对能耗强度的直接效应不显著,而东部和中部地区显著为正,西部地区为负但不显著,说明东部和中部地区现阶段城镇化水平的提升造成了较高的能耗代价,西部地区城镇化水平较低,对能耗强度的影响还不明显。随着经济发展,东部和中部地区的快速城镇化进程导致汽车拥有量增加、劳动力转移、大规模城市建设等,都成为促进能源消耗量增长的重要因素,同时农村经济非农化对能源消耗量的增长也起到一定的推动作用[31]

全国、东部地区经济发展对能源消耗的直接效应都显著为负,中部、西部地区直接效应不显著,全国范围经济发展水平的直接效应大于东部地区且显著为负,一定程度上说明现阶段经济发展水平的提高有利于能耗强度的降低。第二产业比重和第三产业比重对能耗强度的影响在全国及三大地区的直接效应均为正,说明第二产业比重、第三产业比重的增加会直接导致本地区能耗强度的上升,但第三产业对能耗强度的影响远小于第二产业。技术创新活动在全国和东部地区的直接效应显著为正,在中部、西部地区不显著,说明当前中国科技创新活动降低能耗强度的效应还未显现,伴随着创新活动的大量投入往往导致能源强度上升。全国与中部地区外商直接投资对能耗强度的直接效应不显著,东部地区显著为负,西部地区显著为正,说明经济较发达的东部地区引入外商直接投资的质量及技术水平较高,有利于降低能耗强度,而西部地区外商直接投资的效益有待提升。能源价格对能源强度的负向影响效应仅在东部地区显著,说明东部地区有着较合理的产业布局、多样化的能源消耗结构,随着能源成本的相对增加,企业往往寻找可替代的低能耗生产途径。

2) 间接效应。从全国范围内看,经济发展、第二产业比重、第三产业比重、外商直接投资和能源价格的间接效应均不显著,城镇化水平存在着显著的正向间接效应,技术进步存在显著的负向间接效应,总体来看这些因素的间接效应在东部、中部和西部三个地区之间表现出较大差异。

分地区来看,城镇化对能源强度的间接效应在区域之间表现出较大差异,这可能受地区经济发展及城镇化水平差异的影响;全国范围内城镇化对能源强度的间接效应显著为正,说明总体来看城镇化水平的上升有利于区域基础设施的改善,从而产生正向的空间溢出效应。空间溢出效应又称地区反馈效应,反映了直接效应通过因变量的空间相关性作用到相邻区域后又作用到本地区的现象。

3 城镇化影响能源消耗的内在机制

空间杜宾模型的实证结果表明,当前中国城镇化总体上对能源强度产生正向影响,其中间接效应显著为正,直接效应不明显,经济发展、产业结构、技术进步等因素也对能源强度产生程度不一的影响。结合城镇化的伴随效应、城镇化与主要因素的关联性,进一步解析城镇化影响能源消耗的机理及路径,发现城镇化影响能源消耗的直接效应是规模效应、技术效应、结构效应和阶段性效应的综合作用结果,内含直接和间接两条路径(图2),城镇化影响能源消耗的间接效应则主要源于区域之间的空间溢出效应。

图2 城镇化影响能源消耗的内在机制 Fig.2 Mechanism of urbanization affecting energy consumption

3.1 直接效应

城镇化影响能源消耗的直接效应包括两条路径:一是城镇化通过人口乡城迁移、促进经济增长等引致的规模效应影响能源消耗总量进而间接影响能源强度;二通过技术效应、结构效应和阶段性效应直接对能源强度产生影响,并部分经由能耗总量而间接影响能源强度。

