京津冀城市绿色创新效率时空差异及影响因素分析

Comparative Analysis of the Time-space differences and Influencing Factors of Cities’ Green Innovation Efficiency in Beijing-Tianjin-Hebei

经济的快速增长导致资源匮乏、环境恶化等全球性问题不断加剧,国际社会越来越认识到绿色创新的重要性,同时,作为创新驱动和绿色发展两大国家发展战略的结合点,绿色创新必将成为京津冀地区以及全国绿色转型发展的重要引擎和关键抉择。在梳理现有文献的基础上,以京津冀13个城市为主要研究对象,基于2008~2017年13个城市的面板数据,运用考虑非期望产出的SBM模型测度绿色创新效率,并利用全局莫兰指数分析绿色创新效率空间相关性及空间集聚特征,最后采用空间计量模型研究绿色创新效率的影响因素。研究发现,京津冀城市绿色创新效率总体呈波动上升态势,效率水平的高低与京津冀地区创新、环境政策紧密相关,资本投入力度和废水、 SO2排放水平等非期望产出冗余是绿色创新效率未达到DEA有效状态的关键制约因素。城市间绿色创新水平差距明显,从时序上来看差距有明显缩小趋势,河北省多个城市绿色创新能力提升空间较大。城市绿色创新效率的全局莫兰指数均为正值,绿色创新效率具有空间集聚特征。通过空间分析来看,经济发展水平、政府资助力度、城市信息化程度、城市文化水平和产业结构等因素均对绿色创新效率有正向驱动作用,但京津冀的对外开放水平受地区绿色创新发展程度作用对绿色创新效率的提升影响效果不显著。鉴于研究结论,本文从扶持政策、产业结构、人才培养、创新协同等方面对京津冀城市绿色创新效率的提升提供了一些对策建议。

The rapid economic growth has led to global problems such as the lack of resources and environmental degradation. The international community is increasingly aware of the importance of green innovation. At the same time, as a combination of innovation-driven and green development strategies, green innovation will surely become an important engine and key choice for the Beijing-Tianjin-Hebei region and the country’s green transformation. On the basis of combing the existing literature, 13 cities are the main research objects. Based on the panel data of 13 cities in 2008-2017, the SBM model considering undesired output is used to measure the efficiency of green innovation, using Global Moran index analyzes the spatial correlation and spatial agglomeration characteristics, and finally uses the spatial measurement model to study the influencing factors. The study has found that the green innovation efficiency of Beijing-Tianjin-Hebei is generally fluctuating, the level of efficiency is closely related to the innovation and environmental policies of Beijing-Tianjin-Hebei region, capital input and undesired output redundancy such as wastewater and SO2 emission levels are key constraints to the failure of green innovation efficiency to reach DEA’s effective state. There is a clear gap in the level of green innovation among cities. From the perspective of timing, the gap has been significantly reduced. There is a large room for improvement to many cities in Hebei Province. The Global Moran index of urban is positive, and the green innovation efficiency has spatial agglomeration characteristics. Through the results of spatial analysis, factors such as economic development level, government funding, urban informatization, urban cultural level and industrial structure all have positive driving effects on green innovation efficiency, however, the effect of the level of opening up by the degree of development of regional green innovation, on the improvement of green innovation efficiency is not significant. In view of the research conclusions, this paper provides some suggestions for the improvement from the aspects of support policy, industrial structure, talent cultivation and innovation coordination.