强可持续理念下绿色创新效率与生态福利绩效耦合协调的时空特征
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摘要
从强可持续理念出发,基于改进的SFA模型对中国2004-2015年30个省份的绿色创新效率及生态福利绩效值进行测度,结合耦合协调度模型对两系统的耦合协调度进行分析,同时考虑其空间特征及演变规律。结果表明:(1)中国生态福利绩效值在空间上已形成由北京—浙江—广东—陕西构成的四角极点支撑,并不断向沿线地区辐射。(2)2004-2015年两系统的耦合度均值C∈[0.666, 0.680],整体处于较高强度耦合阶段,而协调度均值则整体处于初级协调阶段(D∈[0.512, 0.565]),未来仍有较大的优化空间。(3)从空间格局上看,地区间的耦合协调度差距显著,高值区(中高级协调)主要集中在东部沿海地区,且已形成由广东—浙江两个高级协调发展极核辐射的"U"型发展轴带;初级协调阶段的地区连片扩张趋势明显。相比较而言,西北地区仍处于中国绿色创新效率与生态福利绩效耦合协调的最后梯队,受周边地区辐射影响较小,增速缓慢。
Starting from the concept of strong sustainability, we measure the green innovation efficiency and ecological welfare performance of 30 provinces in China from 2004 to 2015 based on the improved SFA model. We analyze the degree of the coupling coordination of the two systems with a coupling-coordination model, taking into account their spatial characteristics and evolution rules. The results show that:(1) China's ecological welfare performance value has been spatially supported by a quadrangular pole composed of Beijing, Zhejiang, Guangdong and Shaanxi, and continues to radiate to the areas along the lines.(2) The average coupling degree of the two systems in 2004-2015 is C∈ [0.666, 0.680], which is in the stage of high intensity coupling, while the average coordination degree is in the stage of elementary coordination(D∈ [0.512, 0.565]), meaning that there is still large improvement space in the future.(3) In terms of spatial pattern, there is a significant gap in the degree of coupling coordination between different regions. The high-value areas(midium-and high-level coordination) are mainly concentrated in the eastern coastal areas, and have formed a "U"-shaped development axis of polar nuclear radiation coordination between Guangdong and Zhejiang. At the elementary coordination stage, the trend of connected regional expansion is obvious. In comparison, the northwest region is still in the final echelon of the coupling coordination between China's green innovation efficiency and ecological welfare performance. It is less affected by the radiation from the surrounding areas and the growth rate is slow.
Starting from the concept of strong sustainability, we measure the green innovation efficiency and ecological welfare performance of 30 provinces in China from 2004 to 2015 based on the improved SFA model. We analyze the degree of the coupling coordination of the two systems with a coupling-coordination model, taking into account their spatial characteristics and evolution rules. The results show that:(1) China's ecological welfare performance value has been spatially supported by a quadrangular pole composed of Beijing, Zhejiang, Guangdong and Shaanxi, and continues to radiate to the areas along the lines.(2) The average coupling degree of the two systems in 2004-2015 is C∈ [0.666, 0.680], which is in the stage of high intensity coupling, while the average coordination degree is in the stage of elementary coordination(D∈ [0.512, 0.565]), meaning that there is still large improvement space in the future.(3) In terms of spatial pattern, there is a significant gap in the degree of coupling coordination between different regions. The high-value areas(midium-and high-level coordination) are mainly concentrated in the eastern coastal areas, and have formed a "U"-shaped development axis of polar nuclear radiation coordination between Guangdong and Zhejiang. At the elementary coordination stage, the trend of connected regional expansion is obvious. In comparison, the northwest region is still in the final echelon of the coupling coordination between China's green innovation efficiency and ecological welfare performance. It is less affected by the radiation from the surrounding areas and the growth rate is slow.
引文
[1]冯吉芳,袁健红.生态福利绩效:可持续发展新的分析工具.科技管理研究,2016,(12):240-244.[FENG J F,YUAN JH.Ecological welfare performance:A new analysis tool for sustainable development.Science and Technology Management Research,2016,(12):240-244.]
