人口结构与家庭规模对生活能源消费的影响——基于中国省级面板数据的实证研究
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摘要
文章基于中国1995～2015年省级面板数据,研究人均生活能源消费量的空间差异与动态变化,探索人口结构与家庭规模对生活能源消费量的影响。研究发现,各省份人均生活能源消费量整体呈递增趋势,在2005～2015年间,黑龙江、海南和重庆的人均生活用能增长率位居全国前三。实证研究结果显示:城镇人口比重与人均生活能耗之间呈"U"型关系,即城镇化早期可抑制生活能源消费,但随着城镇化的推进,人均生活能耗将逐渐提高;人口老龄化与家庭规模小型化均会显著增加人均生活用能。在积极应对气候变化与满足人民日益增长的美好生活需要的双重目标导向下,除了切实贯彻节能减排措施之外,更应强调改善能源结构、提升能源使用效率和推广清洁能源的使用。
Drawing upon provincial data between 1995 and 2015 in China, this study presents the regional distributions and dynamic changes of residential energy consumption per capita, and also investigates the impacts of population structure and household size on residential energy consumption. Residential energy consumption per capita is on a rising trend across China, and the annual growth rates in Heilongjiang, Hainan, and Chongqing provinces between 2005 and 2015 top the list. Empirical analyses reveal that there is a U-shaped correlation between urbanization and residential energy consumption, and moreover, population aging and the shrinkage of household size lead to the increased energy consumption. In order to achieve the dual targets of combating climate change and meeting the rising demand for prosperous life, China should further promote energy reservation, and more importantly, improve the energy consumption structure and expand the utilization of clean energy.
Drawing upon provincial data between 1995 and 2015 in China, this study presents the regional distributions and dynamic changes of residential energy consumption per capita, and also investigates the impacts of population structure and household size on residential energy consumption. Residential energy consumption per capita is on a rising trend across China, and the annual growth rates in Heilongjiang, Hainan, and Chongqing provinces between 2005 and 2015 top the list. Empirical analyses reveal that there is a U-shaped correlation between urbanization and residential energy consumption, and moreover, population aging and the shrinkage of household size lead to the increased energy consumption. In order to achieve the dual targets of combating climate change and meeting the rising demand for prosperous life, China should further promote energy reservation, and more importantly, improve the energy consumption structure and expand the utilization of clean energy.
引文
1 傅崇辉, 王文军, 曾序春, 张玲华, 雷光和. 生活能源消费的人口敏感性分析——以中国城镇家庭户为例. 资源科学, 2013; 10: 1933-1944Fu Chonghui, Wang Wenjun, Zeng Xuchun, Zhang Linghua and Lei Guanghe. 2013. Population Sensitivity of Residential Energy Consumption: The Case of China’s Urban Households. Resources Science 10: 1933-1944.
2 郭志刚. 清醒认识中国低生育率风险.国际经济评论, 2015; 2:100-119Guo Zhigang. 2015. A Clear Understanding of China’s Low Fertility Risk. International Economic Review 2:100-119.
3 贺仁飞,牛叔文,贾艳琴,张馨,丁永霞.人均生活能源消费、收入和碳排放的面板数据分析.资源科学, 2012;6: 1142-1151He Renfei, Niu Shuwen, Jia Yanqin, Zhang Xin and Ding Yongxia. 2012. Panel Data Analysis of Per Capita Household Energy Consumption. Income and Carbon Emissions. Resources Science 6: 1142-1151.
4 胡湛, 彭希哲. 中国当代家庭户变动的趋势分析——基于人口普查数据的考察. 社会学研究, 2014; 3: 145-166Hu Zhan and Peng Xizhe. 2014. Analysis of the Trend of Changes in Contemporary Households in China:Based on the Data of Population Census. Sociological Studies 3: 145-166.
5 蒋耒文. 人口变动对气候变化的影响. 人口研究,2010; 1: 59-69Jiang Leiwen. 2010. The Impacts of Demographic Dynamics on Climate Change. Population Research 1: 59-69.
6 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. 资源科学, 2016; 12: 2295-2306Liu Manzhi and Liu Xianxian. 2016. Analysis on the Influencing Factors and Effects of Residential Energy Consumption in Urban China:A Static Panel Data Model Based on Eight Areas. Resources Science 12: 2295-2306.
