An Empirical Research Of The Impact Of R&D On Technical Progress In China’s High-tech Industry

Since the reform and opening-up of China, the High-tech industry has being developed quickly. It is becoming the backbone and key power of China’s economy and social development gradually, and it is also a concrete manifestation of innovation-driven strategy. After a rapid development of thirty years, it has become one of the most dynamic and foundational industry in China. The High-tech industry is highly technology-intensive and an important symbol of advanced productivity. The level and pace in technology improvement are related to production and innovation capacity of the whole industry even the country directly. Therefore, technical progress is just the subject of this study. Total Factor Productivity (TFP) is considered as an important indicator to measure the technical progress and its growth is of significance to the High-tech industry development.Existed literature has made a full research on this subject from various perspectives which providea good reference value for the study of this paper. Based on the analysis and reorganization of previous achievements, the paper focuses on investigating the main driving forces from the investment perspective of our own research and development activities. Internal R&D, human capital and technology introduction are three key factors theoretically. So in reality, whether those factors are effective in promoting TFP growth or not? Is the technical progress sustainable in the current model? What’s the mechanism of action both in short and long run? By constructing econometric models, we study the contributions of all elements to technical progress and put forward the corresponding policy recommendations.The paper consists of five parts. The first part is the introduction, including the background and significance of the subject, literature review, concept definition and the research framework; The second part made a tease and review of relevant theories, laying the foundation for empirical research; In the third part, the rate of TFP change is measured and decomposed based on the DEA; In the fourth part, by constructing a Co-integration and Error Correction Model, we explore the Long-term Equilibrium Characteristics and Short-term Fluctuation Effects of technical progress under the influence of R&D, human capital and technology input. The last part is the conclusions and policy recommendations. We mainly obtained the following two conclusions:(1)Technical progress is the main driving force of TFP change in China’s High-tech industry, and technical efficiency forms the prime cause that leads to the differences among the regional rates of TFP growth. From the dimension of time, the rate of TFP growth is quite large over the whole period, but it shows a shake and downward trend in a long interval. From the dimension of region, all TFP in28provinces are improved and the growth rates decrease in a row in western and middle and eastern regions. The unbalance in growth rates tells that there existing a astringency in the process of TFP growth. Compared with technical efficiency, technical progress has stronger impact on TFP growth both in the points of time and region.(2)R&D expenditure and technical investments increased the TFP, while the return of human capital possesses an uncertain nature obviously. On average among the whole country, R&D and technical introduction have a positive influence to TFP both in long-term or short-run, and the contribution of technical investment are bigger than that of R&D. In the long term, the elasticity of R&D in high R&D expenditure region is not significant while low R&D expenditure region has the biggest R&D elasticity. Elasticities of technical investment are all significant in three regions. Its return in the high R&D expenditure region is the largest one and technical progress mainly depends on technical investment, not on R&D expenditure. In the short term, the elasticity of R&D in low R&D expenditure region is not significant while the return of technical investment in this region is obvious and technical investment is the main support of TFP growth. On the contrary, R&D expenditure is the most important factor in the high R&D expenditure region and the middle R&D expenditure region. The adjustment speed of R&D activity in the middle R&D expenditure region is fastest and the process of technical progress can return to the equilibrium state in about three years. In short, the R&D activity of the middle R&D expenditure region in China’s high-tech industry is more steady and has a higher efficiency. The main innovation of this paper is the introduction of technology investment in import and absorption to the model which can measure the absorption capacity to foreign technology in China’s High-tech industry directly. Then, in the processing of variable, TFP_R calculated from DEA was not used as the dependent variable in the empirical model. Instead, the paper did a multiplicative process year by year to get the TFP index representing the technical progress which has a more clear economic implications. Finally, the paper divided all provinces to three regfons according to their R&D stocks, not according to traditional administrative division, and the result has more directive significance. The shortage is that the calculation of a few indices may lead to inaccurate results. Besides, the paper did not include comparative studies of various industries, the whole manufacturing industry and that of developed countries. Due to the different focus, the paper failed to consider the impact of import and export, foreign R&D and policy. All mentioned above are worth a further study.