[2]MORAN D D,MATHIS W,KITZES J A,et al.Measuring sustainable development:Nation by nation.Ecological Economics,2008,64(3):470-474.
[3]NEUMAYER E.Weak Versus Strong Sustainability:Exploring the Limits of Two Opposing Paradigms.Cheltenham:Edward Elgar,2010.
[4]诸大建,张帅.生态福利绩效与深化可持续发展的研究.同济大学学报:社会科学版,2014,25(5):106-115.[ZHU DJ,ZHANG S.Ecological wellbeing performance and further research on sustainable development.Tongji University Journal Social Science Section,2014,25(5):106-115.]
[5]乔元波,王砚羽.基于三阶段DEA-Windows分析的中国省域创新效率评价.科学学与科学技术管理,2017,38(1):88-97.[QIAO Y B,WANG Y Y.The evaluation of innovation efficiency in China based on three-stage DEA-Windows.Science of Science and Management of Science&Technology,2017,38(1):88-97.]
[6]曹霞,于娟.绿色低碳视角下中国区域创新效率研究.中国人口·资源与环境,2015,25(5):10-19.[CAO X,YU J.Regional innovation efficiency in China from the green low-carbon perspective.China Population,Resources and Environment,2015,25(5):10-19.]
[7]何小钢.能源约束、绿色技术创新与可持续增长:理论模型与经验证据.中南财经政法大学学报,2015,(4):30-38.[HE X G.The constraint of energy,green technology innovation and sustainable growth:Theoretical model and empirical evidence.Journal of Zhongnan University of Economics and Law,2015,(4):30-38.]
[8]陈艳春,韩伯棠,岐洁.中国绿色技术的创新绩效与扩散动力.北京理工大学学报:社会科学版,2014,16(4):50-56.[CHEN Y C,HAN B T,QI J.The innovation performance and diffusion driven force of green technology in China.Journal of Beijing Institute of Technology:Social Sciences Edition,2014,16(4):50-56.]
[9]张振刚,白争辉,陈志明.绿色创新与经济增长的多变量协整关系研究:基于1989-2011年广东省数据.科技进步与对策,2014,31(10):24-30.[ZHANG Z G,BAI Z H,CHEN Z M.Multivariate cointegration relationship between green innovation and economic growth:Based on the yearly data of Guangdong between 1989 and 2011.Science&Technology Progress and Policy,2014,31(10):24-30.]
[10]Daly H E.A further critique of growth economics.Ecological Economics,2013,88:20-24.
[11]诸大建,张帅.生态福利绩效及其与经济增长的关系研究.中国人口·资源与环境,2014,24(9):59-67.[ZHU D J,ZHANG S.Research on ecological wellbeing performance and its relationship with economic growth.China Population,Resources and Environment,2014,24(9):59-67.]
[12]臧漫丹,诸大建,刘国平.生态福利绩效:概念、内涵及G20实证.中国人口·资源与环境,2013,23(5):118-124.[ZANG M D,ZHU D J,LIU G P.Ecological well-being performance:Concept,connotation and empirical of G20.China Population,Resources and Environment,2013,23(5):118-124.]
[13]龙亮军,王霞.上海市生态福利绩效评价研究.中国人口·资源与环境,2017,27(2):84-92.[LONG L J,WANG X.Astudy on Shanghai's ecological well-being performance.China Population,Resources and Environment,2017,27(2):84-92.]
[14]龙亮军,王霞,郭兵.基于改进DEA模型的城市生态福利绩效评价研究:以我国35个大中城市为例.自然资源学报,2017,32(4):595-605.[LONG L J,WANG X,GUO B.Evaluation of urban ecological well-being performance based on revised DEA model:A case study of 35 major cities in China.Journal of Natural Resources,2017,32(4):595-605.]
[15]张逸昕,林秀梅.中国省际绿色创新效率与系统协调度双演化研究.当代经济研究,2015,(3):51-56.[ZHANG Y X,LIN X M.The double evolution of system coordination degree of provincial green innovation efficiency in China.Contemporary Economic Research,2015,(3):51-56.]
