中国电力消费周期的路径演化识别——基于Markov区制转移模型
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摘要
基于1980—2016年中国第一产业、第二产业(工业、建筑业)和第三产业的年度电力消费数据,采用H-P滤波技术对中国电力消费的趋势成分和波动成分轨迹进行刻画,运用马尔科夫区制转移[MS(n)-AR(p)]模型分析中国电力消费周期在各区制间的动态转移过程,识别改革开放以来中国电力消费周期的路径演化特征,在此基础上预测未来5年中国电力消费周期的区制分布情况。研究发现:(1)中国电力消费增长率的波动程度自2003年明显缩窄,且从2007年开始进入下行周期。(2)中国电力消费周期具有较强的稳定性,不易向着其收缩期和扩张期跨越。且中国电力消费处于"低速增长区制"的年份往往对应着中国经济发展相对趋缓的大环境。(3)2014—2015年中国电力消费向其收缩期转移的迹象明显,但预测结果表明,未来5年中国电力消费整体上将继续保持稳定增长的趋势。
Based on the annual electricity consumption data of China's first industry, industry, construction industry and the third industry from 1980 to 2016, H-P filtering technology was used to depict the trajectories of the trend and fluctuation of China 's electricity consumption. The dynamic migration process of China's electricity consumption cycle in different districts was analyzed using MS(n)-AR(p) model. The path evolution characteristics of China's electricity consumption cycle since the reform and opening up were identified. On this basis, the regional distribution of China's power consumption cycle in the next 5 years was predicted.The study found that:(1)The fluctuation of China's electricity consumption growth rate narrowed significantly since 2003 and began to enter the downlink cycle from 2007.(2)China's power consumption cycle had a high stability, and it would not move easily to its systole period and expansion period. And China's electricity consumption in the years of "low growth regime"often corresponded to the relatively slow development of China's economic development environment.(3)In 2014—2015, China's electricity consumption showed an obvious sign of contraction, but the prediction results showed that China's electricity consumption would continue to maintain a steady growth trend in the next 5 years.
Based on the annual electricity consumption data of China's first industry, industry, construction industry and the third industry from 1980 to 2016, H-P filtering technology was used to depict the trajectories of the trend and fluctuation of China 's electricity consumption. The dynamic migration process of China's electricity consumption cycle in different districts was analyzed using MS(n)-AR(p) model. The path evolution characteristics of China's electricity consumption cycle since the reform and opening up were identified. On this basis, the regional distribution of China's power consumption cycle in the next 5 years was predicted.The study found that:(1)The fluctuation of China's electricity consumption growth rate narrowed significantly since 2003 and began to enter the downlink cycle from 2007.(2)China's power consumption cycle had a high stability, and it would not move easily to its systole period and expansion period. And China's electricity consumption in the years of "low growth regime"often corresponded to the relatively slow development of China's economic development environment.(3)In 2014—2015, China's electricity consumption showed an obvious sign of contraction, but the prediction results showed that China's electricity consumption would continue to maintain a steady growth trend in the next 5 years.
引文
[1]杨敏英.对电力供需形势变化的思考[J].数量经济技术经济研究,2004(2):35-38.
[2]宋瑞礼,徐策.当前电力供需紧张原因及对策[J].宏观经济管理,2011(12):29-30,36.
[3]李际,樊慧娴.2017年中国电力发展形势及2018年展望[J].中国能源,2018,40(1):19-22,14.
[4]BURNS A F,MITCHELL W C.Measuring business cycles[M].New York:National Bureau of Economic Research,1946.
[5]何永秀,赵四化,李莹,等.中国电力工业与国民经济增长的关系研究[J].产业经济研究,2006(1):47-53.
[6]YUAN J,ZHAO C,YU S,et al.Electricity consumption and economic growth in China:cointegration and co-feature analysis[J].Energy Economics,2007,29(6):1179-1191.
[7]ZHENG F,YANG C.Human capital and energy in economic growth—evidence from Chinese provincial data[J].Energy Economics,2017,68:340-35.
