中国城镇居民生活能源消费影响因素及其效应分析——基于八区域的静态面板数据模型

doi:10.18402/resci.2016.12.09

摘要/Abstract

摘要：

探究城镇居民生活能源消费的影响因素可为引导城镇居民生活能源合理消费提供依据。本文以中国八大区域为研究对象,建立静态面板数据模型挖掘2000-2013年节能政策、居民实际消费支出、能源价格对城镇居民生活能耗的影响。研究结果显示：城镇居民生活能耗与居民实际消费支出、能源价格、节能政策之间存在长期协整关系;能源价格对城镇居民生活能耗的影响最大,且具有显著负向作用,而实际消费支出对生活能耗具有显著正向作用,但城镇居民生活能源消费增长速度小于实际消费支出增长速度;节能政策的滞后期为2年,即政策颁布2年后对生活能耗具有一定抑制作用但该作用较小;由于经济发展水平及环境气候引起的居民取暖制冷需求的不同,节能政策、实际消费支出、能源价格对于生活能耗的影响呈现出显著的空间差异。由此建议：应通过调整居民实际消费支出结构、适当提高能源价格、加强节能政策的宣传与执行等方式降低生活能耗。

关键词: 城镇生活能源消费, 消费支出, 能源价格, 节能政策, 静态面板数据模型, 中国

Abstract:

Exploring the factors that influence urban household energy consumption provides a basis for the reasonable energy consumption of urban residents in China. Based on eight regions in China （Beijing-Tianjin region,northeast region,northern coastal region,southern coastal region,eastern coastal region,central region,southwest region,northwest region）we establish a static panel data model to analyze the impact of actual consumption expenditure,energy price and energy saving policy on the energy consumption of urban residents from 2000 to 2013. We found a long-term cointegration relationship between urban household energy consumption and actual consumption,energy prices and energy saving policy. Energy price has the greatest negative effect on the energy consumption of urban residents. Actual consumption expenditure has a significant positive effect on household energy consumption,and its growth rate is greater than urban household energy consumption. The lag period of energy saving policy is two years,in other words,energy saving policy has a certain effect on household energy consumption after two years but the effect is small. Due to the level of economic development,household energy is mainly used in heating and cooling （climate becomes a key factor influencing residential energy consumption）and the effects of energy saving policy,actual consumption expenditure and energy price on household energy consumption show spatial differences. Since the level of economic development and energy saving policy both play an important role in household energy consumption,we should reduce urban household energy consumption by adjusting the structure of household consumption expenditure,increasing the price of energy,and strengthening advocacy and implementation of energy saving policy.

Key words: urban household energy consumption, consumption expenditure, energy price, policy, static panel data model, China

刘满芝, 刘贤贤. 中国城镇居民生活能源消费影响因素及其效应分析——基于八区域的静态面板数据模型[J]. 资源科学, 2016, 38(12): 2295-2306.

LIU Manzhi,LIU Xianxian. Factors affecting Chinese urban household energy consumption and spatial differences based on static panel data modelling for eight regions[J]. Resources Science, 2016, 38(12): 2295-2306.

图/表 7

表1

2000-2013年中国居民领域重大节能政策[47]"

