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中国省际绿色技术创新效率测度及影响因素研究
引用本文:张在旭,黄卓琳.中国省际绿色技术创新效率测度及影响因素研究[J].资源与产业,2020,22(6):1-8.
作者姓名:张在旭  黄卓琳
作者单位:(1中国石油大学(华东)经济管理学院,山东 青岛 266580;2中国石油大学胜利学院 文法与经济管理学院,山东 东营 257061)
基金项目:国家社会科学基金项目(17BGL176);青岛市哲学社会科学规划项目(QDSKL1801045);中央高校基本科研业务费专项资金(17CX06052B)
摘    要:文章基于2011—2017年中国30个省份面板数据,运用super-SBM模型对绿色技术创新效率进行测算,并利用ML指数对绿色技术创新效率进行动态分析,最后通过空间滞后模型分析影响效率的关键因素。研究结果表明:中国绿色技术创新效率呈逐渐增长的趋势,但整体效率偏低,有较大进步空间;中国绿色技术创新效率存在明显区域差异,呈现由东部向西部递减的格局;绿色技术创新水平的提高是技术效率和技术进步共同贡献的结果;产业结构、区域开放程度和教育水平对绿色技术创新效率产生积极的正向影响,环境规制和研发投入强度对绿色技术创新效率影响不显著。

关 键 词:绿色技术创新  super-SBM模型  空间计量模型  影响因素  
收稿时间:2020-04-13
修稿时间:2020-06-16

MEASUREMENT AND FACTORS OF CHINA'S PROVINCIAL GREEN TECHNICAL INNOVATION EFFICIENCY
ZHANG Zaixu,HUANG Zhuolin.MEASUREMENT AND FACTORS OF CHINA'S PROVINCIAL GREEN TECHNICAL INNOVATION EFFICIENCY[J].Resources & Industries,2020,22(6):1-8.
Authors:ZHANG Zaixu  HUANG Zhuolin
Affiliation:(1. School of Economics and Management, China University of Petroleum, Qingdao 266580, China; 2. School of Laws and Economic Management, Shengli College, China Petroleum University, Dongying 257061, China)
Abstract:This paper, based on panel data of China's 30 provinces during 2011 to 2017, uses super-SBM model to measure the green technical innovation efficiency, which is dynamically analyzed by means of ML index. Spatial lagging model is used to study the key factors of the green technical innovation efficiency. China's green technical innovation efficiency shows an increasing trend, low but leaving room for improvement, also varies with regions, decreasing westward. Improvement of the green technical innovation level is a mutually attributed by technical efficiency and technical advances. The green technical innovation efficiency is positively influenced by industrial structure, regional openness and educational level, little by environmental regulations and research and development input.
Keywords:green technical innovation  super-SBM model  spatial quantitative model  factors  
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