| The study of the phenomenon and the rule of regional innovation system is theimportant component of promoting regional innovation and is the important measures forrealizing the regional sustainable development and is also the immportant steps s torealize national regional development strategy. It is necessary to establish regionalinnovation system that can not leave the regional innovation investment. Now, eachregion in China with r&d investment as the main sign of regional innovative investmenthas a improved greatly. Regional innovation direct performance, namely the regionalinnovation input and output relationship, has been studied deeply for the politics, theindustry and the academic circle. There appear a large number of research results, andsome useful conclusions are obtained. But, some questions,for examlpe which kinds ofinfluence will be produce for regional innovation investment to Chinese macroeconomicand regional innovation investment indirect performance and its evaluation, have yet tointroduce paid enough attention.In this paper, study is from that point. The methods in this paper include spacestatistical, space econometrics, space filtering, stochastic frontier model withheterogeneous effects, percentile regression, non-parametric regression, panel unit root,panel cointegration, macro cointegration econometric model and other modern measuringmethod. After completion of the direct performance of regional innovation, transmissionmodel from regional innovation to national macro economy development has been made,and the China’s macro cointegration econometrics model has also been established.Through the two model connection, the influence of regional innovation investment toour country main macroeconomic variables has been analysed. The paper investigatesthe regional innovation indirect performance under the background of national macroeconomic development, which is the innovative points of this paper. The mainconclusions are as follows:Firstly, the study finds that the spatial correlation of Chinese regional innovationactivities is very apparent and that the aggregation trend of innovation in eastern regionexists. Gini coefficient analysis shows that the space concentration trend of China’sregional innovation has been increased. Overall, about forty percent of the provincialinnovation activities appear similar high space correlation form. Research also shows thatin the regional administrative center of300kilometers, inventive activities present a strong positive space correlation from. At the same time, when the distance expands toabout2800kilometers, regional innovation activities present a significant degree ofnegative correlation. China’s regional innovation exists conditions threshold convergenceor conditions convergence effect. Panel threshold regression model solves the problem ofendogenous convergence club in the convergence theory.Secondly, the study finds that there exists strong spatial correlation in proxiedvariables of Chinese regional innovation. With spatial filtering method, the spatialcorrelation can be effectively eliminated and the variables can be applied to traditionalregression model. In the model of this paper, there exists co-integration relationshipamong proxied variables of input and output of Chinese regional innovation.Through theChinese regional knowledge production function, the study finds that research anddevelopment expenditure, science and technology activities, the total amount of foreigninvestment, regional import, regional itself and neighbor area knowledge stock are thesix main factors that affect the regional innovation output significantly. We also findthat the regional knowledge spillovers lie in two-way effects by further analysis ofChinese regional knowledge spillover.Thirdly, the study finds that proxied variables of the environment factors that affectChinese regional technological innovation efficiency are stable variables, which canguarantee the co-integration relationship in the regression model. Chinese regionaltechnology innovation efficiency shows the space distribution characteristics which theeastern China has high efficiency, China’s central has middle efficience and westernChina has low efficiency. The western China with low efficiency of technologicalinnovation has a higher growth rate, and there exists sign of catching-up in western areaof technology innovation. Factors affecting regional technological innovation efficiencyin the national and the China’s three big areas vary slightly. Innovation agencyparticipation in strength and regional market openness are the main factors that affecttechnological innovation efficiency in the national and the China’s three big areas. Otherfactors that affect technological innovation efficiency in the national and the China’s threebig areas are not identical.Fourthly, the China regional─macro econometric model for the study of Chineseregional innovation macro performance has three characteristics, which include thatmodel according to SNA system is set up and is a supply and demand of the dual pilotannual macroeconometric model, behavior equation design depends on dual drive of theeconomic theory and data characteristics, the model is a co-integration econometric model. Analysis of macro economic effect of the r&d investment in the Chinese threeregions shows that: the effect of the three regions r&d input to the same extent increase onthe eight main macroeconomic variables are the same. The sort of the influence of thethree regions r&d input increase on the eight main macro economic variables is almostthe same also. Analysis of macro economic effect of the8regional r&d investment showsalso a similar conclusion. Scene analysis finds that increasing the Chinese regional r&dinvestment is beneficial to Chinese urbanization development, to increase income inChina. |
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