管理评论 ›› 2021, Vol. 33 ›› Issue (1): 44-53,67.

• 经济与金融管理 • 上一篇    

我国科技金融效率的空间差异及分布动态演进

沈丽, 范文晓   

  1. 山东财经大学金融学院, 济南 250014
  • 收稿日期:2020-06-16 发布日期:2021-02-03
  • 通讯作者: 范文晓(通讯作者),山东财经大学金融学院硕士研究生
  • 作者简介:沈丽,山东财经大学金融学院教授,博士生导师,博士。
  • 基金资助:
    国家社会科学基金项目(16BGL052)。

The Spatial Difference and Dynamic Evolution of China's Science and Technology Financial Efficiency

Shen Li, Fan Wenxiao   

  1. School of Finance, Shandong University of Finance and Economic, Jinan 250014
  • Received:2020-06-16 Published:2021-02-03

摘要: 科技金融的高效率运行已经成为我国实现创新驱动发展的关键支点之一。为了适时调整和优化各区域科技金融发展模式,运用超效率SBM模型与Dagum基尼系数分解法对我国科技金融效率进行测算和区域差异分析,并基于空间因素的考量使用空间Kernel密度估计考察我国科技金融效率的分布动态演进。研究结果表明,我国科技金融效率的波动态势明显且空间分布不均衡,空间差异的主要来源是区域间差异;各区域效率分布均有不同程度的多极化趋势;东部、中部和西部地区科技金融效率的分布动态演进具有空间溢出性,相比之下东北地区的空间溢出性并不明显。据此,提出了缩小科技金融效率区域差异以及推动我国区域科技金融协同发展的政策建议。

关键词: 科技金融效率, 空间差异, 分布动态, Kernel密度估计

Abstract: The efficient operation of science and technology finance has become one of the key fulcrums of China's innovation-driven development. In order to timely adjust and optimize the development modes of science and technology finance in various regions, super efficiency SBM model and Dagum Gini coefficient decomposition method are used to calculate and analyze the regional differences of the efficiency of science and technology finance in China. Based on the consideration of spatial factors, spatial Kernel density estimation is used to investigate the distributed dynamic evolution of the efficiency of science and technology finance in China. The results are as follows:The efficiency of science and technology finance in China fluctuates significantly and its spatial distribution is unbalanced, the main source of spatial difference is inter-regional difference; the efficiency distribution of each region has the multi-polarization trend of different degrees; in the eastern, central and western regions, the spatial spillover exists in the dynamic evolution of the distribution of science and technology finance efficiency, while the spatial spillover is not obvious in the northeast. Based on this, this paper puts forward policy suggestions on how to reduce the regional differences in the efficiency of science and technology finance and promote the coordinated development of science and technology finance in China.

Key words: science and technology financial efficiency, spatial difference, distribution dynamic, Kernel density estimation