7 陆慧, 卢黎. 农民收入水平对农村家庭能源消费结构影响的实证分析. 财贸研究, 2006; 3: 28-34Lu Hui and Lu Li. 2006. An Empirical Analysis of the Influence of Farmers’ Income Level on Rural Household Energy Consumption Structure. Finance and Trade Research 3: 28-34.
8 仇焕广, 严健标, 李登旺, 韩炜. 我国农村生活能源消费现状、发展趋势及决定因素分析——基于四省两期调研的实证研究. 中国软科学, 2015; 11: 28-38Qiu Huanguang, Yan Jianbiao, Li Dengwang and Han Wei. 2015. Analysis of the Current Situation, Development Trends, and Determinants of China’s Rural Residential Energy Consumption: An Empirical Study based on Two Phases of Research in Four Provinces. China Soft Science 11: 28-38.
9 任正委, 米红. 区域人口城镇化多维特征对居民电力消费的驱动影响——基于浙江省分县数据的实证研究. 人口研究, 2016; 4: 103-112Ren Zhengwei and Mi Hong. 2016. Multiple Dimensions of Urbanization and Residential Electricity Consumption: A County-level Study in Zhejiang Province. Population Research 4: 103-112.
10 沈小波. 中国农村居民电力需求的影响因素. 统计研究, 2014; 1: 84-90Shen Xiaobo. 2014. Factors Affecting Rural Residents’ Electricity Demand in China.Statistical Research 1: 84-90.
11 王芳, 周兴. 人口结构、城镇化与碳排放——基于跨国面板数据的实证研究. 中国人口科学, 2012; 2: 47-56Wang Fang and Zhou Xing. 2012. Population Structure, Urbanization, and Carbon Emissions: An Empirical Study Based on Multinational Panel Data. Chinese Journal of Population Science 2: 47-56.
12 王文蝶, 牛叔文, 齐敬辉, 丁永霞, 李娜. 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. 资源科学, 2014; 7: 1434-1441Wang Wendie, Niu Shuwen, Qi Jinghui, Ding Yongxia and Li Na. 2014. The Correlation and Spatial Differences between Residential Energy Consumption and Income in the Process of Urbanization in China. Resources Science 7: 1434-1441.
13 张妮妮, 徐卫军. 农户生活用电消费分析——基于能源自选择行为. 中国农村经济, 2011;7: 72-84Zhang Nini and Xu Weijun.2011. Analysis of Rural Household Electricity Consumption: Based on Energy Self-selection Behavior. Chinese Rural Economy 7: 72-84.
14 张妮妮, 徐卫军, 曹鹏宇. 影响农户生活能源消费的因素分析——基于9省的微观数据. 中国人口科学, 2011; 3: 73-82Zhang Nini, Xu Weijun and Cao Pengyu. 2011. Analysis of Factors Influencing Rural Residential Energy Consumption: Based on Microdata of Nine Provinces. Chinese Journal of Population Science 3: 73-82.
15 郑新业等. 中国家庭能源消费研究报告2014. 北京: 科学出版社, 2015: 103-104Zheng Xinye et al. 2015. Chinese Household Energy Consumption Report:The 2014 Revision. Beijing: Science Press: 103-104.
16 周晖, 钮文洁, 纪洪. 各种因素影响下的居民夏季用电状况分析. 华北电力技术, 2003; 3: 12-14, 21Zhou Hui,Niu Wenjie and Ji Hong. 2003. Influence of Various Factors on Residents’ Electricity Consumption in Summer. North China Electric Power 3: 12-14, 21.
17 Brockett, D., Fridley, D., Lin, J.M. and Lin, J. 2002. A Tale of Five Cities: The China Residential Energy Consumption Survey. ACEEE Summer Study on Building Energy Efficiency: 29-40.
18 Druckman, A. and Jackson, T. 2008. Household Energy Consumption in the UK: A Highly Geographically and Socio-economically Disaggregated Model. Energy Policy 8: 3177-3192.
