Abstract: Under the new development pattern, China is faced with huge challenges such as international instability, frequent health incidents, and fading demographic dividend. The economic development model driven by traditional factors is not sustainable. Innovation-driven development has gradually become an important source of high-quality economic development. How to effectively accelerate the construction of innovation system is the fundamental way to improve national innovation ability and competitiveness. Since the CPC Central Committee formally put forward the resolution to comprehensively promote the construction of the national innovation system with Chinese characteristics, the construction of the national innovation system has achieved considerable results. According to the statistics of the World Intellectual Property Indicators, China ranks the first in the world in the total number of R&D personnel and applications for patents, trademarks and industrial appearance. However, the rapid growth of individual innovation indicators does not mean that the national innovation system efficiency will be improved simultaneously. China still has a series of problems, such as poor coordination of innovation entities, scattered allocation of innovation resources and low quality of innovation output. Therefore, how to evaluate national innovation system efficiency scientifically has become a practical problem to be solved urgently. Unfortunately, the academic circle's understanding of this issue is still very limited, and the current evaluation of national innovation system efficiency is still lagging behind the practical needs of the construction of an innovative country. Under such circumstances, systematically constructing the index of the national innovation system efficiency and accurately describing its evolution trend, spatial distribution, regional differences and convergence characteristics are of great practical significance for objectively understanding the operation status of the national innovation system, systematically improving the overall efficiency of the innovation system, and accelerating the construction of an innovation-oriented country.
Based on the framework of “foundation-process-result”, this paper constructs a comprehensive index system of national innovation system efficiency from five aspects: innovation basis, innovation environment, innovation synergy, innovation openness and innovation quality. And this paper uses the global principal component analysis method and relevant data from 2009 to 2020 to measure the index of China's innovation system efficiency at the provincial level. Furthermore, the Dagum Gini coefficient and β convergence model are used to empirically analyze the spatial-temporal evolution trend, spatial differences and sources, convergence characteristics and speed of innovation system efficiency in China and the three regions. The results show that: First, the comprehensive level of national innovation system efficiency is not high. And there are serious problems of unbalanced, inadequate and uncoordinated spatial distribution, which is manifested as the gradient characteristics of “eastern region>central region>western region”. There is still a large room for improving national innovation system efficiency in the country and the three regions, and all of them show a steadily rising growth trend. Second, the spatial differences of national innovation systems efficiency show a fluctuating upward trend, and the intra-group differences and inter-group differences also present different increases in the three regions. The inter-group differences are always the main source of spatial differences, and the intra-group differences in the eastern region and the inter-group differences between the eastern and western regions are relatively large. Third, innovation system efficiency in China and the three regions all have typical characteristics of absolute and conditional β convergence, and the convergence speed in the western region is higher than that in the eastern and central regions. In the conditional β convergence after the introduction of control variables, the convergence rate of innovation system efficiency in the country and the three regions is significantly improved, and the convergence rate of the central and western regions is obviously faster than that of the eastern regions. Based on the research results, this paper puts forward policy implications from strengthening the construction of the national innovation system, paying attention to the spatial imbalance of innovation system development, and grasping the driving role of economic and social factors.

Key words: innovation system efficiency, Dagum Gini coefficient, β convergence, space-time evolution

摘要： 基于创新基础、创新环境、创新协同、创新开放和创新质量五个维度构建国家创新体系效能综合指标体系,运用全局主成分分析法及2009—2020年相关数据测算省际层面的创新体系效能指数,并通过Dagum基尼系数和β收敛模型对国家创新体系效能的时空演变趋势、空间差异来源及收敛特征进行实证分析。结果表明:全国及三大地区创新体系效能水平还不高,但呈现出稳步上升的态势,且存在“东高西低”的空间非均衡特征;国家创新体系效能的空间差异主要来源于组间差异,组内差异次之,超变密度最小,且东西部间的组间差异和东部地区的组内差异相对较大;全国及三大地区的创新体系效能均存在典型的绝对β收敛和条件β收敛,条件β收敛速度显著高于绝对β收敛速度,且呈现自西向东依次递减的分布特征。研究结果为系统提升国家创新体系整体效能、缩小区域创新体系效能差距,乃至加快创新型国家建设提供了一定启示。

关键词: 创新体系效能, Dagum基尼系数, β收敛, 时空演化