| Basing on the literature about efficiency, the frontier theory has been introduced. Then, the connotation of China's Current economic efficiency has been given and the factors of Chinese high-tech industries'efficiency are analyzed.Next, we establish an evaluation indicator system of high-tech industries'efficiency to provide the theoretical basis for analysis following.By selecting suitable method, we analyze regional differences of high-tech industries'static and dynamic efficiency in China. In order to obtain stable estimators, we have generated 2000 pseudo-samples times Bootstrap for correcting estimators and statistical inference. At the same time, using SFA approach in this article also estimates the efficiency of the provincial high-tech industry and analyze two methods of high-tech industry in the evaluation of the applicability of efficiency.Through the results, analyze the differences of high-tech industries'static and dynamic efficiency between regions in China, and explore the reason of high-tech industries with low efficiency or inefficiency and the key factors. Finally, we establish a fixed effects panel data model changes to research the how the efficiency of high-tech industries, technological progress and capital effect the added value per capita.Based on the analysis above, six chapters are divided in the paper. The frame of paper is as follows:Chapter I: Introduction. This chapter introducs the background, significance, literatures and innovation framework..Chapter II: Theory and measurement of efficiency and productivity. This chapter is the part of the theoretical basis in the paper.First, the development process of the theory of efficiency and productivity is reviewe. Next, focuses on frontier methods and efficient of measurement that has been widely used by academic currently. Finally, introduce the two most common measurement methods for efficiency, DEA and SFA methods, basing on the frontier theory .Chapter III: Evaluation index system of high-tech industries'efficiency. In this chapter, we firstly give the the definition, characteristicsof high-tech industries.According to China's economic efficiency of the current connotation, pointing out the current factors of high-tech industries'efficiency in China. Finally, According to the principle of index system, establish an evaluation indicator system the of high-tech industries'efficiency in the paper to provide a theoretical foundation for empirical research.Chapter IV: The method of bootstrap in non-parametric frontier models. Traditionally, based on the DEA envelopment analysis estimated non-parametric estimate is only point estimate without considering the impact of random noise, has obvious flaws. This chapter gives the Simar & Wilson (1998,2000) to adopt corrective Bootstrap methods and statistical inference methods and the specific algorithm. Based on assumes the data generation process, the method uses Bootstrap to Calculate score of the efficiency of pseudo samples, and estimated the volume of sample through the pseudo-observation sample parameter estimates and the relationship between the mother of observation for correcting the sample estimator to overcome the system deviation of the traditional DEA point estimate. At the same time, the use of smooth Bootstrap solutions in the process of fitting the distribution of the border issue, carried out statistical inference.Chapter V: Static analysis of regional differences of high-tech industries'efficiency of in China. Using available data,We take a static analysis for different provinces and autonomous regions on China's high-tech industry to evaluate the efficiency of development. The results show that: Chinese high-tech industries'technical efficiency, pure technical efficiency, scale efficiency are centralized as development of the regional economy. At the same time, resources are concentrated, the higher the level of pure technical efficiency, but the expansion of the scale did not improve the efficiency of economies of scale in developed regions; pure technical efficiency is generally low in developing regions. In this chapter, using SFA approach also estimates the efficiency of the provincial high-tech industry and analyze two methods of high-tech industry in the evaluation of the applicability of efficiency. Chapter VI: Dynamic analysis of regional differences of high-tech industries'efficiency of in China. This chapter focused on total factor productivity from the perspective of the use-based Malmquist index of non-parametric methods, the use of panel data on China's 27 provinces and autonomous regions of high-tech industry TFP growth index for dynamic changes in inspection, and to find high-tech industry growth in all regions change. The results showed that: From the dynamic point of view, China's high-tech industry total factor productivity change in the rate of change in the rate of technological progress and efficiency changes in the rate of change in the rate of pure efficiency, scale efficiency is the rate of change of the regional economy with the level of overall development and concentrated.Chapter VII: efficiency and technological progress to increase the gap between high-tech industry of impact analysis. There are obvious interregional disparities between p rovincial high-tech industries during China's rapid economic development. The regional disparity of high-tech industry is a most important behavior of the regional economic disparity. The regional factor such as area industrialized way and initial endowment, the intensive characteristics of high-tech industry growth and the level of high-tech industry input are the main factors to cause the regional industrial economic disparities.The empirical results and conclusions are as follows:1. According to China's economic efficiency of the current connotation, pointing out the current factors of high-tech industries'efficiency in China. Finally, According to the principle of index system, establish an evaluation indicator system the of high-tech industries'efficiency in the paper.We need more comprehensive consideration of the impact of the efficiency of China's high-tech industries'factors. For example, the ecological environment, concentration levels, financial support, policy support and international competitiveness have become an important factor of high-tech industry in China,currently..2. The use of available data, the choice of indicators through the data, processing, using of Bootstrap correcting the DEA method, different provinces and autonomous regions on China's high-tech industry to the efficiency of static analysis. The results show that: Overall, the technical efficiency and per capita GDP to show the relationship between the general is not a linear relationship, but an inverted V-shaped relationship. The eastern part of the three regions in the middle is the leading technical efficiency, and the leader is mainly embodied in purely technical efficiency, scale efficiency is not only the eastern region and relatively low non-leading, but this phenomenon has been signs of improvement. Technical efficiency of the western region have been catching up the trend of the central region. China's high-tech industry, technical efficiency, pure technical efficiency, scale efficiency of the regional economy along with the improvement of the overall level of development and concentrate on not only the economy the more developed regions tend to converge the three more efficient, while the more backward areas of the economy in three tend to spread more efficiently. Technology for the promotion of economically underdeveloped regions, the overall improvement of management to be strengthened. High-tech industries in economically developed areas in relation to less developed regions of the main economic advantage lies in the concentration of resources, not including its strong material and financial resources, but also brought together more high-tech talent, but not with these advantages high-tech industry in the region arising from the expansion of the size scale.3. The use of bootstrap correction, based on the Malmquist index of non-parametric methods, the use of panel data on China's 27 provinces and autonomous regions of high-tech industry TFP growth study dynamic changes in index. The results showed that: dynamic changes of total factor productivity and per capita GDP to show the relationship between the general, no linear relationship, is also a kind of inverted V-shaped relationship. In the three regions of the eastern part of the dynamic efficiency had not increased significantly, therefore the development of future high-tech industries are facing many problems. China's high-tech industry total factor productivity change in the rate of change in the rate of technological progress and efficiency changes in the rate of change in the rate of pure efficiency, scale efficiency is the rate of change of the overall development of the regional economy with the level of concentration. Economically developed areas of pure efficiency and scale efficiency of the rate of change was no significant change in the rate of change at the same time, technological advances in developed areas compared with the less developed regions to improve the efficiency of the slow speed. Economically underdeveloped regions to improve total factor productivity high and low, the problem varies. Different regions should be targeted for their own problems, should be, respectively, from the technological progress, efficiency and pure efficiency started to increase the size of the high-tech industry in this region.4. The establishment of a fixed effect panel data model changes in the efficiency of high-tech industries, technological progress and the funding of high-tech industries the impact of the added value per capita. The results showed that: in the period 2001-2005 between the elements of capital input and the extensive nature of the eastern part of the initial endowment advantage, in the eastern and the central and western regions the level of development of high-tech industries of the root causes of the gap opened, and in between 2005-2007 , leading to differences in inter-provincial high-tech industry a decisive factor in the region by the early or initial endowment of factors based on a change in the development of high-tech industries of the region's new capital formation, efficiency and technological strength.
|
PDF Full Text Request