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R&D资源错配对工业绿色技术创新效率的影响研究——基于数字经济的门槛效应
Research on the impact of R&D resource mismatch on the efficiency of industrial green technology innovation: Based on the threshold effect of digital economy
R&D资源的不合理配置制约着绿色技术创新效率的提升,严重阻碍中国绿色高质量发展的进程。基于2011—2020年中国30个省级行政区的面板数据,研究R&D资源错配以及数字经济对工业绿色技术创新效率的影响。将代表环境收益的工业固体废物无害率引入工业绿色技术创新效率的测度指标体系,运用超效率SBM模型测算中国工业绿色技术创新效率,并测算R&D资源的错配程度;构建双向固定效应模型,回归分析R&D资源错配对工业绿色技术创新效率的影响;构建门槛效应模型,回归分析数字经济对R&D资源错配、工业绿色技术创新效率起到协调作用的门槛效应。结果表明:(1)中国30个省级行政区的工业R&D资源均表现出配置匮乏的问题;(2) R&D资源错配会显著抑制中国工业绿色技术创新效率的提高;(3)在数字经济的调节作用下,R&D资源错配会对工业绿色技术创新效率呈现“U”型的影响机制,当数字经济达到门槛值后,R&D人员和资金都会从抑制效率提高转变为促进效率提升。本研究丰富了绿色技术创新效率的研究思路,并为加快数字经济发展、优化资源配置、提高工业绿色技术创新效率提供了实证依据与政策建议。
Industrial green technology innovation is an important link to promote green development and harmonious coexistence between man and nature, and it plays a vital role in promoting the development of real economy and promoting new industrialization. However, the unreasonable allocation of R&D resources restricts the improvement of the innovation efficiency of industrial green technology and seriously hinders the process of China's green development. With the rapid development of digital technology, digital economy has achieved unprecedented development, and it has a profound impact on the mode of production and production factors. Based on the panel data of 30 provincial-level regions in China from 2011 to 2020, this paper studied and measured the impact of R&D resource mismatch on innovation efficiency of industrial green technology, as well as the impact mechanism of digital economy development on R&D resource mismatch and innovation efficiency of industrial green technology.
Introducing the harmless rate of industrial solid waste representing environmental benefits into the measurement index system of the innovation efficiency of industrial green technology, this paper used the super efficiency SBM model to estimate the innovation efficiency of China's industrial green technology, and calculate the degree of mismatch of R&D resources by modeling. A two-way fixed effect model of time and individual was established to analyze the influence of R&D resource mismatch on innovation efficiency of industrial green technology. A threshold effect model was built to regress and analyze the threshold effect that digital economy plays a coordinating role in R&D resource mismatch and innovation efficiency of industrial green technology.
The results show that: (1) The industrial R&D resources in 30 provincial-level administrative regions in China have shown a shortage of allocation, and the efficiency of industrial green technology innovation shows strong regional heterogeneity; (2) The mismatch of R&D personnel and capital will significantly inhibit the improvement of China's innovation efficiency of industrial green technology. The regression results showed that compared with R&D personnel, R&D capital mismatch has a stronger and more significant inhibitory effect on the efficiency of industrial green technology innovation; (3) Under the moderating effect of digital economy, R&D resource mismatch has a U-shaped influence mechanism on the efficiency of industrial green technology innovation. When the digital economy reaches the threshold value, R&D personnel and capital will change from inhibiting the improvement of efficiency to promoting the improvement of efficiency. The threshold value of R&D personnel is higher than that of R&D capital, but the positive promotion coefficient after reaching the threshold is much larger than that of R&D capital.
This paper will enrich the research ideas on the innovation efficiency of industrial green technology, and provide empirical basis and policy recommendations for accelerating the development of the digital economy, optimizing resource allocation, and promoting the efficiency of industrial green technology innovation.
R&D资源错配 / 工业绿色技术创新效率 / 数字经济 / 固定效应 / 门槛效应
R&D resource mismatch / innovation efficiency of industrial green technology / digital economy / fixed effect / threshold effect
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在长三角更高质量一体化的战略背景下,绿色技术创新作为绿色发展和创新驱动两大国家战略的结合点,已成为长三角区域绿色转型发展的重要引擎。通过构建包含非期望产出的超效率SBM-DEA模型,对2010—2017年长三角区域核心城市的绿色技术创新效率进行测度,并研究其时空演化格局和驱动因素。结果显示：① 在时序演变上,长三角区域的绿色技术创新效率呈现“W”型变化特征;② 在空间演变上,长三角东南部地区的绿色技术创新效率相对稳定,而中部、西南部变动明显,整体呈现连片集聚发展特征;③ 在空间关联上,长三角区域绿色技术创新效率的区域空间联系逐渐由“极化效应”转变为“涓滴效应”,泰尔指数和基尼系数整体表现为与时序演变相反的“M”型变化特征;④ 基于长三角区域绿色技术创新投入、产出及效率测算结果,将各城市划分为高高高、高高低、高低低、低高高、低低高和低低低六种类型,进一步揭示了长三角区域绿色技术创新发展路径的区域差异;⑤ 驱动因素分析结果表明,环境规制、经济发展、产业结构、对外开放和人力资本皆对长三角区域整体的绿色技术创新效率有着显著的正向促进影响,但创新支持具有显著的负向溢出效应。
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The increasing investment in R&D and stagnant or even retrogression of total factor productivity severely restricted the high-quality development of Chinese economy. On the basis of R&D resources allocation, the thesis introduces the resource misallocation method into knowledge production function and measures the distorted allocation of R&D funds and personnel in China's innovative production system with the use of the panel data of China’s 30 provinces and cities from 2000 to 2016 （except Tibet, Hong Kong, Macao and Taiwan）. The thesis also studies the effect of distorted allocation of R&D resources on total factor productivity, and the threshold effect of the corrective action existed in the distorted allocation of Chinese R&D resources. The research results show that, firstly, excessive allocation of funds and insufficient allocation of personnel exist in China's R&D resources. Secondly, the distorted allocation of R&D resources restricts the growth of total factor productivity, and the negative effect of the distorted allocation of R&D funds is greater. Thirdly, innovation environment and opening-up have a positive effect on improving total factor productivity, while government policy intervention has significantly restricted total factor productivity growth. Lastly, human capital can absorb excessive R&D funds when it reaches a certain level, but most provinces and cities do not reach this threshold level. To optimize the allocation of R&D resources and give play to its positive promoting effect on total factor productivity, a long-term mechanism for allocating R&D resources dominated by the market should be established to improve the rational flow of R&D resource elements through optimizing innovation environment and improving informatization level. Meanwhile, evaluate the effectiveness of the government's R&D fund allocation policy, and constantly improve the fiscal and tax policy support rules and methods of R&D funds. To play the corrective role of human capital, education training and health investment should be increased, while talent quality and human capital level should be improved as well, and "human capital bonus" should be replaced by "demographic dividend".
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