研发要素流动、空间知识溢出与经济增长

R&D Element Flow,Spatial Knowledge Spillovers and Economic Growth

本文旨在考察研发要素的区际流动,能否通过空间知识溢出效应,促进中国的经济增长。在理论分析这一机制的基础上,本文以中国大陆30个省级行政区域为研究对象,运用多种空间计量分析技术,对其进行了实证检验。研究发现,研发要素的区际流动具有明显的空间溢出效应,且这一溢出效应对中国经济增长呈现显著的正向影响;考虑不同形式的空间权重矩阵以及模型可能存在的内生性以后,这一结果依然具有稳健性。本文结论为促进区域之间研发要素的合理流动,统筹区域创新发展,进而促进中国经济的可持续增长提供政策启示。

R＆D elements are important strategic resources used to insure successful implementation of China＇s innovation- driven strategy and to promote sustainable economic growth. China is stepping into the era of open innovation characterized by free R＆D element flow, reform of the household registration system, and accelerated integration of science and technology. Investigating the cross-regional flow of R＆D elements and its effect on economic growth is of great significance from both theoretical and empirical perspectives. Most of the research explores the effect of R＆D input or its externality on economic growth from a static perspective but ignores the dynamic flow of R＆D elements. On the contrary, we investigate the intrinsic mechanism of how the dynamic flow of inter-regional R＆D elements influences economic growth through spatial knowledge spillovers from a dynamic viewpoint. Thus, we provide policy insights for coordinating the development of regional innovation and implementing the strategy of innovation-driven development. On the basis of new economic geography theory, we introduce R＆D element flow into Fujita ＆ Thisse＇s （2003） knowledge innovation and diffusion models and construct a theoretical model that includes R＆D element flow, spatial knowledge spillovers, and economic growth. Our key distinctions from Fujita ＆ Thisse （2003） are listed as follows ： （ 1 ） Fujita ＆ Thisse （2003） simply equated factor mobility with spatial knowledge spillovers, ignoring their inherent relation mechanism. Instead, we introduce the flow factor of R＆D elements and put it into a unified analytical framework with spatial knowledge spillovers. （2） Based on the analysis of internal mechanisms in theory, we study 30 provincial-level administrative areas of the Chinese mainland （except Tibet because of incomplete data） to investigate the knowledge spillover effect on economic growth as induced by R＆D element flow. Considering the model, misspecification might have occurred had we not noticed the spatial correlation associated with R＆D element flows, as cross-provincial R＆D element flows are not mutually independent and the R＆D element flow of a province may be influenced by the economic activities of other provinces. We first test the spatial relevance of economic behavior statistically using spatial index Moran I, and the results show a significant correlation. As such, we use a spatial econometric analysis method that takes the spatial correlation of economic activity into account to establish the econometric model and to measure the knowledge spillover effect practically. To obtain the optimal fitted model and investigate whether different types of models can transform into each other, we construct a measurement model and test the influence machine empirically along the path of OLS-E SAR and SEM ]-SAC-SDM, as different models assume different spatial conduction mechanisms and represent different economic implications. Several results were found. First, there exist significant spatial correlations between Chinese provincial economic activities. Furthermore, both the direct growth effect and the spatial spillover growth effect of cross-provincial R＆D element flow are positive and statistically significant. Second, the growth effect of spatial knowledge spillovers accounts for more than half of the gross growth effect, and the growth effect of R＆D capital flow accounts for more than 10%. Based on these results, we suggest that local governments pay attention to not only local economic conditions but also the development strategy of surrounding areas at the policy level, actively set up a platform of regional coordination and strengthen exchange and cooperation. Additionally, to further break down regional barriers, we suggest that the local government improve the mechanism of cross-regional R＆D element flow and encourage the free flow of R＆D elements to bring the knowledge spillover effect into full play by deepening the census register system reform and strengthening science technology and finance systems.