年份	政策	颁布机构	与居民节能相关的内容
2003	该年份起每年开展“全国节能宣传周”活动	国家发展和改革委员会	开展“全国节能宣传周”活动,宣传节能新技术、新产品的开发成果,普及节能知识,提高全社会节能意识
2004	《节能中长期专项规划》	国家发展和改革委员会	“十大重点节能工程”中提出新建建筑严格实施节能,供热体制改革全面展开,开展既有居住和公共建筑节能改造以及家用及办公电器、照明器具等方面的节能政策
2006	《“十一五”十大重点节能工程实施意见》	科技部、财政部、建设部、国家质检总局、国家环保总局等	“十大重点节能工程”中建筑节能工程和绿色照明工程对居民节能提出了详细要求
2007	《关于印发节能减排全民行动实施方案的通知》	国家发展和改革委员会	通过重塑家庭生活消费新模式、搭建节能减排社区平台、“简约生活”宣讲活动、设立“节能减排家庭、社区行动”网页等形式开展“节能减排家庭社区行动”
2009	《关于开展“节能产品惠民工程”的通知》	财政部、国家发展与改革委员会	对高效节能和新能源产品给予财政补贴,推广“节能产品惠民工程”高效节能房间空调
2012	《节能产品惠民工程高效节能电动洗衣机推广目录》、《节能产品惠民工程高效太阳能热水器推广目录》等	国家发展与改革委员会、财政部、工业和信息化部	为开展“节能产品惠民工程”,中央财政安排363亿元补贴推广节能空调、节能家电、高效照明、节能汽车和高效电机
2013	《关于2013年全国节能宣传周和全国低碳日活动安排的通知》	国家发展与改革委员会	每年开展“全国低碳日活动”,促进全民在生活中节能减排

表1

表2

表3

面板数据协整检验结果"

检验方法	检验假设	统计量名	统计量值（P值）
Kao检验	$H 0$ ：不存在协整关系 $(ρ = 1)$	ADF	-5.071*** （0.000）
Pedroni检验	$H 0 ： ρ i = 1$ $H 1 ： (ρ i = ρ) < 1$	Panel PP	-7.043*** （0.000）
	$H 0 ： ρ i = 1$ $H 1 ： (ρ i = ρ) < 1$	Panel ADF	-6.515*** （0.000）
	$H 0 ： ρ i = 1$ $H 1 ： ρ i < 1$	Group PP	-8.768*** （0.000）
	$H 0 ： ρ i = 1$ $H 1 ： ρ i < 1$	Group ADF	-8.207*** （0.000）

表3

表4

中国各区域固定影响变系数模型估计结果"

区域	$α i$ 的估计值	$β 1 i$ 的估计值	$β 2 i$ 的估计值	$β 5 i$ 的估计值
京津	-0.476	0.241（3.148）***	-0.769（-4.095）***	-0.057（-2.174）**
东北	0.686	0.156（1.737）*	-0.277（-10.769）***	-0.048（-1.715）*
北部沿海	0.106	0.232（3.534）***	-0.735（-5.103）***	-0.059（-1.421）
东部沿海	-0.668	0.604（9.247）***	-0.308（-2.063）**	-0.022（-1.120）
南部沿海	0.400	0.341（5.295）***	-0.499（-3.650）***	-0.062（-2.078）**
中部	0.496	0.705（7.842）***	-0.052（-0.889）	-0.025（-0.754）
西北	-0.439	-0.332（-1.772）*	-1.665（-2.393）**	-0.034（-1.745）*
西南	-0.105	-0.021（-0.309）	-1.218（-10.359）***	-0.094（-2.391）**

