创新转化效率、要素禀赋与中国经济增长

Innovation Transformation Efficiency,Factor Endowments,and China’s Economic Growth

党的二十大报告指出高质量发展是全面建设社会主义现代化国家的首要任务。研究中国各地区从“要素驱动”向“创新驱动”转换的动态分布特征,对于促进中国经济高质量发展具有重要的理论和现实意义。鉴于此,本文首先构建理论模型分析创新转化效率、要素禀赋对经济增长的影响机制,同时采用修正后的三阶段DEA模型和熵权—TOPSIS方法,分别测算2003~2016年中国281个城市创新转化效率和要素禀赋。在考虑内生性问题的情况下,使用动态面板门槛模型对理论分析得到的结论进行验证。研究发现,中国各城市创新转化效率差异较大,在考虑环境变量等因素后,综合技术效率下降。创新转化效率和要素禀赋对经济增长的影响存在门槛效应,要素驱动向创新驱动转换过程中,经济增长速度放缓。中国大部分城市动能转换的动态分布特征是从要素驱动型区域进入结构转换型区域,其中小部分城市最终到达创新驱动型区域。中国东部省份多数城市动能转换类型为创新引领型和创新突破型,大多数创新滞后型城市分布在中、西部省份。

The 14 th Five-Year Plan period is the first five years of China’s efforts to achieve its second century goal, and it is an important period for China to carry out the conversion of new and old driving forces and upgrade its economic structure. In the context of the innovation-driven development strategy, it is of great theoretical and practical significance to study the dynamic distribution characteristics of the conversion from “factor-driven” to “innovation-driven” in various regions of China to promote the high-quality development of China’s economy. In view of this, this study first constructs a theoretical model to analyze the mechanism of the impact of innovation transformation efficiency and factor endowment on economic growth. The model covers factors of production, R&D factors, innovation transformation processes, factor flows and endowment structures, intersectoral utility levels, and output growth. The revised three-stage data envelopment analysis(DEA) model and entropy-TOPSIS method are used to measure the innovation transformation efficiency and factor endowment of 281 cities in China from 2003 to 2016. The conclusions obtained from the theoretical analysis are validated using a dynamic panel threshold model, considering endogeneity issues. The study finds that the innovation transformation efficiency varied considerably across Chinese cities, with the comprehensive technical efficiency declining after accounting for environmental variables and other factors. There is a threshold effect on the impact of innovation transformation efficiency and factor endowments on economic growth. When innovation transformation efficiency and factor endowment are below the threshold, factor-driven is the main driving force of economic growth. When innovation transformation efficiency and factor endowments are above the threshold, the innovation-driven is the main driving force of economic growth. When the efficiency of innovation transformation is above the threshold and the factor endowment is below the threshold or when the efficiency of innovation transformation is below the threshold and the factor endowment is above the threshold, economic growth slows down during the transition from factor-driven to innovation-driven. The region types are further classified according to the thresholds measured by the empirical results. Most cities in the eastern provinces are located in innovation-driven regions. Most cities in the middle and western provinces are located in factor-driven regions. The dynamic distribution characteristic of driving force transformation in most Chinese cities is characterized by conversion from factor-driven regions to structural transformation regions, with a small number of cities eventually reaching innovation-driven regions. Most cities in China’s eastern provinces are the innovation-led and innovation-breakthrough type, with most of the innovation-lagging cities located in the middle and western provinces. The following policy recommendations are provided based on the findings of this study. First, there is a threshold effect on the impact of innovation transformation efficiency on economic growth. Before breaking through the threshold, incentive policies to promote innovation transformation efficiency should be introduced in conjunction with the level of local factor endowment to give sufficient room for error in innovation transformation. Second, with reference to the rule of the evolution of driving force transformation in Chinese cities, when a city’s factor endowment and innovation transformation efficiency are both below the threshold, it should first focus on improving the factor endowment. When a city’s factor endowment is above the threshold and the efficiency of innovation transformation is below the threshold, the economy is in the process of driving force transformation. At this point, expectations of a slowdown in economic growth should be factored into economic development planning. Here, an innovation-driven development strategy should be implemented in depth to avoid reverting to the old path of high pollution, high energy consumption, and low efficiency externally driven economic development, not to mention the pursuit of rapid short-term economic growth. Third, as the dynamic distribution of dynamic energy conversion in cities within the East, Middle, and Western regions is very different, policy formulation should be city-specific. A peer-to-peer approach should be used to pair cities in the east that have higher levels of innovation transformation efficiency and factor endowment with cities in the middle and west that are lagging behind in innovation. The advanced technology and experience of innovation-led and innovation-breakthrough cities in the east should be used to improve the level of industrialized development and efficiency of innovation transformation in central and western cities and promote inter-regional co-development.