创新对中国城市生态效率的影响研究——基于空间溢出分解的视角
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摘要
在创新驱动城市绿色发展的背景下,需要高度重视区域异质性,并通过创新及其空间溢出等途径协同提升城市生态效率。本文将凸共同前沿拓展到非凸共同前沿,并利用改进的数据包络分析模型测度了中国2003-2015年191个地级及以上城市的生态效率,研究了城市创新空间溢出的高位压力和低位吸力对生态效率的提升机制。主要发现有:邻近地区城市创新的高位压力对本市生态效率提升具有显著的促进作用,表现为"见贤思齐"效应,且这种提升作用不会随距离阈值的增大而出现衰减。分组比较发现,东部城市、环境保护重点城市、非资源型城市和两控区城市创新能力的高位压力对生态效率具有明显的提升作用,表明"见贤思齐"效应依然占主导。实证研究表明:地方政府应高度重视城市创新的正、负向空间溢出,积极发挥"见贤思齐"的积极作用,避免"见劣自缓"的负面影响,对不同城市类型采取差别化约束机制,坚持分类指导、特色发展,以快速有效地提升城市生态效率,实现区域绿色发展、协调发展的目标。
It is necessary to attach great importance to regional heterogeneity in the precence of innovation driven urban green development,promoting ecological efficiency through innovation and its spatial spillovers. In this study,we extend the convex metafrontier to non-convex one and measure the eco-efficiency of 191 prefectural-level cities in China by using the proposed DEA model to research the promotion mechanisms of the spatial spillovers from city innovation including higher-order pressure and lower-order suction on eco-efficiency during the period of 2003-2015.The main findings are as follows: the higher-order pressure of city innovation in neighboring areas exerts a significant boosting effect on the local regions' eco-efficiency,indicating the effect of "Witnessing Excellence and Emulating( WEE) "is prominent,and the effect will be strengthened with the distance threshold increasing. The subgroup estimation results show that the higher-order pressure of city innovation of the prefecture in eastern region,the prefectures listed as key environmental protection,the prefectures do not list as resource-based cities and two control zones have a significant positive effect on eco-efficiency,indicating that the hypothesis of WEE plays a dominant role. The empirical findings suggest that we should attach great importance to the positive and negative spatial spillovers of city innovation,actively play the positive role of WEE other than the oppose patterns and adopt differential restraint mechanisms for different types of cities. In order to improve the eco-efficiency of prefecture-level cities quickly and effectively,and achieve the goal of regional green development and coordinated development,the government should adopt differential constraint mechanism for different cities.
It is necessary to attach great importance to regional heterogeneity in the precence of innovation driven urban green development,promoting ecological efficiency through innovation and its spatial spillovers. In this study,we extend the convex metafrontier to non-convex one and measure the eco-efficiency of 191 prefectural-level cities in China by using the proposed DEA model to research the promotion mechanisms of the spatial spillovers from city innovation including higher-order pressure and lower-order suction on eco-efficiency during the period of 2003-2015.The main findings are as follows: the higher-order pressure of city innovation in neighboring areas exerts a significant boosting effect on the local regions' eco-efficiency,indicating the effect of "Witnessing Excellence and Emulating( WEE) "is prominent,and the effect will be strengthened with the distance threshold increasing. The subgroup estimation results show that the higher-order pressure of city innovation of the prefecture in eastern region,the prefectures listed as key environmental protection,the prefectures do not list as resource-based cities and two control zones have a significant positive effect on eco-efficiency,indicating that the hypothesis of WEE plays a dominant role. The empirical findings suggest that we should attach great importance to the positive and negative spatial spillovers of city innovation,actively play the positive role of WEE other than the oppose patterns and adopt differential restraint mechanisms for different types of cities. In order to improve the eco-efficiency of prefecture-level cities quickly and effectively,and achieve the goal of regional green development and coordinated development,the government should adopt differential constraint mechanism for different cities.
引文
[1]陈林心,何宜庆,程家鼎.创新、创业与生态效率提升研究——基于长江中游城市群的空间面板模型[J].华东经济管理,2016,30(10):87-94.
