关键词: 绿色化协同创新, 新旧动能转换, 经济增长, 非期望产出超效率SBM模型, 动态空间计量

Abstract: Based on the unexpected output super efficiency SBM model, this paper uses the input-output data of 30 provinces (autonomous regions and municipalities) in China from 2010 to 2017 to calculate the regional industrial green collaborative innovation efficiency and the conversion index of old and new growth drivers. On this basis, it uses the dynamic spatial model based on the economic characteristic spatial matrix to analyze the impact of industrial green collaborative innovation and the conversion of old and new growth drivers on China?s regional economic growth. We find that: The improvement of green collaborative innovation efficiency can promote local economic growth in the long term and short term, while for the surrounding areas, it can promote their economic growth in the short term and inhibit the economic growth in the long term. The improvement of the old and new growth driver conversion index will inhibit local economic growth in the short term and promote it in the long term; for the surrounding areas, it will promote the economic growth in both the long term and the short term. Industrial green collaborative innovation and the conversion of old and new growth drivers exert some or all of the economic growth effects through the interaction of supply and demand. This paper aims to reveal the impact and mechanism of China?s industrial green collaborative innovation and the conversion of old and new growth drivers on regional economic growth, which is of important practical significance to realizing the green transformation and high-quality development of China?s regional economy. 

Key words: Green Collaborative Innovation, Conversion of Old and New Growth Drivers, Economic Growth, Unexpected Output Super Efficiency SBM Model, Dynamic Spatial Metering