表4

图1

Figure 2

图3

参考文献 49

[39]	Kao C.Spurious regression and residual-based tests for coin-tegration in panel data[J]. Journal of Econometrics,1999,90(1):1-44.
[40]	国家信息中心. 中国区域间投入产出表[M]. 北京:社会科学文献出版社,2005.
	[The State Information Center. China Regional Input-Output Table[M]. Beijing:Social Science Literature Press,2005.]
[41]	中华人民共和国国家统计局. 中国能源统计年鉴(2001-2014)[M].北京:中国统计出版社,2002-2015.
	[National Bureau of Statistics of China. China Energy Statistics Yearbook(2001-2014)[M]. Beijing:China Statistics Press,2002-2015.]
[42]	中华人民共和国国家统计局. 中国统计年鉴(2001-2014)[M].北京:中国统计出版社,2002-2015.
	[National Bureau of Statistics of China. China Statistics Yearbook(2001-2014)[M]. Beijing:China Statistics Press,2002-2015.]
[43]	国家发展和改革委员会. 综合能耗计算通则(GB/T2589-2008)[EB/OL].(2008-06-01)[2016-07-07].
	[National Development and Reform Com-mission. General Principles for Calculation of the Comprehensive Energy Consumption(GB/T2589-2008)[EB/OL].(2008-06-01)[2016-07-07].
[44]	张欢,成金华. 中国能源价格上涨对居民消费水平的影响-基于SVAR模型的研究[J]. 经济经纬,2011,(4):25-29.
	[Zhang H,Cheng J H.The effect of Chinese energy price increase on resident consumption level -a research based on the SVAR model[J]. Economic Survey,2011,(4):25-29.]
[45]	贺刚. 能源消费、能源价格与经济增长-基于能源消费大国的经验数据分析[J]. 价格理论与实践,2008,(12):45-46.
	[He G.Energy consumption,energy prices and economic growth-based on analysis of empirical data of energy consumption[J]. Price Theory and Practice Analysis of Empirical Data of Energy Con-sumption,2008,(12):45-46.]
[46]	江凌. 我国生活能源消费影响因素的区域比较及政策引导[D]. 大连:大连理工大学,2014.
	[Jiang L.China's Energy Consum-ption Influence Factors of Regional Comparison and Policy Guidance[D]. Dalian:Dalian University of Technology,2014.]
[47]	杨树. 中国城市居民节能行为及节能消费激励政策影响研究[D]. 合肥:中国科学技术大学,2015.
	[Yang S.Chinese Energy Saving Behavior of City Residents and Energy Consumption Incentives Research[D]. Hefei:University of Science & Tech-nology China,2015.]
[48]	王红兵,成金华. 中国财政政策对能源消费影响的动态效应分析[J]. 中国人口·资源与环境,2008,18(3):156-162.
[1]	彭希哲,朱勤. 我国人口态势与消费模式对碳排放的影响分析[J]. 人口研究,2010,(1):48-58.
	[Peng X Z,Zhu Q.Impacts of population dynamics and consumption pattern on carbon emission in China[J]. Population Effect on Carbon Emissions,2010,(1):48-58.]
[48]	[Wang H B,Cheng J H.Analysis of the dynamic effects of China's fiscal policy on energy consumption[J]. China's Population Resources and Environment,2008,18(3):156-162.]
[49]	林伯强,牟敦国. 能源价格对宏观经济的影响-基于可计算一般均衡价格(CGE)的分析[J]. 经济研究,2008,(11):88-101.
[2]	Joyeux R,Ripple R D.Household energy consumption versus income and relative standard of living:A panel approach[J]. Energy Policy,2007,35(1):50-60.
[3]	中华人民共和国国家统计局. 统计数据-年度数据[EB/OL]. (2016-01)[2016-07-07].
	[National Bureau of Statistics of China. Statistics Data-Year Data [EB/OL].(2016-01)[2016-07-07].
[4]	Yildirim E,Saraç Ş,Aslan A.Energy consumption and economic growth in the USA:Evidence from renewable energy[J]. Renewable and Sustainable Energy Reviews,2012,16(9):6770-6774.
[5]	Streimikiene D,Kasperowicz R.Review of economic growth and energy consumption:A panel cointegration analysis for EU countries[J]. Renewable and Sustainable Energy Reviews,2016,59:1545-1549.
[6]	张伟,张金锁,袁显平. 工业化、经济增长与能源消费-基于中国分省面板数据的实证分析[J]. 统计与信息论坛,2012,27(1):60-66.
	[Zhang W,Zhang J S,Yuan X P.The industrialization,energy consumption and economic growth-an empirical analysis based on provincial panel data Chinese[J]. Statistics and Information Forum,2012,27(1):60-66.]
