我国高技术产业区域效率研究
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摘要
本文以产业经济学、微观经济学、管理学理论和现代效率理论为依托,以现代前沿统计方法为工具,采用规范分析和实证分析相结合、定性与定量研究相结合、横向与纵向比较分析的方法,对我国各个省份高技术产业的静态效率和动态效率进行实证研究。
首先,本文在对已有研究文献进行回顾和梳理基础上,介绍生产前沿面理论与方法,并给出新时期我国经济效率的内涵,分析了新时期我国高技术产业效率的影响因素,从而构建了高技术产业效率评价的指标体系,为之后效率区域差异实证分析提供合理的研究视角、理论基础。然后,选定了合适的计量方法,对高技术产业效率区域差异的实证研究,分别进行了静态和动态研究。为了得到稳健的估计结果,我们通过2000次Bootstrap生成伪样本,进行纠偏估计和统计推断。同时本文还采取SFA方法估计各省高技术产业效率,并分析两种方法在高技术产业效率评价的适用性。通过得到的估计结果,深入分析我国高技术产业效率区域间的差异,探索高技术产业低效率或无效率的原因、关键影响因素以及考察各个地区高技术产业增长变化的原因。最后,建立固定效应面板数据模型分析高技术产业中效率变化、技术进步以及资金对高技术产业人均增加值的影响。
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.
首先,本文在对已有研究文献进行回顾和梳理基础上,介绍生产前沿面理论与方法,并给出新时期我国经济效率的内涵,分析了新时期我国高技术产业效率的影响因素,从而构建了高技术产业效率评价的指标体系,为之后效率区域差异实证分析提供合理的研究视角、理论基础。然后,选定了合适的计量方法,对高技术产业效率区域差异的实证研究,分别进行了静态和动态研究。为了得到稳健的估计结果,我们通过2000次Bootstrap生成伪样本,进行纠偏估计和统计推断。同时本文还采取SFA方法估计各省高技术产业效率,并分析两种方法在高技术产业效率评价的适用性。通过得到的估计结果,深入分析我国高技术产业效率区域间的差异,探索高技术产业低效率或无效率的原因、关键影响因素以及考察各个地区高技术产业增长变化的原因。最后,建立固定效应面板数据模型分析高技术产业中效率变化、技术进步以及资金对高技术产业人均增加值的影响。
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.
引文
①陈德棉,蔡莉:《风险投资:运行机制与管理》,.经济科学出版社,2003年
②胡鞍钢:《知识与发展——21世纪新追赶战略》,北京大学出版社,1999年
①保罗·A·萨谬尔森、威廉·D·诺德豪斯:《经济学》,中国发展出版社,1992年版.
②罗伯特·S·平狄克,丹尼尔·L·鲁宾费尔德:《微观经济学》(中译本,张军等译),中国人民大学出版社,1997年
①樊刚:《公有制宏观经济理论大纲》,三联书店,1990年
①亚当·斯密:《国民财富的性质和原因研究》(上册),王大力,王亚南译,商务印书馆,1974年
①周四军:中国商业银行效率研究,湖南大学博士学位论文,2006年12月
①保罗·A·萨谬尔森、威廉·D·诺德豪斯.《经济学》,中国发展出版社,1992年版,P45.
①蒂莫西·J·科埃利,D·S·普拉萨德·拉奥,克里斯托弗·J·奥唐奈:《效率与生产率分析引论》,王忠玉译,中国人民大学出版社,2002年6月
①孙静娟,戴忻,杨际昌:对我国高技术产业统计界定的思考,《统计与决策》2008年2期
①吴运建等:高技术企业创新及其风险,《科研管理》1998年4期。
①武立敬:论公平与效率观在当代中国的新内涵[D],西安科技大学,2006年4月
①陈泽亚:试论科学发展观下的新经济公平与效率观,《求实》2004年7期
①杜栋,庞庆华:现代综合评价方法与案例精选[M]。北京:清华大学出版社,2005年
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