3.1.1 规模效应

从规模上看,城镇化水平提高必然引致能源消耗总量的大幅上升,因为城镇居民人均能耗明显高于农村居民的人均能耗,已为一些实证结果所证实[16,17]。城镇化本质上是生产要素在空间上向城镇集中的过程,在这一过程中,城镇化对建筑、交通、道路等方面产生巨大的建设需求,无论是建设过程中还是建成后投入运行,都要消耗大量能源。快速城镇化推动建筑业的发展,新增大量建筑不仅导致城镇建筑总能耗持续增长,还推动水泥、钢材、玻璃等高耗能建材业的快速发展[18]。城市居民私家车的拥有量远超过农村,城镇化导致机动车拥有量增多、行驶次数与距离增加,使得交通能耗大幅度增长。城镇化作为拉动内需的重要途径,能够带动资本形成,提高生产率,推动经济增长,进而带来能源消耗总量的上升。可见,城镇化带来的规模效应使得能耗总量不断增加,进而对能源强度产生正向影响,但城镇化对能源强度的实际影响还受到经济发展规模、速度的影响,前文实证结果显示经济发展对能源强度产生显著的负向影响,正负两方面影响的综合作用导致中国城镇化进程对能源强度的直接效应不显著。

3.1.2 技术效应

城镇化为技术进步创造良好的环境,进而通过技术效应影响能源强度。城镇化的空间聚集效应促使生产要素在空间上重新配置,城市数量增加和城市规模扩张都会带来创新投入规模的扩大,有利于提升技术创新能力。城市集中了各种专业化企业和人才,形成专业化与多样性、创新网络结构、人力资本积累及交易效率提高等方面的优势,有利于技术创新的产生;城市还为技术创新的扩散创造良好条件,能够加速创新扩散[32]。所以,城镇化使得技术创新的成本更低、效率更高。另外,城镇化创造的良好投资环境使国外先进技术设备以外商直接投资的形式大量进入,推动相关行业的技术进步及经济增长。理论上,技术创新一方面有利于提高能源利用效率,降低能源消耗强度,另一方面也有利于促进经济快速增长,带动能耗总量上升从而提高能源强度[18]。当前发展阶段,中国技术创新的后一种效应更为突出,导致实证结果显示技术进步对能源强度的直接效应显著为正,即技术创新引致能源强度上升。技术创新对能源强度的间接效应显著为负,说明某一区域的技术创新有利于降低周边区域的能源强度,原因在于技术创新的非竞争性、部分排他性使其具有明显的外部性,在区域之间产生显著的空间溢出效应。

3.1.3 结构效应

与中国城镇化进程相伴随的工业特征是高耗能产业的迅速发展,第二产业发展加速和大城市不断壮大必然导致能源强度上升[33],实证分析也表明产业结构变动对能源强度产生显著正向影响。除此之外,城镇化还通过人口的城乡结构转换、居民的消费结构变动等影响能耗总量进而间接影响到能源强度。城镇化促使农村劳动力向城市转移,由于城镇居民的能源消耗水平明显高于农村居民,所以人口从农村迁往城镇必然引起生活用能增加,提高能源强度。城镇化对能源消费结构提出新的要求并产生明显影响,由于城市居民能源消费以商品能源为主,电力、天然气等优质能源所占比例较高,而农村居民以农作物的秸秆、动物的粪便等生物能、煤炭等作为主要能源[34],所以,城镇化促使居民生活用能中煤炭所占比重逐渐下降,电力、天然气等优质能源的消费比重逐渐提高,这种结构变化也影响到能源强度。另外,城镇化水平的提高引起产业组织结构、产品结构等不断调整[31],资源更合理的配置与能源使用效率的提高,有利于降低能源强度。

3.1.4 阶段性效应

由于中国东部、中部及西部的城镇化水平存在明显的梯次性差异,导致实证结果显示不同地区城镇化对能源强度的实际影响效应存在明显不同。一些文献表明,在城镇化发展的不同阶段,城镇化对能源强度产生非线性影响,两者之间可能存在着倒U型关系[28]。不同的城镇化模式对能源消耗和环境质量也产生不一样的影响,且对于不同发展阶段的国家或地区有所差异。城镇化早期,城镇化导致人口、资源、知识等要素的集聚,从而促进生产力水平的提高和快速技术进步,产业结构从以农业为主向以工业为主转变,推动能源需求大幅增加,人均能耗和能源强度快速上升;随着城镇化的进一步推进,农业生产和运输、城市生活的负外部性、居民能源消费倾向提高等因素,都导致能源强度的继续上升;城镇化进程基本完成、城镇化水平趋于饱和后,产业结构以第三产业为主,城市带动的技术创新速度加快,人均能耗增长减缓或基本稳定,能源消耗强度趋于下降。