[16]肖黎明,高军峰,刘帅.基于空间梯度的我国地区绿色技术创新效率的变化趋势:省际面板数据的经验分析.软科学,2017,31(9):63-68.[XIAO L M,GAO J F,LIU S.The change trend of green technology innovation efficiency in China based on spatial gradient:Empirical analysis of provincial panel data.Soft Science,2017,31(9):63-68.]
[17]张晓娣.生态效率变动的产业及要素推动:基于投入产出和系统优化模型.自然资源学报,2015,30(5):748-760.[ZHANG X D.Eco-efficiency change driven by products and factors:Combining input-output and system optimization models.Journal of Natural Resources,2015,30(5):748-760.]
[18]严立冬,屈志光,黄鹂.经济绿色转型视域下的生态资本效率研究.中国人口·资源与环境,2013,23(4):18-23.[YAN L D,QU Z G,HUANG L.Research on ecological capital efficiency under the perspective of green economic transition.China Population,Resources and Environment,2013,23(4):18-23.]
[19]SACH J,SCHMIDT-TRAUB G,KROLL C.SDG index and dashboard-global report.New York:Bertelsmann Stiftung and Sustainable Development Solutions Network,2016:11-52.
[20]薛澜,翁凌飞.中国实现联合国2030年可持续发展目标的政策机遇和挑战.中国软科学,2017,(1):1-12.[XUE L,WENG L F.The policy opportunities and challenges in China's implementation of 2030 sustainable development goals.China Soft Science,2017,(1):1-12.]
[21]赵喜仓,安荣花.江苏省科技成果转化效率及其影响因素分析:基于熵值和随机前沿的实证分析.科技管理研究,2013,(9):81-85.[ZHAO X C,AN R H.Transformation efficiency of sci-tech achievements and influence factors in Jiangsu province:Empirical analysis based on entropy and stochastic frontier function.Science and Technology Management Research,2013,(9):81-85.]
[22]张乐,曹静.中国农业全要素生产率增长:配置效率变化的引入:基于随机前沿生产函数法的实证分析.中国农村经济,2013,(3):4-15.[ZHANG L,CAO J.TFP growth in China:The introduction of changes in allocation efficiency:An empirical analysis based on stochastic frontier production function.Chinese Rural Economy,2013,(3):4-15.]
[23]BATTESE G E,COELLI T J.Frontier production functions,technical efficiency and panel data:With application to paddy farmers in India.Journal of Productivity Analysis,1992,3(6):153-169.
[24]王少剑,方创琳,王洋.京津冀地区城市化与生态环境交互耦合关系定量测度.生态学报,2015,35(7):2244-2254.[WANG S J,FANG C L,WANG Y.Quantitative investigation of the interactive coupling relationship between urbanization and eco-environment.Acta Ecologica Sinica,2015,35(7):2244-2254.]
[25]张荣天,焦华富.泛长江三角洲地区经济发展与生态环境耦合协调关系分析.长江流域资源与环境,2015,24(5):719-727.[ZHANG R T,JIAO H F.Coupling and coordinating between economic development and ecological environment in the Pan Yangtze River Delta.Resources and Environment in the Yangtze Basin,2015,24(5):719-727.]
[26]邹璇,贾蕾玉.工业能源消耗结构的优化路径及地区差异.软科学,2017,31(6):46-50.[ZOU X,JIA L Y.The optimal path and regional differences of the industrial energy consumption structure.Soft Science,2017,31(6):46-50.]
(1)环境污染综合值为人均工业废水、废气、固废排放量在熵值法测算下的综合值。
(2)综合能耗产出率等于规模以上工业企业总产值与能源消耗总量之比(元/吨标准煤)。
(3)本文涉及的价格指数依次为地区研发价格指数(RPI=0.75PPI+0.25CPI)、地区工业生产者出厂价格指数(PPI)、居民消费价格指数(CPI)、地区生产总值指数、地区固定资产投资价格指数。
(4)参考已有文献[26]将西部地区划分为西北地区和西南地区,其中西南地区包括广西、重庆、四川、贵州和云南;西北地区包括内蒙古,陕西、甘肃、青海、宁夏和新疆。
[2]MORAN D D,MATHIS W,KITZES J A,et al.Measuring sustainable development:Nation by nation.Ecological Economics,2008,64(3):470-474.
