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.

Key words: green technical innovation, super-SBM model, spatial quantitative model, factors

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