[7]	罗光华,牛叔文. 气候变化、收入增长和能源消耗之间的关联分析-基于面板数据的省际居民生活能源消耗实证研究[J]. 干旱区资源与环境,2012,26(2):20-24.
	[Luo G H,Nu S W.The relationship between energy consumption,income growth and climate change-based on the inter-provincial panel data of resi-dential energy consumption[J]. Panel Data of Provincial Residents Living Energy,2012,26(2):20-24.]
[8]	纪广月. 基于面板数据模型的人口城镇化与能源消费关系的实证研究[J]. 数学的实践与认识,2014,(16):97-102.
	[Ji G Y.An empirical study of population urbanization and energy con-sumption based on panel data model[J]. Mathematics in Practice & Theory,2014,(16):97-102.]
[9]	Al-mulali U,Fereidouni H G,Lee J Y M,et al. Exploring the relationship between urbanization,energy consumption,and CO2 emission in MENA countries[J]. Renewable and Sustainable Energy Reviews,2013,23(4):107-112.
[10]	Sun C,Ouyang X,Cai H,et al. Household pathway selection of energy consumption during urbanization process in China[J]. Energy Conversion and Management,2014,84:295-304.
[11]	Zhou K,Yang S.Understanding household energy consumption behavior:The contribution of energy big data analytics[J]. Renew-able and Sustainable Energy Reviews,2016,56(4):810-819.
[12]	Chatterton T J,Anable J,Barnes J,et al. Mapping household direct energy consumption in the United Kingdom to provide a new perspective on energy justice[J]. Energy Research & Social Science,2016,18(8):71-87.
[13]	Ren Z,Chan W Y,Wang X,et al. An integrated approach to modelling end-use energy and water consumption of Australian households[J]. Sustainable Cities and Society,2016,26:344-353.
[14]	Bin S,Dowlatabadi H.Consumer lifestyle approach to US energy use and the related CO2 emissions[J]. Energy Policy,2005,33(2):197-208.
[15]	Yun G Y,Steemers K.Behavioural,physical and socio-economic factors in household cooling energy consumption[J]. Applied Energy,2011,88(6):2191-2200.
[16]	Du G,Sun C W,Fang Z N.Evaluating the Atkinson index of household energy consumption in China[J]. Renewable and Sustainable Energy Reviews,2015,51(11):1080-1087.
[17]	Kelly S.Do homes that are more energy efficient consume less energy? A structural equation model of the English residential sector[J]. Energy,2011,36(9):5610-5620.
[18]	Black J S,Stern P C,Elworth J T.Personal and contextual influences on household energy adaptations[J]. Journal of Applied Psychology,1985,70(1):3-21.
[19]	贺仁飞,牛叔文,贾艳琴,等. 人均生活能源消费、收入和碳排放的面板数据分析[J]. 资源科学,2012,34(6):1142-1151.
	[He R F,Nu S W,Jia Y Q,et al. Panel data analysis of per capita household energy consumption,income and carbon emissions[J]. Resources Science,2012,34(6):1142-1151.]
[20]	王文蝶,牛叔文,齐敬辉,等. 中国城镇化进程中生活能源消费与收入的关联及其空间差异分析[J]. 资源科学,2014,36(7):1434-1441.
	[Wang W D,Nu S W,Qi J H,et al. The correlation and spatial differences between residential energy consumption and income in China[J]. Resources Science,2014,36(7):1434-1441.]
[21]	陈迅,袁海蔚. 中国生活能源消费行为影响因素的实证研究[J]. 消费经济,2008,(5):47-50.
	[Chen X,Yuan H Y.An empirical study on the influencing factors of China's energy consumption behavior[J]. Consumer Economy,2008,(5):47-50.]
[22]	Nesbakken R.Price sensitivity of residential energy consumption in Norway[J]. Energy Economics,1999,21(6):493-515.
[23]	Lopes L,Hokoi S,Miura H,et al. Energy efficiency and energy savings in Japanese residential buildings-research methodology and surveyed results[J]. Energy and Buildings,2005,37(7):698-706.