[2]陈真玲.生态效率、城镇化与空间溢出——基于空间面板杜宾模型的研究[J].管理评论,2016,28(11):66-74.
[3]付丽娜,陈晓红,冷智花.基于超效率DEA模型的城市群生态效率研究——以长株潭“3+5”城市群为例[J].中国人口·资源与环境,2013,23(4):169-175.
[4]郭莉,L.Malesu,胡筱敏.环境技术创新对产业生态管理的影响[J].中国人口·资源与环境,2009,19(2):78-82.
[5]黄建欢,谢优男,余燕团.城市竞争、空间溢出与生态效率:高位压力和低位吸力的影响[J].中国人口·资源与环境,2018,28(3):1-12.
[6]黄建欢,许和连.中国区域生态效率的时空演变和提升机制[J].湖南大学学报(社会科学版),2016,30(1):60-70.
[7]黄建欢.区域异质性,生态效率与绿色发展[M].北京:中国社会科学出版社,2016.
[8]贾军,张卓.中国高技术产业技术创新与能源效率协同发展实证研究[J].中国人口·资源与环境,2013,23(2):36-42.
[9]柯善咨,向娟.1996-2009年中国城市固定资本存量估算[J].统计研究,2012,(7):19-24.
[10]寇宗来,刘学悦.中国城市和产业创新力报告2017[R].2017.
[11]李小平,杨翔,王洋.国际贸易提高了中国制造业的碳生产率吗?[J].环境经济研究,2016,1(2):8-24.
[12]连平,周昆平,唐建伟,刘学智.新时代中国经济发展趋势展望[J].科学发展,2018,(110):14-20.
[13]梁星,卓得波.中国区域生态效率评价及影响因素分析[J].统计与决策,2017,(19):143-147.
[14]刘丙泉,于晓燕,李永波.基于共同前沿模型的中国区域生态效率差异研究[J].科技管理研究,2016,36(5):211-214.
[15]卢燕群,袁鹏.中国省域工业生态效率及影响因素的空间计量分析[J].资源科学,2017,39(7):1326-1337.
[16]马述忠,柴宇曦.科技创新、资源配置与技术效率——以浙江省高技术产业为例[J].中共浙江省委党校学报,2016,32(1):60-66.
[17]石敏俊,范宪伟,逄瑞,陈旭宇.透视中国城市的绿色发展——基于新资源经济城市指数的评价[J].环境经济研究,2016,1(2):46-59.
[18]汪克亮,王丹丹,孟祥瑞.基于技术差距的中国地区工业生态效率研究[J].安徽理工大学学报(社会科学版),2016,18(4):25-31.
[19]王恩旭,武春友.基于超效率DEA模型的中国省际生态效率时空差异研究[J].管理学报,2011,08(3):443-450.
[20]王瑾.工业技术与资源环境协调发展的实证研究——基于超效率DEA生态效率和区域面板数据[J].科技管理研究,2014,(22):208-212.
[21]王亚平,任建兰,程钰.科技创新对绿色发展的影响机制与区域创新体系构建[J].山东师范大学学报(人文社会科学版),2017,62(4):68-76.
[22]王永芹.对创新驱动绿色发展的思考[J].河北学刊,2014,(2):222-225.
[23]武春友,于文嵩,郭玲玲.基于演化理论的生态效率影响因素研究[J].技术经济,2015,34(5):63-69.
[24]叶依广,孙林.资源效率与科技创新[J].中国人口·资源与环境,2002,(6):17-19.
[25]张浩然,衣保中.地理距离与城市间溢出效应——基于空间面板模型的经验研究[J].当代经济科学,2011,33(3):117-123.
[26]Afsharian,M.Metafrontier Efficiency Analysis with Convex and Non-convex Metatechnologies by Stochastic Nonparametric Envelopment of Data[J].Economics Letters,2017,160:1-3.