[8]李科.中国经济增长对电力消费的阈值效应分析[J].中国软科学,2011(7):31-41.
[9]牟敦果,林伯强.中国经济增长、电力消费和煤炭价格相互影响的时变参数研究[J].金融研究,2012(6):42-53.
[10]LIN B Q,LIU C.Why is electricity consumption inconsistent with economic growth in China?[J].Energy Policy,2016,88:310-316.
[11]SALAHUDDIN M,ALAM K.Information and communication technology,electricity consumption and economic growth in OECD countries:a panel data analysis[J].International Journal of Electrical Power&Energy Systems,2016,76:185-193.
[12]李强,王洪川,胡鞍钢.中国电力消费与经济增长——基于省际面板数据的因果分析[J].中国工业经济,2013(9):19-30.
[13]刘龙生,高宇宁,胡鞍钢.电力消费与中国经济增长[J].产业经济研究,2014(3):71-80.
[14]ZHANG C,ZHOU K L,YANG S,et al.Exploring the transformation and upgrading of China’s economy using electricity consumption data:a VAR–VEC based model[J].Physica A Statistical Mechanics&Its Applications,2017,473:144-155.
[15]刘畅,高铁梅.中国电力行业周期波动特征及电力需求影响因素分析——基于景气分析及误差修正模型的研究[J].资源科学,2011,33(1):169-177.
[16]柳瑞禹,叶子菀.高耗能行业电力消费长期波动效应研究[J].中国管理科学,2014,22(6):125-133.
[17]WANG H X,ZHANG J F,FANG H.Electricity footprint of China’s industrial sectors and its socioeconomic drivers[J].Resources Conservation&Recycling,2017,124:98-106.
[18]吴玉鸣.中国区域电力消费需求决定因素的实证研究[J].经济地理,2009(8):1318-1322.
[19]沈小波.中国农村居民电力需求的影响因素[J].统计研究,2014,31(1):84-90.
[20]何晓萍,刘希颖,林艳苹.中国城市化进程中的电力需求预测[J].经济研究,2009(1):118-130.
[21]史丹,冯永晟.中国电力需求的动态局部调整模型分析——基于电力需求特殊性的视角[J].中国工业经济,2015(10):5-20.
[22]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[J].人口研究,2016,40(4):103-112.
[23]梁亚丽.中国电力需求周期波动特性研究[D].北京:华北电力大学,2005.
[24]杨淑霞.中国电力需求周期演变规律及转折点研究[D].北京:华北电力大学,2006.
[25]张宇,何永秀,戴爱英等.中国典型城市电力与经济发展周期的关系研究[J].统计与决策,2009,24(1):106-108.
[26]谢品杰,孙飞虎,王绵斌.中国电力周期与经济周期的协同性—基于Markov区制转移模型[J].技术经济,2017,36(7):75-83,116.
[27]HALDUN S.Cyclical aspects of business cycle turning points[J].International Journal of Forecasting,2001(17):369-382.
[28]刘金全,隋建利,闫超.金融危机下中国经济周期波动态势与经济政策取向[J].中国工业经济,2009(8):37-46.
[29]刘金全,王雄威.中国经济周期波动态势的区域划分与动态特征检验[J].经济与管理研究,2011(6):5-10.
[30]KROLZIG H M.Markov-switching vector autoregressions:modeling,statistical inference,and application to business cycle analysis[M].Berlin:Springer,1997.
[31]HAMILTON J D.Analysis of time series subject to changes in regime[J].Journal of Econometrics,1990(45):39-70.
[32]FALLAHI F.Causal relationship between energy consumption(EC)and GDP:A Markov-switching(MS)causality[J].Energy,2011,36:4165-4170.
[33]陈强.高级计量经济学及Stata应用[M].北京:高等教育出版社,2010.
[34]FILARDO A J.Business-cycle phases and their transitional dynamics[J].Journal of Business&Economic Statistics,1994,12(3):299-308.