19 Fan, J.L., Zhang, Y.J. and Wang, B. 2017.The Impact of Urbanization on Residential Energy Consumption in China: An Aggregated and Disaggregated Analysis. Renewable and Sustainable Energy Reviews 75: 220-233.
20 Jiang, L. and O’Neill, B.C. 2004. The Energy Transition in Rural China. International Journal of Global Energy Issues 21: 2-26.
21 O’Neill, B.C. and Chen, B.S. 2002. Demographic Determinants of Household Energy Use in the United States. Population and Development Review 28: 53-88.
22 Pachauri, S. and Jiang, L. 2008. The Household Energy Transition in India and China. Energy Policy 11: 4022-4035.
23 Poumanyvong, P. and Kaneko, S. 2010. Does Urbanization Lead to Less Energy Use and Lower CO2 Emissions? A Cross-country Analysis. Ecological Economics 2: 434-444.
24 Prskawetz, P., Jiang, L. and O’Neill, B.C. 2004.Demographic Composition and Projections of Car Use in Austria. Vienna Yearbook of Population Research 2: 175-201.
25 United Nations. Department of Economic and Social Affairs. Population Division. 2015. World Population Prospects: The 2015 Revision.
26 Wang, X.H. and Feng, Z.M. 2001. Rural Household Energy Consumption with the Economic Development in China: Stages and Characteristic Indices. Energy Policy 15: 1391-1397.
27 Yamasaki, E. and Tominaga, N. 1997. Evolution of an Aging Society and Effect on Residential Energy Demand. Energy Policy 11: 903-912.
(1)IEA官网数据库,https://www.iea.org/energyaccess/database/。
(2)中国国家统计局的能源消费数据以“千克标准煤(kgce)”为单位计算,统计总量为“能源消费总量”,其中包含终端能源消费量、能源加工转换损失量和损失量。国际能源署的数据以“千克油当量(ktoe)”为单位,统计总量为“终端能源消费量”。因此,两者估计的生活能源消费占比略有出入。
(3)历年《中国人口统计年鉴》和《中国人口和就业统计年鉴》。
(4)其中,广西1995～2011年的数据和海南、福建的数据直接来自统计年鉴中的“人均生活用能”;浙江省的数据来源于各年份的《浙江省能源与利用状况》白皮书。能源消费量中不包括低热值能源、生物质能和太阳能的使用,或只包含这些能源作为商品能源使用的部分。
(5)考虑到“老年人口比重”与“少年人口比重”具有较强的多重共线性,本文只纳入“老年人口比重”这一变量。
(6)本文根据东、中、西部经济带划分省市,将北京、天津等11个省市列为东部地区,黑龙江、吉林等8个省市列为中部地区,内蒙古、广西等10个省市列为西部地区。我国以“秦岭、淮河为界”确定北方为集中供暖区域(郑新业等,2015),个别省市地跨“秦岭-淮河”一线,本文根据地理位置和实际供暖情况,将北京、天津、河北、山西、内蒙古、辽宁、吉林、黑龙江、山东、河南、陕西、甘肃、青海、新疆等14个省市划入北方地区,将上海、江苏、浙江、安徽、福建、江西、湖北、湖南、广东、广西、海南、重庆、四川、贵州、云南等15个省市划入南方地区。
(7)http://shupeidian.bjx.com.cn/news/20171113/861210.shtml。
(8)二次函数的顶点横坐标为-(-8.94)/(2*0.10)=44.7%。
(9)日本总务省统计局官网,http://www.stat.go.jp/data/nihon/02.html;韩国统计信息服务网,http://kosis.kr/eng/。
2 郭志刚. 清醒认识中国低生育率风险.国际经济评论, 2015; 2:100-119Guo Zhigang. 2015. A Clear Understanding of China’s Low Fertility Risk. International Economic Review 2:100-119.
3 贺仁飞,牛叔文,贾艳琴,张馨,丁永霞.人均生活能源消费、收入和碳排放的面板数据分析.资源科学, 2012;6: 1142-1151He Renfei, Niu Shuwen, Jia Yanqin, Zhang Xin and Ding Yongxia. 2012. Panel Data Analysis of Per Capita Household Energy Consumption. Income and Carbon Emissions. Resources Science 6: 1142-1151.
