Effect Of China 's Provincial R & D Space Overflow

To speed up the transformation of economic development patterns, thefundamental way out is the independent innovation, R&D activities are the source ofindependent innovation. Under the background of the Chinese provincial characteristicsof spatial distribution of R&D activities? Whether China’s provincial R&D activitieshave space overflow? R&D spillover mechanism have obvious difference between theprovinces domain? This paper starting from the external thought of romer’s factors ofproduction, based on knowledge production function and the endogenous economicgrowth theory base, using spatial statistical techniques, on the scale of China’sprovincial R&D spillover effect to study these problems:(1) Provincial R&D activities in China has a tendency to spatial agglomeration.R&D activities output domain is highly concentrated in a limited number of provinces.Innovation of innovation activities occurred in the coastal province area, especially inShanghai as the center of the Yangtze river delta region, guangdong as the core of thepearl river delta region and Beijing as the core of the bohai rim region.(2) Use exploratory data analysis (ESDA) preliminary analyzes the spatialdependence and spatial heterogeneity of R&D activities. Global spatial autocorrelationMoran’s I index shows that2005-2012provincial R&D activities are highly significantspatial autocorrelation, provincial R&D activities exist interaction; Local spatialautocorrelation detection with Shanghai as the center of the Yangtze river delta regioncluster marked characteristics for high level R&D activities, and its neighboringprovinces domain exists positive correlation, the relationship between fujian and anhuiadjacent to the low level of provincial R&D activities, such as for LH (low R&Dactivity levels-high spatial lag) atypical provincial; Western province of xinjiang andInner Mongolia etc fields marked characteristics of LL (low level of R&D activities-low spatial lag) cluster,; In west sichuan is a typical province area for HL (high-lowlevel of R&D activities space lag) provincial.(3) The deterministic data analysis method (CSDA) empirical studies show thatR&D spillover space exists, namely provincial R&D activities exist spatial dependence.Findings suggest that on the R&D activities in the neighbouring province of domainknowledge production for local R&D activities play an important role, under thecondition of other conditions unchanged, every1%increase R&D nearby provincialoutput, around the region’s R&D output will be increased by0.3159%; R&D activity space overflow depend on human capital in the region.(4) The provinces domain of human capital and R&D input level on the impact ofR&D output has a bigger difference, the provincial R&D activities are spatialheterogeneity. GWR model, the spatial differences into consideration, the result showsthat although the contribution of R&D investment on R&D output stability, theinfluence of human capital on R&D output has significant regional differences, therelatively less developed western region does not have enough absorption ability tolearn, digest and absorb new knowledge. Based on the above study found that R&Ddevelopment countermeasures: briefly to enhance investment in R&D, multi-channel toraise funds; Attaches great importance to the education development, improve theoverall quality; Cultivate good R&D cooperation environment, build communicationplatform of R&D; Adjust measures to local conditions, implement differentiationstrategy of R&D.