[35]CASTILLO P,HUMALA A,TUESTA V.Regime shifts and inflation uncertainty in PERU[J].Journal of Applied Economics,2012,15(1):71-87.
[36]张同斌,高铁梅.中国经济周期波动的阶段特征及驱动机制研究——基于时变概率马尔科夫区制转移(MS-TVTP)模型的实证分析[J].财贸经济,2015(1):27-39.
[37]朱锦月.中国通货膨胀率周期波动及其形成机制[D].北京:北京理工大学,2015.
(1)《BP世界能源统计年鉴(2017)》数据显示,2016年中国能源消费量达到3 053百万吨油当量,占世界能源消费总量的23%。中国国家能源局数据显示,2016年和2017年中国电力消费分别为59 198亿千瓦时和63 077亿千瓦时,电力消费增长速率分别为5.0%和6.6%。
(1)限于篇幅,单位根检验结果未在文中列出,如有需要,可向作者索取。
(1)“寻的行为”(Homing Behavior)是系统动力学(System Dynamics)中动态系统行为模式与结构的一种,指系统无限逼近于某一个常数的行为。
(2)绝对误差是既指明误差的大小,又指明误差的正负方向,以同一单位量纲反映预测结果偏离实际结果大小的值,它确切地表示了偏离实际值的实际大小。相对误差是指“绝对误差与实际值之比”,即该误差相当于预测的绝对误差占实际结果的百分比或用数量级表示,它是一个无量纲的值。用公式可表示为:δ=Δ/L×100%,其中,δ表示相对误差,一般用百分数给出。其中,Δ表示绝对误差;L表示实际值。
[2]宋瑞礼,徐策.当前电力供需紧张原因及对策[J].宏观经济管理,2011(12):29-30,36.
[3]李际,樊慧娴.2017年中国电力发展形势及2018年展望[J].中国能源,2018,40(1):19-22,14.
[4]BURNS A F,MITCHELL W C.Measuring business cycles[M].New York:National Bureau of Economic Research,1946.
[5]何永秀,赵四化,李莹,等.中国电力工业与国民经济增长的关系研究[J].产业经济研究,2006(1):47-53.
[6]YUAN J,ZHAO C,YU S,et al.Electricity consumption and economic growth in China:cointegration and co-feature analysis[J].Energy Economics,2007,29(6):1179-1191.
[7]ZHENG F,YANG C.Human capital and energy in economic growth—evidence from Chinese provincial data[J].Energy Economics,2017,68:340-35.
[8]李科.中国经济增长对电力消费的阈值效应分析[J].中国软科学,2011(7):31-41.
[9]牟敦果,林伯强.中国经济增长、电力消费和煤炭价格相互影响的时变参数研究[J].金融研究,2012(6):42-53.
[10]LIN B Q,LIU C.Why is electricity consumption inconsistent with economic growth in China?[J].Energy Policy,2016,88:310-316.
[11]SALAHUDDIN M,ALAM K.Information and communication technology,electricity consumption and economic growth in OECD countries:a panel data analysis[J].International Journal of Electrical Power&Energy Systems,2016,76:185-193.
[12]李强,王洪川,胡鞍钢.中国电力消费与经济增长——基于省际面板数据的因果分析[J].中国工业经济,2013(9):19-30.
[13]刘龙生,高宇宁,胡鞍钢.电力消费与中国经济增长[J].产业经济研究,2014(3):71-80.
[14]ZHANG C,ZHOU K L,YANG S,et al.Exploring the transformation and upgrading of China’s economy using electricity consumption data:a VAR–VEC based model[J].Physica A Statistical Mechanics&Its Applications,2017,473:144-155.
[15]刘畅,高铁梅.中国电力行业周期波动特征及电力需求影响因素分析——基于景气分析及误差修正模型的研究[J].资源科学,2011,33(1):169-177.
[16]柳瑞禹,叶子菀.高耗能行业电力消费长期波动效应研究[J].中国管理科学,2014,22(6):125-133.