4 胡湛, 彭希哲. 中国当代家庭户变动的趋势分析——基于人口普查数据的考察. 社会学研究, 2014; 3: 145-166Hu Zhan and Peng Xizhe. 2014. Analysis of the Trend of Changes in Contemporary Households in China:Based on the Data of Population Census. Sociological Studies 3: 145-166.
5 蒋耒文. 人口变动对气候变化的影响. 人口研究,2010; 1: 59-69Jiang Leiwen. 2010. The Impacts of Demographic Dynamics on Climate Change. Population Research 1: 59-69.
6 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. 资源科学, 2016; 12: 2295-2306Liu Manzhi and Liu Xianxian. 2016. Analysis on the Influencing Factors and Effects of Residential Energy Consumption in Urban China:A Static Panel Data Model Based on Eight Areas. Resources Science 12: 2295-2306.
7 陆慧, 卢黎. 农民收入水平对农村家庭能源消费结构影响的实证分析. 财贸研究, 2006; 3: 28-34Lu Hui and Lu Li. 2006. An Empirical Analysis of the Influence of Farmers’ Income Level on Rural Household Energy Consumption Structure. Finance and Trade Research 3: 28-34.
8 仇焕广, 严健标, 李登旺, 韩炜. 我国农村生活能源消费现状、发展趋势及决定因素分析——基于四省两期调研的实证研究. 中国软科学, 2015; 11: 28-38Qiu Huanguang, Yan Jianbiao, Li Dengwang and Han Wei. 2015. Analysis of the Current Situation, Development Trends, and Determinants of China’s Rural Residential Energy Consumption: An Empirical Study based on Two Phases of Research in Four Provinces. China Soft Science 11: 28-38.
9 任正委, 米红. 区域人口城镇化多维特征对居民电力消费的驱动影响——基于浙江省分县数据的实证研究. 人口研究, 2016; 4: 103-112Ren Zhengwei and Mi Hong. 2016. Multiple Dimensions of Urbanization and Residential Electricity Consumption: A County-level Study in Zhejiang Province. Population Research 4: 103-112.
10 沈小波. 中国农村居民电力需求的影响因素. 统计研究, 2014; 1: 84-90Shen Xiaobo. 2014. Factors Affecting Rural Residents’ Electricity Demand in China.Statistical Research 1: 84-90.
11 王芳, 周兴. 人口结构、城镇化与碳排放——基于跨国面板数据的实证研究. 中国人口科学, 2012; 2: 47-56Wang Fang and Zhou Xing. 2012. Population Structure, Urbanization, and Carbon Emissions: An Empirical Study Based on Multinational Panel Data. Chinese Journal of Population Science 2: 47-56.
12 王文蝶, 牛叔文, 齐敬辉, 丁永霞, 李娜. 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. 资源科学, 2014; 7: 1434-1441Wang Wendie, Niu Shuwen, Qi Jinghui, Ding Yongxia and Li Na. 2014. The Correlation and Spatial Differences between Residential Energy Consumption and Income in the Process of Urbanization in China. Resources Science 7: 1434-1441.
13 张妮妮, 徐卫军. 农户生活用电消费分析——基于能源自选择行为. 中国农村经济, 2011;7: 72-84Zhang Nini and Xu Weijun.2011. Analysis of Rural Household Electricity Consumption: Based on Energy Self-selection Behavior. Chinese Rural Economy 7: 72-84.
14 张妮妮, 徐卫军, 曹鹏宇. 影响农户生活能源消费的因素分析——基于9省的微观数据. 中国人口科学, 2011; 3: 73-82Zhang Nini, Xu Weijun and Cao Pengyu. 2011. Analysis of Factors Influencing Rural Residential Energy Consumption: Based on Microdata of Nine Provinces. Chinese Journal of Population Science 3: 73-82.
15 郑新业等. 中国家庭能源消费研究报告2014. 北京: 科学出版社, 2015: 103-104Zheng Xinye et al. 2015. Chinese Household Energy Consumption Report:The 2014 Revision. Beijing: Science Press: 103-104.
16 周晖, 钮文洁, 纪洪. 各种因素影响下的居民夏季用电状况分析. 华北电力技术, 2003; 3: 12-14, 21Zhou Hui,Niu Wenjie and Ji Hong. 2003. Influence of Various Factors on Residents’ Electricity Consumption in Summer. North China Electric Power 3: 12-14, 21.