3.2 间接效应

城镇化影响能源消耗的间接效应是指区域之间城镇化水平的空间溢出对能源消耗产生的影响。实证显示,城镇化影响能源强度的总效应中间接效应较显著,原因就在于区域之间的城镇化水平存在着空间依赖性,空间溢出效应明显。

区域城镇化之所以存在空间溢出效应,是因为伴随着城镇化发展区域间的商品流通日益频繁,区域之间不断进行着物质、人员、资金和信息的交换,这种时空上的交换即为空间相互作用。作为区域间经济或创新差异演变过程中的真实成分,城镇化的空间依赖性是区域之间要素流动、产业转移、创新扩散等效应的现实反映,是确确实实存在的空间交互影响,且随着时间变化可能呈现出不同的变动态势。空间依赖性的具体表现形式多种多样,既包括劳动力与资本流动、产业结构调整与升级等耦合形成的经济行为在空间上相互影响、相互作用,又包括科技研发与创新的投入产出行为及政策在地理空间上的示范作用和激励效应等。由于城镇化水平空间依赖性的存在,本区域的城镇化水平通过溢出效应影响到邻近区域的能源强度,本区域的能源强度也受到邻近区域城镇化水平的影响。

4 结论及启示

本文在利用空间杜宾模型探讨全国城镇化影响能源消耗实际效应的基础上,开展东部、中部、西部三大地区的对比分析,并将城镇化影响能源消耗的总效应分解为直接效应与间接效应,全面解析城镇化影响能源消耗的现实表现与理论机制。结果显示: 城镇化水平和能耗强度均存在着显著的空间自相关,当前城镇化对能源强度具有正向促进效应,但东部、中部及西部地区之间存在显著差异; 全国范围内城镇化影响能源强度的总效应中间接效应显著为正,直接效应不明显,而东部、中部及西部地区三种效应的显著性呈现出不同的特点; 城镇化影响能源消耗的显著间接效应在于城镇化水平的空间依赖性而导致区域空间溢出效应明显,不显著的直接效应则是规模效应、技术效应、结构效应和阶段性效应经由直接、间接两条路径及正向、负向两种影响综合作用的结果。

在中国能源消耗总量已居世界第一的背景下,为推动经济转型升级,加快生态文明建设,实现绿色低碳发展,上述结论具有以下政策启示:着眼于长期效应,提升城镇化质量,充分发挥城镇化对能源效率的促进作用。当前中国快速城镇化并未带来能源强度的下降,而城镇居民人均能耗高于农村居民人均能耗,使得能源消耗总量大幅上升,但不能因此而否定积极的城镇化战略;长期来看城镇化带来的技术效应、结构效应等将逐步显现,并促进能源效率的提高,问题的关键在于切实提高城镇化质量,加快产业优化升级,发挥城镇化培育技术创新的优势,使城镇化对能源效率的正向促进效应得以充分显现。 不同地区应结合本地实际采取差异城镇化战略,强化区域合作,提高能源效率。实证显示,中国城镇化对能源消耗的影响效应存在着明显的地区差异,区域之间的空间溢出效应使城镇化对能源消耗的间接效应突出。故而,面对较强能源约束的东部地区应优化城镇空间结构,提高城市产业层次与创新能力,逐步发挥城镇化对能源效率的提升效应;西部地区大力提高城镇化水平时,需考虑到城镇的吸纳能力和承载力,避免大规模“造城运动”而导致的“鬼城”、“空城”;另外,地方城镇化及能源政策的制定,要重视地理空间因素的作用,通过统筹区域规划、优势资源互补、基础设施共享等方式加强区域间的协同合作,以充分利用空间溢出效应,优化能源空间配置,提高能源效率。

尽管本文利用空间杜宾模型进行分析,弥补了以往研究中忽略区域之间空间相关性的不足,并结合实证结果开展了城镇化影响能源消耗内在机制的解析,但实证分析中未能考虑城镇化对能源强度的非线性影响,城镇化影响能源消耗的规模效应、结构效应、技术效应和阶段性效应也需要更充分的实证支持,这些都有待于后续的进一步研究。

The authors have declared that no competing interests exist.

