[1]孙欣,曾菊芬.中国区域绿色技术创新效率的空间分布及影响因素分析[J].长安大学学报(社科版),2019,21(06):29-44.
SUN Xin,ZENG Jufen.Spatial distribution and influential factors of regional green technology innovation efficiency in China[J].Journal of Chang'an University(Social Science Edition),2019,21(06):29-44.
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中国区域绿色技术创新效率的空间分布及影响因素分析(PDF)
《长安大学学报(社科版)》[ISSN:1671-6248/CN:61-1391/C]
- 卷:
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第21卷
- 期数:
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2019年06期
- 页码:
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29-44
- 栏目:
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区域经济
- 出版日期:
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2020-01-06
文章信息/Info
- Title:
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Spatial distribution and influential factors of regional green technology innovation efficiency in China
- 作者:
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孙欣; 曾菊芬
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安徽财经大学 统计与应用数学学院,安徽 蚌埠233010
- Author(s):
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SUN Xin; ZENG Jufen
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School of Statistics and Applied Mathematics,Anhui University of Finance and Economics,Bengbu 233010,Anhui,China
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- 关键词:
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绿色技术; 创新效率; 区域经济; 环境规制; DEASBM模型; 全局MalmquistLuenberger指数; 空间计量模型
- Keywords:
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green technology; innovation efficiency; regional economy; environmental regulation; DEA-SBM model; global Malmquist-Luenberger index; spatial econometric model
- 分类号:
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F205
- DOI:
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-
- 文献标志码:
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A
- 摘要:
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绿色技术创新是绿色发展主要动力,研究区域绿色技术创新效率对提升区域创新能力和推动区域经济可持续发展具有重要意义。基于传统的测算绿色技术创新效率的DEA模型没有考虑非期望产出和要素“松弛”的情况,本文以2008~2017年各省的面板数据为样本,结合非期望产出的DEA-SBM模型和全局Malmquist-Luenberger指数评价研究各区域绿色技术创新效率的静态和动态变化,并将绿色技术创新效率与纯技术创新效率进行比较分析,采用全局空间自相关和局部空间自相关检验区域间绿色技术创新效率的空间相关性,建立空间计量模型对绿色技术创新效率的影响因素进行探究。研究认为,各区域的绿色技术创新效率整体水平不高,大部分区域呈现逐年上升的趋势,总体处于“东高西低”的分布格局;纯技术创新效率要优于绿色技术创新效率;大多数省份的绿色技术创新全要素生产率呈增长态势,并且技术进步是影响的主要因素;区域创新效率具有明显的空间正自相关性和空间集聚效应,集聚效应主要体现在低效率的LL象限和高效率的H-H象限;完善技术市场环境机制、扩大经济对外开放、优化产业结构对提升区域绿色技术创新效率有积极的促进作用,环境规制对创新效率发展具有明显的抑制作用,可能与环境政策在短期内造成的挤出效应有关。
- Abstract:
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Green technology innovation is the main driving force of green development. Studying regional green technology innovation efficiency is of great significance to enhance regional innovation capability and promote regional economic sustainable development. Based on the traditional DEA model for measuring the innovation efficiency of green technology, the undesired output and the “relaxation” of the factors are not considered. This paper takes the panel data of each province in 2008~2017 as a sample,evaluates the static and dynamic changes in the efficiency of green technology innovation in various regions of China in combination with the DEA-SBM model of undesired output and the global Malmquist-Luenberger index, and compares the efficiency of green technology innovation with the efficiency of pure technology innovation. Then the global spatial autocorrelation and local spatial autocorrelation are used to test the spatial correlation of green technology innovation efficiency between regions, and then the spatial econometric model is established to explore the influencing factors of green technology innovation efficiency. The research results show that the overall level of green technology innovation efficiency in various regions of China is not high, and most regions exhibit an increasing trend year by year, and the overall distribution pattern is “high in the east and low in the west”.The efficiency of pure technology innovation is better than that of green technology innovation. In most provinces, the total factor productivity of green technology innovation is increasing, and technological progress is the main factor of influence.Regional innovation efficiency has obvious spatial positive autocorrelation and spatial agglomeration effect, and the agglomeration effect is mainly reflected in the inefficient L-L quadrant and highefficiency HH quadrant.Improving technology market environment mechanism, expanding economic opening-up to the outside world, and optimizing the industrial structure have a positive role in promoting regional green technology innovation efficiency, while environmental regulation has a significant inhibitory effect on innovation efficiency development, and may be related to the crowdingout effect caused by the environmental policies in the short term.
参考文献/References:
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相似文献/References:
[1]秦倩. 绿色发展理念推动下中国绿色专利制度的构建[J].长安大学学报(社科版),2017,19(02):117.
Qin Qian. Construction of Chinese green patent system under the concept of green development[J].Journal of Chang'an University(Social Science Edition),2017,19(06):117.
备注/Memo
- 备注/Memo:
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基金项目:国家社会科学基金重点项目(18AJY014);安徽省高校自然科学研究项目(KJ2018ZD043);安徽财经大学校级课题(ACKY1703ZDA);安徽财经大学研究生科研创新基金项目(ACYC2017237)
作者简介:孙欣(1973-),男,安徽庐江人,教授,经济学博士。
更新日期/Last Update:
2020-01-06