17 Brockett, D., Fridley, D., Lin, J.M. and Lin, J. 2002. A Tale of Five Cities: The China Residential Energy Consumption Survey. ACEEE Summer Study on Building Energy Efficiency: 29-40.
18 Druckman, A. and Jackson, T. 2008. Household Energy Consumption in the UK: A Highly Geographically and Socio-economically Disaggregated Model. Energy Policy 8: 3177-3192.
19 Fan, J.L., Zhang, Y.J. and Wang, B. 2017.The Impact of Urbanization on Residential Energy Consumption in China: An Aggregated and Disaggregated Analysis. Renewable and Sustainable Energy Reviews 75: 220-233.
20 Jiang, L. and O’Neill, B.C. 2004. The Energy Transition in Rural China. International Journal of Global Energy Issues 21: 2-26.
21 O’Neill, B.C. and Chen, B.S. 2002. Demographic Determinants of Household Energy Use in the United States. Population and Development Review 28: 53-88.
22 Pachauri, S. and Jiang, L. 2008. The Household Energy Transition in India and China. Energy Policy 11: 4022-4035.
23 Poumanyvong, P. and Kaneko, S. 2010. Does Urbanization Lead to Less Energy Use and Lower CO2 Emissions? A Cross-country Analysis. Ecological Economics 2: 434-444.
24 Prskawetz, P., Jiang, L. and O’Neill, B.C. 2004.Demographic Composition and Projections of Car Use in Austria. Vienna Yearbook of Population Research 2: 175-201.
25 United Nations. Department of Economic and Social Affairs. Population Division. 2015. World Population Prospects: The 2015 Revision.
26 Wang, X.H. and Feng, Z.M. 2001. Rural Household Energy Consumption with the Economic Development in China: Stages and Characteristic Indices. Energy Policy 15: 1391-1397.
27 Yamasaki, E. and Tominaga, N. 1997. Evolution of an Aging Society and Effect on Residential Energy Demand. Energy Policy 11: 903-912.
(1)IEA官网数据库,https://www.iea.org/energyaccess/database/。
(2)中国国家统计局的能源消费数据以“千克标准煤(kgce)”为单位计算,统计总量为“能源消费总量”,其中包含终端能源消费量、能源加工转换损失量和损失量。国际能源署的数据以“千克油当量(ktoe)”为单位,统计总量为“终端能源消费量”。因此,两者估计的生活能源消费占比略有出入。
(3)历年《中国人口统计年鉴》和《中国人口和就业统计年鉴》。
(4)其中,广西1995～2011年的数据和海南、福建的数据直接来自统计年鉴中的“人均生活用能”;浙江省的数据来源于各年份的《浙江省能源与利用状况》白皮书。能源消费量中不包括低热值能源、生物质能和太阳能的使用,或只包含这些能源作为商品能源使用的部分。
(5)考虑到“老年人口比重”与“少年人口比重”具有较强的多重共线性,本文只纳入“老年人口比重”这一变量。
(6)本文根据东、中、西部经济带划分省市,将北京、天津等11个省市列为东部地区,黑龙江、吉林等8个省市列为中部地区,内蒙古、广西等10个省市列为西部地区。我国以“秦岭、淮河为界”确定北方为集中供暖区域(郑新业等,2015),个别省市地跨“秦岭-淮河”一线,本文根据地理位置和实际供暖情况,将北京、天津、河北、山西、内蒙古、辽宁、吉林、黑龙江、山东、河南、陕西、甘肃、青海、新疆等14个省市划入北方地区,将上海、江苏、浙江、安徽、福建、江西、湖北、湖南、广东、广西、海南、重庆、四川、贵州、云南等15个省市划入南方地区。
(7)http://shupeidian.bjx.com.cn/news/20171113/861210.shtml。
(8)二次函数的顶点横坐标为-(-8.94)/(2*0.10)=44.7%。
(9)日本总务省统计局官网,http://www.stat.go.jp/data/nihon/02.html;韩国统计信息服务网,http://kosis.kr/eng/。