[3]NEUMAYER E.Weak Versus Strong Sustainability:Exploring the Limits of Two Opposing Paradigms.Cheltenham:Edward Elgar,2010.
[4]诸大建,张帅.生态福利绩效与深化可持续发展的研究.同济大学学报:社会科学版,2014,25(5):106-115.[ZHU DJ,ZHANG S.Ecological wellbeing performance and further research on sustainable development.Tongji University Journal Social Science Section,2014,25(5):106-115.]
[5]乔元波,王砚羽.基于三阶段DEA-Windows分析的中国省域创新效率评价.科学学与科学技术管理,2017,38(1):88-97.[QIAO Y B,WANG Y Y.The evaluation of innovation efficiency in China based on three-stage DEA-Windows.Science of Science and Management of Science&Technology,2017,38(1):88-97.]
[6]曹霞,于娟.绿色低碳视角下中国区域创新效率研究.中国人口·资源与环境,2015,25(5):10-19.[CAO X,YU J.Regional innovation efficiency in China from the green low-carbon perspective.China Population,Resources and Environment,2015,25(5):10-19.]
[7]何小钢.能源约束、绿色技术创新与可持续增长:理论模型与经验证据.中南财经政法大学学报,2015,(4):30-38.[HE X G.The constraint of energy,green technology innovation and sustainable growth:Theoretical model and empirical evidence.Journal of Zhongnan University of Economics and Law,2015,(4):30-38.]
[8]陈艳春,韩伯棠,岐洁.中国绿色技术的创新绩效与扩散动力.北京理工大学学报:社会科学版,2014,16(4):50-56.[CHEN Y C,HAN B T,QI J.The innovation performance and diffusion driven force of green technology in China.Journal of Beijing Institute of Technology:Social Sciences Edition,2014,16(4):50-56.]
[9]张振刚,白争辉,陈志明.绿色创新与经济增长的多变量协整关系研究:基于1989-2011年广东省数据.科技进步与对策,2014,31(10):24-30.[ZHANG Z G,BAI Z H,CHEN Z M.Multivariate cointegration relationship between green innovation and economic growth:Based on the yearly data of Guangdong between 1989 and 2011.Science&Technology Progress and Policy,2014,31(10):24-30.]
[10]Daly H E.A further critique of growth economics.Ecological Economics,2013,88:20-24.
[11]诸大建,张帅.生态福利绩效及其与经济增长的关系研究.中国人口·资源与环境,2014,24(9):59-67.[ZHU D J,ZHANG S.Research on ecological wellbeing performance and its relationship with economic growth.China Population,Resources and Environment,2014,24(9):59-67.]
[12]臧漫丹,诸大建,刘国平.生态福利绩效:概念、内涵及G20实证.中国人口·资源与环境,2013,23(5):118-124.[ZANG M D,ZHU D J,LIU G P.Ecological well-being performance:Concept,connotation and empirical of G20.China Population,Resources and Environment,2013,23(5):118-124.]
[13]龙亮军,王霞.上海市生态福利绩效评价研究.中国人口·资源与环境,2017,27(2):84-92.[LONG L J,WANG X.Astudy on Shanghai's ecological well-being performance.China Population,Resources and Environment,2017,27(2):84-92.]
[14]龙亮军,王霞,郭兵.基于改进DEA模型的城市生态福利绩效评价研究:以我国35个大中城市为例.自然资源学报,2017,32(4):595-605.[LONG L J,WANG X,GUO B.Evaluation of urban ecological well-being performance based on revised DEA model:A case study of 35 major cities in China.Journal of Natural Resources,2017,32(4):595-605.]
[15]张逸昕,林秀梅.中国省际绿色创新效率与系统协调度双演化研究.当代经济研究,2015,(3):51-56.[ZHANG Y X,LIN X M.The double evolution of system coordination degree of provincial green innovation efficiency in China.Contemporary Economic Research,2015,(3):51-56.]