[27]Afsharian,M.and V.V.Podinovski.A Linear Programming Approach to Efficiency Evaluation in Nonconvex Metatechnologies[J].European Journal of Operational Research,2018,268(1):268-280.
[28]Andersen,P.and N.C.Petersen.A Procedure for Ranking Efficient Units in Data Envelopment Analysis[J].Management Science,1993,39(10):1261-1264.
[29]Huang,C.W.,C.T.Ting,C.H.Lin,and C.T.Lin.Measuring Non-convex Metafrontier Efficiency in International Tourist Hotels[J].Journal of the Operational Research Society,2013,64(2):250-259.
[30]Huang,J.,and J.Xia.Regional Competition,Heterogeneous Factors and Pollution Intensity in China:A Spatial Econometric Analysis[J].Sustainability,2016,8(2):171.
[31]Huang,J.,J.Xia,Y.Yu,and N.Zhang.Composite Eco-efficiency Indicators for China Based on Data Envelopment Analysis[J].Ecological Indicators,2018,85:674-697.
[32]Huang,J.,X.Yang,G.Cheng,and S.Wang.A Comprehensive Eco-efficiency Model and Dynamics of Regional Eco-efficiency in China[J].Journal of Cleaner Production,2014,67(3):228-238.
[33]Huang,J.,Y.Yu,and C.Ma.Energy Efficiency Convergence in China:Catch-up,Lock-in and Regulatory Uniformity[J].Environmental and Resource Economics,2017,70(1):107-130.
[34]Orea,L.and A.Wall.A Parametric Approach to Estimating Eco-Efficiency[J].Journal of Agricultural Economics,2017,68(3):901-907.
[35]Orea,L.and A.Wall.Measuring Eco-efficiency Using the Stochastic Frontier Analysis Approach[M].Germany:Springer,2016.
[36]Tiedemann,T.,T.Francksen,and U.Latacz-Lohmann.Assessing the Performance of GermanBundesliga,Football Players:A Non-parametric Metafrontier Approach[J].Central European Journal of Operations Research,2011,19(4):571-587.
[37]Tone,K.A Slacks-based Measure of Efficiency in Data Envelopment Analysis[J].European Journal of Operational Research,2001,130(3):498-509.
[38]Walheer,B.Aggregation of Metafrontier Technology Gap Ratios:The Case of European Sectors in 1995-2015[J].European Journal of Operational Research,2018,269(3):1013-1026.
[39]Yu,Y.,J.Huang,and N.Luo.Can More Environmental Information Disclosure Lead to Higher Eco-Efficiency?Evidence from China[J].Sustainability,2018,10(2):528.
[40]Zhang,B.,J.Bi,Z.Fan,Z.Yuan,and J.Ge.Eco-efficiency Analysis of Industrial System in China:A Data Envelopment Analysis Approach[J].Ecological Economics,2008,68:306-316.
[41]Zhang,J.,Y.Chang,L.Zhang,and D.Li.Do Technological Innovations Promote Urban Green Development?—A Spatial Econometric Analysis of 105 Cities in China[J].Journal of Cleaner Production,2018,182:395-403.
(1)国家“七五”规划(1986-1990)将中国划分为3个经济区域:东部、中部和西部。东部地区由北京市、天津市、河北省、辽宁省、上海市、江苏省、浙江省、福建省、山东省、广东省和海南省组成;中部地区由山西省、内蒙古自治区、吉林省、黑龙江省、安徽省、江西省、河南省、湖北省、湖南省和广西壮族自治区组成;西部地区由四川省、贵州省、云南省、西藏自治区、陕西省、甘肃省、青海省、宁夏回族自治区、新疆维吾尔自治区组成。
(1)《大气污染防治法》规定,根据气象、地形、土壤等自然条件,可以将已经产生、可能产生酸雨的地区或者其他二氧化硫污染严重的地区,划定为酸雨控制区或者二氧化硫污染控制区,即“两控区”。具体的划分标准参考《酸雨控制区和二氧化硫污染控制区划分方案》,详见:http://www.zhb.gov.cn/gkml/zj/wj/200910/t20091022_172231.htm。
[2]陈真玲.生态效率、城镇化与空间溢出——基于空间面板杜宾模型的研究[J].管理评论,2016,28(11):66-74.
