R & D Spillovers Measure

Along with the development of the new economic growth theory, the role of R & D spillover effects has become increasingly concerned by various studies. Because traditional measure methods have various limitations, this paper adopts the latest spatial econometrics methods to measure this effect. With regarding Chinese 31 provinces, industry sectors and high-tech industries as the research objects respectively, this paper studies R & D spillover effects in the perspective of macro and middle level. On the basis of analyzing mechanism of this effect, some different measure models were built to put forward more accurate and effective measurement.Beginning with the externality of R & D activities, this paper firstly introduces the mechanism, the subject and the convergence effect of R&D spillover effects. By comparing traditional measurement methods with spatial econometrics method, this paper analyzes the limitation of the former and the applicability of the latter in measuring R&D spillover effects.Before measuring the R&D spillover effects, this paper carries out deep analysis and comparative studies on Chinese R & D input and output characteristics. R & D expenditure on GDP and scientific and technological activities personnel were selected as the core R&D input indicators. Patent application, patent grants and research papers were selected as the core R&D output indicators. Comparing Chinese R&D input and output level with developed countries, it is found that although there is a gap with the developed countries, but the gap narrowed year by year with the number of research papers in China ranking in the world the first place. As a more objective indicator, triadic patent is applied in comparing Chinese R&D output quality. It is necessary to transfer from big country in patent quantity to powerful country in patent quality for China. Through analyzing R & D input and output convergence effect between the 31 provincial-level regions in China, it is found that theδ-convergence andβ-convergence are very significant in R & D input activities, while the output of R & D activities are not always the case. Further researches imply that the lower efficiency of investment means the lower output efficiency, so it is also necessary to study the R & D spillover effect between different regions.It is carried out by using 31 provincial-level regions in China as object in perspective of macro level to research on R&D spillover effects. By using spatial panel econometrics methods, regarding 31 provincial-level regions of China data for the year 1998-2008 as the research object, this paper analyzes the R&D spatial spillover effect between these regions. According to R&D spillover characteristics, this paper redefines spatial weight matrix, and finds the optimal spatial weighting matrix which includes both economic and geographical distance factor. Meanwhile, from empirical comparison R&D funds come into the greatest contribution of the patent output lag period of 2. It is also found whether in direct or indirect way, R&D spatial spillover effects are very significant, and this spillover effect appeared M-A-R externalities. By dividing R&D funds into private investment and public investment in accordance with the source constitution, the accuracy of model estimation has risen markedly. It is also found private investment's contribution to the patent output was significantly higher than public investment, and in the direct way the former's spatial spillover effect is also larger than the latter.From this perspective of independent innovation, it is a strong practical significance to study local R & D spillover between industrial sectors. According to the characteristics of industrial sectors, R & D spillover can be studied from two dimensions, namely vertical and horizontal spillover, and vertical spillovers can be further divided into forward and backward spillover. This paper regards 33 industrial sectors of China between 1998-2008 panel data as the object, and analyzes the features of these two dimensions R & D spillover. The spatial matrix measuring vertical spillovers is transferred from I-O table, and the spatial matrix measuring horizontal is defined by technology distance invented by Jaffe in 1986. It is found that that the asymmetry of vertical spillover effects and the forward spillover is not significant, with the significance of backward spillover and horizontal spillover. The 33 industries are divided into high-tech industries and low technology industries according to the technical level, and the local R & D investment is found to exhibit the substitution effect with high-tech industry R & D investment in the level of horizontal spillover and the complementary effects with low-tech industries R & D investment in the backward and horizontal spillover.As the technology heights in industries, high-tech industries are the most important participants in R & D activities. This paper regards the 14 sub-sectors of Chinese high-tech industries during 1995-2008 as the research objects, and studies the R & D spillover effects in both the internal and international ways within the same framework. Through decomposing the mechanism for R & D spillovers and combining two factors of technology gap and concentration degree, we obtain an R & D spillover effects mechanism model of Chinese high-tech industries. By using of spatial econometrics method, we regress this SAR model and find some results, which include that a substitute relationship between the internal and international ways spillover and the industry factor play an important role in spillover effects. It is also found that different groups within the industry in R & D under different mechanisms show different characteristics of spillover effects.By studying the R & D spillover effect of China's provincial regions, industrial sectors and high-tech industry respectively, it is found that their respective R & D spillovers features and the role of influencing factors. On the basis of these conclusions, the paper puts forward some suggestions on how to effectively promote this kinds of R & D spillovers and enhance the role of R&D activities in improving economic development.