[24]	Wu X,Lampietti J,Meyer A S.Coping with the cold:Space heating and the urban poor in developing countries[J]. Energy Economics,2004,26(3):345-357.
[25]	张志柏. 中国能源消费因果关系分析[J]. 财贸研究,2008,19(3):15-21.
	[Zhang Z B.Causal analysis of Chinese energy consumption[J]. Chinese Research,2008,19(3):15-21.]
[26]	Anker-Nilssen P.Household energy use and the environment-a conflicting issue[J]. Applied Energy,2003,76(1):189-196.
[27]	Abrahamse W,Steg L,Vlek C,et al. A review of intervention studies aimed at household energy conservation[J]. Journal of Environmental Psychology,2005,25(3):273-291.
[28]	Steg L.Promoting household energy conservation[J]. Energy Policy,2008,36(12):4449-4453.
[29]	Yu B,Tian Y,Zhang J.A dynamic active energy demand management system for evaluating the effect of policy scheme on household energy consumption behavior[J]. Energy,2015,91(11):491-506.
[30]	郭琪,樊丽明. 城市家庭节能措施选择偏好的联合分析-对山东省济南市居民的抽样调查[J]. 中国人口·资源与环境,2007,17(3):149-153.
	[Guo Q,Fan L M.Analysis of joint energy saving measures of city family preferences on a sample survey in Shandong province Ji'nan city residents[J]. Chinese,Population Resources and Environment,2007,17(3):149-153.]
[31]	焦有梅,白慧仁,蔡飞. 山西城乡居民生活节能潜力与途径分析[J]. 山西能源与节能,2009,(2):61-63.
	[Jiao Y M,Bai H R,Cai F.Shanxi urban and rural residents and ways of energy saving potential of energy and energy saving analysis[J]. Shanxi Energy and Conservation,2009,(2):61-63.]
[32]	姜百臣. 消费需求系统模型的理论约束与实证应用探讨[J]. 经济评论,2007,(6):93-96.
	[Jang B C.Discussion on the theory and empirical application of constrained consumer demand sys-tem model[J]. Economic Review,2007,(6):93-96.]
[33]	Cameron T.A nested logit model of energy conservation activities by owners of existing single family dwellings[J]. Review of Eco-nomies and Statistics,1985,6(2):205-211.
[34]	郭琪. 公众节能行为的经济分析及政策研究[D]. 济南:山东大学,2007.
	[Guo Q.Economic Analysis and Policy Research on the Behavior of Public Energy Conservation[D]. Ji'nan:Shandong University,2007.]
[35]	Bertrand M,Karlan D,Mullainathan S,et al. What’s advertising content worth? Evidence from a consumer credit marketing field experiment[J]. The Quarterly Journal of Economics,2010,125(1):263-306.
[36]	芈凌云. 城市居民低碳化能源消费行为及政策引导研究[D]. 徐州:中国矿业大学,2011.
	[Mi L Y.Energy Consumption Behavior and Low-Carbon City Residents to Guide Policy Research[D]. Xuzhou:China University of Mining and Technology,2011.]
[37]	高铁梅. 计量经济分析方法与建模-EViews应用及实例(第二版)[M]. 北京:清华大学出版社,2009.
	[Gao T M.Application of Econometric Methods and Examples and Modeling of an EViews (Second Edition)[M]. Beijing:Tsinghua University press,2009.]
[38]	Pedroni P.Critical values for cointegration tests in heterogeneous panels with multiple regressors[J]. Oxford Bulletin of Economics and Statistics,1999,61(S1):653-678.
[49]	[Lin B Q,Mou D G.The impact of energy price increases on macro-economy:An analyses based on CGE method[J]. Economic Research,2008,(11):88-101.]

统计量	LUEC		LUC		LPR
统计量	水平值	一阶差分	水平值	一阶差分	水平值	一阶差分
LLC	-2.217** （0.013）	-7.435*** （0.000）	-1.579* （0.057）	-5.719*** （0.000）	1.550 （0.939）	-8.936***（0.000）
IPS	-1.234 （0.109）	-5.079*** （0.000）	0.240 （0.595）	-3.168*** （0.001）	1.648 （0.950）	-4.196*** （0.000）
Fisher-ADF	25.588* （0.060）	50.444*** （0.000）	12.018 （0.743）	36.345*** （0.003）	6.679 （0.979）	43.363*** （0.000）
Fisher-PP	31.405** （0.012）	58.695*** （0.000）	8.462 （0.934）	51.318*** （0.000）	6.769 （0.978）	67.356*** （0.000）