[3]付丽娜,陈晓红,冷智花.基于超效率DEA模型的城市群生态效率研究——以长株潭“3+5”城市群为例[J].中国人口·资源与环境,2013,23(4):169-175.
[4]郭莉,L.Malesu,胡筱敏.环境技术创新对产业生态管理的影响[J].中国人口·资源与环境,2009,19(2):78-82.
[5]黄建欢,谢优男,余燕团.城市竞争、空间溢出与生态效率:高位压力和低位吸力的影响[J].中国人口·资源与环境,2018,28(3):1-12.
[6]黄建欢,许和连.中国区域生态效率的时空演变和提升机制[J].湖南大学学报(社会科学版),2016,30(1):60-70.
[7]黄建欢.区域异质性,生态效率与绿色发展[M].北京:中国社会科学出版社,2016.
[8]贾军,张卓.中国高技术产业技术创新与能源效率协同发展实证研究[J].中国人口·资源与环境,2013,23(2):36-42.
[9]柯善咨,向娟.1996-2009年中国城市固定资本存量估算[J].统计研究,2012,(7):19-24.
[10]寇宗来,刘学悦.中国城市和产业创新力报告2017[R].2017.
[11]李小平,杨翔,王洋.国际贸易提高了中国制造业的碳生产率吗?[J].环境经济研究,2016,1(2):8-24.
[12]连平,周昆平,唐建伟,刘学智.新时代中国经济发展趋势展望[J].科学发展,2018,(110):14-20.
[13]梁星,卓得波.中国区域生态效率评价及影响因素分析[J].统计与决策,2017,(19):143-147.
[14]刘丙泉,于晓燕,李永波.基于共同前沿模型的中国区域生态效率差异研究[J].科技管理研究,2016,36(5):211-214.
[15]卢燕群,袁鹏.中国省域工业生态效率及影响因素的空间计量分析[J].资源科学,2017,39(7):1326-1337.
[16]马述忠,柴宇曦.科技创新、资源配置与技术效率——以浙江省高技术产业为例[J].中共浙江省委党校学报,2016,32(1):60-66.
[17]石敏俊,范宪伟,逄瑞,陈旭宇.透视中国城市的绿色发展——基于新资源经济城市指数的评价[J].环境经济研究,2016,1(2):46-59.
[18]汪克亮,王丹丹,孟祥瑞.基于技术差距的中国地区工业生态效率研究[J].安徽理工大学学报(社会科学版),2016,18(4):25-31.
[19]王恩旭,武春友.基于超效率DEA模型的中国省际生态效率时空差异研究[J].管理学报,2011,08(3):443-450.
[20]王瑾.工业技术与资源环境协调发展的实证研究——基于超效率DEA生态效率和区域面板数据[J].科技管理研究,2014,(22):208-212.
[21]王亚平,任建兰,程钰.科技创新对绿色发展的影响机制与区域创新体系构建[J].山东师范大学学报(人文社会科学版),2017,62(4):68-76.
[22]王永芹.对创新驱动绿色发展的思考[J].河北学刊,2014,(2):222-225.
[23]武春友,于文嵩,郭玲玲.基于演化理论的生态效率影响因素研究[J].技术经济,2015,34(5):63-69.
[24]叶依广,孙林.资源效率与科技创新[J].中国人口·资源与环境,2002,(6):17-19.
[25]张浩然,衣保中.地理距离与城市间溢出效应——基于空间面板模型的经验研究[J].当代经济科学,2011,33(3):117-123.
[26]Afsharian,M.Metafrontier Efficiency Analysis with Convex and Non-convex Metatechnologies by Stochastic Nonparametric Envelopment of Data[J].Economics Letters,2017,160:1-3.
[27]Afsharian,M.and V.V.Podinovski.A Linear Programming Approach to Efficiency Evaluation in Nonconvex Metatechnologies[J].European Journal of Operational Research,2018,268(1):268-280.