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As a key issue in China's economic development, urbanisation creates increasing pressure on energy supply and the natural environment. Thus, a better understanding of the relationship between urbanisation and energy consumption is necessary for Chinese decision makers at various levels to address energy security and sustainable economic and social development. This paper empirically investigates the effects of China's urbanisation on residential energy consumption (REC) and production energy consumption (PEC) through a time-series analysis. The results show that compared with rural areas, urbanisation slows per capita REC growth because of the economy of scale and technological advantages associated with urbanisation but has greater promotional effects on the growth of REC and the improvement of REC structure. The economic growth caused by urbanisation most significantly contributes to an increase in PEC, whereas technological advancement was found to reduce the scale of PEC (except from 2001 to 2005). Finally, the structural effect of the energy supply increased rather than decreased China's PEC, and the effect of industrial structure adjustment on PEC was found to be insignificant.
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随着城镇化的大力推进,中国城镇化、工业化与能源消费之间的相互关系已经发生新的变化.而目前对城镇化与能源消费之间关系的研究尚存在一些不足:①没有考虑工业化对能源消费的影响,过高估计了城镇化的作用;②没有考虑区域发展阶段和发展模式的差异,正是由于这种差异导致不同区域的城镇化、工业化和能源消费之间关系呈现的不同特征;③从中国的实际情况出发,实证方法尚需要进一步完善.基于此,本文构建了固定效应面板模型,估计了反映不同区域能源消费水平长期趋势的均衡方程.结果显示,在全国层面,中国城镇化、工业化对能源消费的净效应为正,并且城镇化的影响作用更加明显.分区域情况来看,东部、中部、西部地区城镇化对能源消费的净效应为正.其中,中部地区影响程度最大.这意味着中部地区城镇化转型面临的能源消费压力最大.据此表明中国在城镇化进程中,降低能源消费强度,缓解能源消费压力,需要注意以下两个问题:①新型城镇化要考虑城市的规模效益;②要充分考虑地区发展的差异,制定差别化的政策.
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As urbanization accelerates, urban areas play a leading role in energy consumption and CO 2 emissions in China. The existing research is extensively concerned with the relationships between urbanization, energy consumption and CO 2 emissions in recent years, but little attention has been paid to the regional differences. This paper is an analysis of the impact of urbanization on energy consumption and CO 2 emissions at the national and regional levels using the STIRPAT model and provincial panel data from 1995 to 2010 in China. The results showed that urbanization increases energy consumption and CO 2 emissions in China. The effects of urbanization on energy consumption vary across regions and decline continuously from the western region to the central and eastern regions. The impact of urbanization on CO 2 emissions in the central region is greater than that in the eastern region. The impact of urbanization on energy consumption is greater than the impact on CO 2 emissions in the eastern region. And some evidences support the argument of compact city theory. These results not only contribute to advancing the existing literature, but also merit particular attention from policy makers and urban planners in China.
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通过利用2000-2009年我国的省级面板数据,建立时间和空间双固定效应的面板空间杜宾模型,发现我国存在一条U形的城市化能耗库兹涅茨曲线,该曲线的转折点出现在城市化率约为24%的阶段。现阶段我国的城市化水平已经处在该曲线的右侧部分,表明如果我国的城市化率在今后仍不断提高的话,由城市化所导致的能耗将迅速增长。同时还发现城市化在我国能耗增长中的贡献比重较大,但对于在2003年出现的我国能耗迅速增加的拐点,从城市化的角度找不到解释。最后提出如果今后我国城市化率进一步提高,由能耗迅速增加所导致的城市发展的离心力达到一定程度,将会对我国的城市化格局产生重要的影响。
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