| During the second half of the20th century, the. high-tech industry developed rapidly as a knowledge-intensive and technology-intencive industry. It also contributed to adjusting the industrial structure and upgrading the product technology for the countries at the same time. What’s more, the high-technology industry has become an important driving force of promoting the economic growth. So its development affect the country’s position and role of the world economic structure directly. At present, Chinese high-tech industry has become the industry with the most rapid growth among the national economy. However, the growth of Chinese high-tech industry mainly rely on the huge investment, not the increasing of the efficiency. Considering that the technical innovation is important to the development of high-tech industry, so increasing the efficiency of the technology innovation is the key to improve the whole industry’s efficiency. This paper focus on the following several aspects to analysis the technology innovation efficiency of national high-tech industry.Firstly, the. paper defines the concept of high-tech industry, elaborates its characteristics, and illustrates the definition of technological innovation efficiency as well as its measurement. This paper compares the parametric methods and the non-parametric methods to measure the efficiency, then selects the three-stage DEA model of non-parametric methods to measure technical innovation efficiency of national high-tech industry. At the same time, this paper chooses the DEA-Malmquist index to measure the dynamic changes of the technological innovation efficiency, gives the level of significance by the bootstrap method.Secondly, this paper combines three-stage DEA model with bootstrap method to measure the technology innovation efficiency of Chinese high-tech industries from the year2001to2010. The three-stage DEA model eliminates the external environment factors and random errors, while the bootstrap method removes the inefficient elements on the production frontier, and gives the confidence intervals of the efficiency. The empirical results show that the technical innovation efficiency of country’s high-tech industry is low, which is mainly attributed to the low of the pure technical efficiency. What’s more, the technical innovation efficiencies of high-tech industries in provinces differs greatly. At the same time, the empirical results of the SFA model at the second stage show that the four environmental factors have the significant influence on the technical innovation efficiency of high-tech industry. The government support is not good for the R&D resources’configurations. The decreasing proportion of enterprise nationalization, as well as the increasing proportion of foreign capital, is good to reduce the waste of R&D resources and increase the technical innovation efficiencies. Higher market concentration and moderate enterprise scale can help reduce the redundancy of R&D resources.In addition, the technical innovation efficiency corrected by the bootstrap-DEA model is significantly lower than the efficiency value not corrected. This is because that the bootstrap method considers the inefficient factors on the production frontier, which makes the relative efficiency turns to the absolute efficiency. Finally, this paper makes cluster analysis to divide the national30provinces into four categories, which is based on the pure technical efficiency and the scale efficiency. All provinces and cities will be classified into four types, and the measures to promote the technical innovation efficiency for each type high-tech industry will be given respectively.Thirdly, this paper uses DEA-Malmquist index and bootstrap method to measure the total factor productivity changes of high-tech industry technical innovation from year2000to2010, and to give the significant level of the efficiency estimates. Then, this paper uses the convergence model to analyze the regional convergences of the high-tech industry technical innovation efficiencies’changes. Research conclusions are as follows:the total factor productivity of China’s high-tech industry technology innovation from the year2000to2010is in a continuous wave, its improvement and fall appear alternately. So the improvement of technical innovation efficiency is not deal. From the perspective of the three regions, the directions of TFP changes are significant difference, and the technical innovation efficiency in the east area increases fastest. From the perspective of TFP decomposition, the directions of technical efficiency change and technical progress are not stable, hence the direction of TFP change depends on the directions of the two indexes. As the power of promoting the technical innovation of the high-tech industry, the technical advance and the technology efficiency increasing are contributing to the increasing of the TFP alternatively. The increases on both the technology progress and the technology efficiency in the east area are higher than the central and western regions. This paper inspects the convergence of the technical innovation efficiency changes by the variation coefficient and the convergence model. And the results show that, in the short term, the technical innovation efficiencies of the high-tech industry are of convergence in the western region and the whole country, and the east from year2000to2005is of convergence, the central region from year2005to2010is of convergence.Finally, this paper gives the corresponding policy recommendations based on the empirical study results of the three-stage DEA model, DEA-Malmquist index and the convergence model.The two innovation points of this paper are as follows:Firstly, different from the existing research, this paper compares the difference of the technical innovation efficiencies between the provinces and cities, and points out the existing inefficient problems in different provinces.Secondly, this paper gives the efficiency estimates as well as the corresponding confidence intervals by the DEA model and the bootstrap method to make up for the accuracy and robustness problems of the existing research on technical innovation efficiency of high-tech industry. |
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