[28]Andersen,P.and N.C.Petersen.A Procedure for Ranking Efficient Units in Data Envelopment Analysis[J].Management Science,1993,39(10):1261-1264.
[29]Huang,C.W.,C.T.Ting,C.H.Lin,and C.T.Lin.Measuring Non-convex Metafrontier Efficiency in International Tourist Hotels[J].Journal of the Operational Research Society,2013,64(2):250-259.
[30]Huang,J.,and J.Xia.Regional Competition,Heterogeneous Factors and Pollution Intensity in China:A Spatial Econometric Analysis[J].Sustainability,2016,8(2):171.
[31]Huang,J.,J.Xia,Y.Yu,and N.Zhang.Composite Eco-efficiency Indicators for China Based on Data Envelopment Analysis[J].Ecological Indicators,2018,85:674-697.
[32]Huang,J.,X.Yang,G.Cheng,and S.Wang.A Comprehensive Eco-efficiency Model and Dynamics of Regional Eco-efficiency in China[J].Journal of Cleaner Production,2014,67(3):228-238.
[33]Huang,J.,Y.Yu,and C.Ma.Energy Efficiency Convergence in China:Catch-up,Lock-in and Regulatory Uniformity[J].Environmental and Resource Economics,2017,70(1):107-130.
[34]Orea,L.and A.Wall.A Parametric Approach to Estimating Eco-Efficiency[J].Journal of Agricultural Economics,2017,68(3):901-907.
[35]Orea,L.and A.Wall.Measuring Eco-efficiency Using the Stochastic Frontier Analysis Approach[M].Germany:Springer,2016.
[36]Tiedemann,T.,T.Francksen,and U.Latacz-Lohmann.Assessing the Performance of GermanBundesliga,Football Players:A Non-parametric Metafrontier Approach[J].Central European Journal of Operations Research,2011,19(4):571-587.
[37]Tone,K.A Slacks-based Measure of Efficiency in Data Envelopment Analysis[J].European Journal of Operational Research,2001,130(3):498-509.
[38]Walheer,B.Aggregation of Metafrontier Technology Gap Ratios:The Case of European Sectors in 1995-2015[J].European Journal of Operational Research,2018,269(3):1013-1026.
[39]Yu,Y.,J.Huang,and N.Luo.Can More Environmental Information Disclosure Lead to Higher Eco-Efficiency?Evidence from China[J].Sustainability,2018,10(2):528.
[40]Zhang,B.,J.Bi,Z.Fan,Z.Yuan,and J.Ge.Eco-efficiency Analysis of Industrial System in China:A Data Envelopment Analysis Approach[J].Ecological Economics,2008,68:306-316.
[41]Zhang,J.,Y.Chang,L.Zhang,and D.Li.Do Technological Innovations Promote Urban Green Development?—A Spatial Econometric Analysis of 105 Cities in China[J].Journal of Cleaner Production,2018,182:395-403.
(1)国家“七五”规划(1986-1990)将中国划分为3个经济区域:东部、中部和西部。东部地区由北京市、天津市、河北省、辽宁省、上海市、江苏省、浙江省、福建省、山东省、广东省和海南省组成;中部地区由山西省、内蒙古自治区、吉林省、黑龙江省、安徽省、江西省、河南省、湖北省、湖南省和广西壮族自治区组成;西部地区由四川省、贵州省、云南省、西藏自治区、陕西省、甘肃省、青海省、宁夏回族自治区、新疆维吾尔自治区组成。
(1)《大气污染防治法》规定,根据气象、地形、土壤等自然条件,可以将已经产生、可能产生酸雨的地区或者其他二氧化硫污染严重的地区,划定为酸雨控制区或者二氧化硫污染控制区,即“两控区”。具体的划分标准参考《酸雨控制区和二氧化硫污染控制区划分方案》,详见:http://www.zhb.gov.cn/gkml/zj/wj/200910/t20091022_172231.htm。