[16]肖黎明,高军峰,刘帅.基于空间梯度的我国地区绿色技术创新效率的变化趋势:省际面板数据的经验分析.软科学,2017,31(9):63-68.[XIAO L M,GAO J F,LIU S.The change trend of green technology innovation efficiency in China based on spatial gradient:Empirical analysis of provincial panel data.Soft Science,2017,31(9):63-68.]
[17]张晓娣.生态效率变动的产业及要素推动:基于投入产出和系统优化模型.自然资源学报,2015,30(5):748-760.[ZHANG X D.Eco-efficiency change driven by products and factors:Combining input-output and system optimization models.Journal of Natural Resources,2015,30(5):748-760.]
[18]严立冬,屈志光,黄鹂.经济绿色转型视域下的生态资本效率研究.中国人口·资源与环境,2013,23(4):18-23.[YAN L D,QU Z G,HUANG L.Research on ecological capital efficiency under the perspective of green economic transition.China Population,Resources and Environment,2013,23(4):18-23.]
[19]SACH J,SCHMIDT-TRAUB G,KROLL C.SDG index and dashboard-global report.New York:Bertelsmann Stiftung and Sustainable Development Solutions Network,2016:11-52.
[20]薛澜,翁凌飞.中国实现联合国2030年可持续发展目标的政策机遇和挑战.中国软科学,2017,(1):1-12.[XUE L,WENG L F.The policy opportunities and challenges in China's implementation of 2030 sustainable development goals.China Soft Science,2017,(1):1-12.]
[21]赵喜仓,安荣花.江苏省科技成果转化效率及其影响因素分析:基于熵值和随机前沿的实证分析.科技管理研究,2013,(9):81-85.[ZHAO X C,AN R H.Transformation efficiency of sci-tech achievements and influence factors in Jiangsu province:Empirical analysis based on entropy and stochastic frontier function.Science and Technology Management Research,2013,(9):81-85.]
[22]张乐,曹静.中国农业全要素生产率增长:配置效率变化的引入:基于随机前沿生产函数法的实证分析.中国农村经济,2013,(3):4-15.[ZHANG L,CAO J.TFP growth in China:The introduction of changes in allocation efficiency:An empirical analysis based on stochastic frontier production function.Chinese Rural Economy,2013,(3):4-15.]
[23]BATTESE G E,COELLI T J.Frontier production functions,technical efficiency and panel data:With application to paddy farmers in India.Journal of Productivity Analysis,1992,3(6):153-169.
[24]王少剑,方创琳,王洋.京津冀地区城市化与生态环境交互耦合关系定量测度.生态学报,2015,35(7):2244-2254.[WANG S J,FANG C L,WANG Y.Quantitative investigation of the interactive coupling relationship between urbanization and eco-environment.Acta Ecologica Sinica,2015,35(7):2244-2254.]
[25]张荣天,焦华富.泛长江三角洲地区经济发展与生态环境耦合协调关系分析.长江流域资源与环境,2015,24(5):719-727.[ZHANG R T,JIAO H F.Coupling and coordinating between economic development and ecological environment in the Pan Yangtze River Delta.Resources and Environment in the Yangtze Basin,2015,24(5):719-727.]
[26]邹璇,贾蕾玉.工业能源消耗结构的优化路径及地区差异.软科学,2017,31(6):46-50.[ZOU X,JIA L Y.The optimal path and regional differences of the industrial energy consumption structure.Soft Science,2017,31(6):46-50.]
(1)环境污染综合值为人均工业废水、废气、固废排放量在熵值法测算下的综合值。
(2)综合能耗产出率等于规模以上工业企业总产值与能源消耗总量之比(元/吨标准煤)。
(3)本文涉及的价格指数依次为地区研发价格指数(RPI=0.75PPI+0.25CPI)、地区工业生产者出厂价格指数(PPI)、居民消费价格指数(CPI)、地区生产总值指数、地区固定资产投资价格指数。
(4)参考已有文献[26]将西部地区划分为西北地区和西南地区,其中西南地区包括广西、重庆、四川、贵州和云南;西北地区包括内蒙古,陕西、甘肃、青海、宁夏和新疆。
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