The Relations Of China’s R&D Inputs And Outputs Based On PVAR And SPDM Models

In recent years, our country has higher economic growth, however, this is a kind of extensive growth excessively depending on investment drive and consumption of resources. This growth mode will naturally bring some problems, such as environment pollution or the lack of energy, and these problems will gradually become the bottleneck of the economic growth in China. Therefore, how to change our economic growth way is particularly important, and in the conversion process, science and technology play an irreplaceable role. As a developing country, China’s scientific and technical level is still lower in the world, especially the ability of independent innovation. So, it’s important to strengthen the research and development ability and improve the level of science for the target of promoting our country’s economic development and enhancing China’s science and technology competitiveness. There are many problems which possibly restrict the development of China’s economy and affect it’s international position, such as the lower efficiency of R&D inputs, unbalanced level of regional innovation and the harder process from R&D outputs to new products. Therefore, in this period relying on technology progress, it appears very important to coordinate different departments’ investment and achieve innovation spill and resource sharing in all regions.In view of science and technology has irreplaceable advantages, its innovation level gradually becomes the measure of a country embodies the comprehensive strength, and the competition between countries more and more performance for the competition of technology capability. R&D investment is the main input factor in science and technology innovation activities, is the energy of scientific and technological progress, and R&D level directly determines a national science and technology innovation level. Therefore, with R&D activities gradually become the focus of attention of the countries, many problems such as the efficiency of R&D input, the level of R&D output and the coordinated development of regional R&D activities, have became the focus of domestic and foreign scholars.Firstly, on the basis of review of domestic and international research literature, combined with the comparative analysis of the relevant variables’ status, and in allusion to the existence of the blank or inadequate in research methods and contents in the field of R&D inputs and outputs, we introduce the PVAR model and the spatial panel data model to analyze the problem of R&D inputs and outputs in China. In this paper, we make R&D expenditures and R&D personnel full-time equivalent as R&D input factors, patent applications as the measure mean of the level of regional R&D output, an empirical analysis of the1998-2010panel data on China’s30provinces (except Tibet).Among them, financial input is divided into three departments, including the scientific research institutions, large and medium-sized industrial enterprises and universities, in order to measure each departments’ R&D efficiency and the relationships among different departments. PVAR analysis regards all variables as endogenous variable, does not distinguish between the independent variable and the dependent variable, through this method we can get the short-term and long-term effects between R&D input and output variables. The space panel data model analysis can discuss whether there is space connection and the direction and size of this association in R&D activities’ input and output variables in space range. Through the two empirical analysis methods, this paper comes to these conclusions:Firstly, PVAR methods have not applied to the research on the relationship of China R&D input and output at present, and by establishing the PVAR model, using variance decomposition and impulse response function analysis method, we can get the empirical results:Three departments’ funds input have impact on R&D output, compared with the output effect of scientific research institutions and universities’fund inputs, the enterprise’input on the contribution of output is greater; There are interactions between enterprise funds input and universities、research institutions’ funds input. The output contribution rate of R&D personnel in the short term doesn’t come out, while its output elasticity is very large in the long run. The preliminary patent applications and the current patent applications have same effect, the three departments’preliminary funds investment and the current investment also have same effect. R&D personnel input and funds investment also have certain effect. By above the empirical results, it is known that the output effect of funding inputs and human inputs are not the same, the difference in output elasticity of three departments’ funds investment are big, R&D input and output factors exist intricate relationships, and thus, the government’s R&D decisions should have specific aim and time limit.Secondly, by using the SLM、SEM and SDM in the econometrics, we compare the output elasticity of three departments’fund inputs and human input in R&D activities, and emphatically analyzes the space spillover effect between these elements. In consideration of space factor, scientific research institutions and universities’funds’contribution to patent output is small, enterprise funds’output elasticity is bigger. R&D personnel is also a significant positive role in the patent output; There are positive spillover effects between adjacent areas’patent outputs, and the adjacent areas’fund inputs have spatial effects, but the R&D personnel inputs’spatial effect is not significant. Combined with the results of the analysis of spatial effects, we can easily find R&D activities of each province are not completely isolated, the government should pay full attention to the space effect between different provinces and coordinate the development of inter-regional R&D activities.