[17]WANG H X,ZHANG J F,FANG H.Electricity footprint of China’s industrial sectors and its socioeconomic drivers[J].Resources Conservation&Recycling,2017,124:98-106.
[18]吴玉鸣.中国区域电力消费需求决定因素的实证研究[J].经济地理,2009(8):1318-1322.
[19]沈小波.中国农村居民电力需求的影响因素[J].统计研究,2014,31(1):84-90.
[20]何晓萍,刘希颖,林艳苹.中国城市化进程中的电力需求预测[J].经济研究,2009(1):118-130.
[21]史丹,冯永晟.中国电力需求的动态局部调整模型分析——基于电力需求特殊性的视角[J].中国工业经济,2015(10):5-20.
[22]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[J].人口研究,2016,40(4):103-112.
[23]梁亚丽.中国电力需求周期波动特性研究[D].北京:华北电力大学,2005.
[24]杨淑霞.中国电力需求周期演变规律及转折点研究[D].北京:华北电力大学,2006.
[25]张宇,何永秀,戴爱英等.中国典型城市电力与经济发展周期的关系研究[J].统计与决策,2009,24(1):106-108.
[26]谢品杰,孙飞虎,王绵斌.中国电力周期与经济周期的协同性—基于Markov区制转移模型[J].技术经济,2017,36(7):75-83,116.
[27]HALDUN S.Cyclical aspects of business cycle turning points[J].International Journal of Forecasting,2001(17):369-382.
[28]刘金全,隋建利,闫超.金融危机下中国经济周期波动态势与经济政策取向[J].中国工业经济,2009(8):37-46.
[29]刘金全,王雄威.中国经济周期波动态势的区域划分与动态特征检验[J].经济与管理研究,2011(6):5-10.
[30]KROLZIG H M.Markov-switching vector autoregressions:modeling,statistical inference,and application to business cycle analysis[M].Berlin:Springer,1997.
[31]HAMILTON J D.Analysis of time series subject to changes in regime[J].Journal of Econometrics,1990(45):39-70.
[32]FALLAHI F.Causal relationship between energy consumption(EC)and GDP:A Markov-switching(MS)causality[J].Energy,2011,36:4165-4170.
[33]陈强.高级计量经济学及Stata应用[M].北京:高等教育出版社,2010.
[34]FILARDO A J.Business-cycle phases and their transitional dynamics[J].Journal of Business&Economic Statistics,1994,12(3):299-308.
[35]CASTILLO P,HUMALA A,TUESTA V.Regime shifts and inflation uncertainty in PERU[J].Journal of Applied Economics,2012,15(1):71-87.
[36]张同斌,高铁梅.中国经济周期波动的阶段特征及驱动机制研究——基于时变概率马尔科夫区制转移(MS-TVTP)模型的实证分析[J].财贸经济,2015(1):27-39.
[37]朱锦月.中国通货膨胀率周期波动及其形成机制[D].北京:北京理工大学,2015.
(1)《BP世界能源统计年鉴(2017)》数据显示,2016年中国能源消费量达到3 053百万吨油当量,占世界能源消费总量的23%。中国国家能源局数据显示,2016年和2017年中国电力消费分别为59 198亿千瓦时和63 077亿千瓦时,电力消费增长速率分别为5.0%和6.6%。
(1)限于篇幅,单位根检验结果未在文中列出,如有需要,可向作者索取。
(1)“寻的行为”(Homing Behavior)是系统动力学(System Dynamics)中动态系统行为模式与结构的一种,指系统无限逼近于某一个常数的行为。
(2)绝对误差是既指明误差的大小,又指明误差的正负方向,以同一单位量纲反映预测结果偏离实际结果大小的值,它确切地表示了偏离实际值的实际大小。相对误差是指“绝对误差与实际值之比”,即该误差相当于预测的绝对误差占实际结果的百分比或用数量级表示,它是一个无量纲的值。用公式可表示为:δ=Δ/L×100%,其中,δ表示相对误差,一般用百分数给出。其中,Δ表示绝对误差;L表示实际值。