中国区域技术专业化模式与程度研究
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摘要
近年来，随着中国经济的迅速发展，国家技术创新能力明显增强。作为处于转轨阶段的发展中国家，中国内部区域间技术创新能力存在显著差异，在国家层次对技术创新能力进行分析可能是不适当的。而从区域角度分析中国的技术创新问题不仅是国内学者研究的热点，对相关政策的制定也有重要指导意义。在此背景下，本文通过文献研究、统计分析和计量经济分析等方法，探讨中国区域技术专业化问题，尤其是技术专业化模式与程度的变迁与规律，取得了以下研究成果：
(1)基于中国发明专利授权数据构建的技术专业化模式指标——显性技术优势(RTA)值，对中国各省区技术专业化模式的情况进行比较分析，发现省区间技术专业化模式各不相同，经济较发达的东部省区，其技术布局差异比中西部省区更为显著。以专利增长速度作为技术机会的指标，发现不同技术领域的发展机会存在很大差异，并且只有广东和北京等极少数省区有能力在拥有最高技术机会的技术领域实现专业化。
(2)通过聚类分析和多维尺度分析，可以将加入WTO前后，中国各区域按照技术专业化模式的差异划分到不同类别。K-means聚类和多维尺度分析的分类结果完全一致。加入WTO之后，湖南、吉林、甘肃、江苏和浙江等省区技术布局的变化较显著。通过技术专业化模式之间的相似性分析，发现加入WTO之前，北京、上海、江苏、福建、广东、湖北和陕西与大多数省区技术布局都不相似，而其他省区技术相似程度较高。加入WTO之后，在ICT领域仅广东有明显的技术优势。
(3)通过双变量Galtonian回归模型，分析中国各省区技术专业化模式与程度的变迁和稳定性。发现加入WTO后，我国绝大多数省区技术专业化模式有显著的稳定性，而且相隔时间越短，稳定性越显著。国内大多数省区的技术收敛度和全球技术收敛度都存在先增加后降低的规律，而技术集中度在2000-2004年间没有明显变化趋势，但是在2005-2008年间大多数省份技术集中度都在降低。
(4)基于技术集中度和技术机会的不同，将技术分为领先技术、普及技术、成熟技术和锁定技术四类。依据技术能力在这四个分类中分布的相似性，通过多维尺度分析，可将29个中国各省区分为四组，其中北京、上海和广东主要在领先技术和普及技术中有相对优势，江苏和浙江的优势则集中于成熟技术领域，其他省区的技术优势多集中于成熟技术和锁定技术。通过回归分析探讨了专业化程度与规模的关系，发现中国各省区技术专业化程度与经济和技术规模之间都存在显著线性关系。同时，技术收敛度与技术规模之间还存在U型关系，所有技术专业化指标之间都高度相关。
(5)通过自回归分布滞后-边界检验模型分析中国信息及通信技术(ICT)领域技术能力和专业化对经济增长的影响，结果发现，ICT技术专业化程度和技术能力与GDP之间存在长期负相关关系，即ICT技术的发展会阻碍经济增长。同时，GDP与ICT技术专业化程度和技术能力之间还存在U型关系，而且U型关系存在临界点，越过临界点之后，ICT技术发展对GDP的增长效应才能体现，临界点出现在2001-2003年。上述研究表明生产率悖论在中国是存在的。
In recent years, with the rapid development of Chinese economy, nationaltechnological innovation capability has been remarkably improved. As a developingcountry at the stage of transition, China has significant variance of innovation capacitybetween regions. So it is not suitable to analyze technological innovation only at nationallevel. The study of innovation at regional level is not only the hot spot of researchers, butalso has significance for innovation policymaker. In this context, the paper studiestechnological distribution in the regions of China, especially patterns and degrees ofregional technological specialization of different provinces by literature research,statistical analysis and econometrics models. The following is the main achievements ofthis dissertation:
Firstly, regional patterns of technological specialization are compared and analyzed,based on Revealed Technological Advantage index (RTA) constructed on the data ofgranted invention patents in China. There are significant differences in patterns oftechnological specialization among provinces, and differences among better developedprovinces in East China are far greater than those in Midwest. Guangdong province andBeijing city enjoy better capability to grasp the technological opportunity, and theopportunity varies among technological sectors which is the result analyzed throughcorrelation analysis upon the index constructed by the data of patent growth rates.
Secondly, all provinces can be classified into several different categories accordingto their patterns of technological specialization through K-means cluster analysis andmulti-dimensional scaling method, and the same result can be obtained through either ofthe two methods. The distributions of technology have notably changed in Hubei, Jilin,Gansu, Jiangsu and Zhejiang provinces after China joined WTO. Through correlationanalysis between patterns of technological specialization of provinces, it is found thatsome provinces or cities, including Beijing, Shanghai, Jiangsu, Fujian, Guangdong, Hubeiand Shaanxi, have major difference with most other provinces which enjoy greatsimilarities in technological distribution before China joined WTO. And Guangdong is the only province which has technology advantage in information and communicationtechnology sector after China entering WTO.
Thirdly, the transition and stability of pattern and degree of technologicalspecialization are analyzed among China provinces using Galtonian regression model. Theresult shows that patterns of the majority of China provinces are stable, and the stability ismore significant with shorter time interval. In most provinces, both the national and globaltechnological convergence degrees first increase and then decrease. Technologicalconcentration had no obvious tendency during year2000to2004, but it decreased in mostprovinces during year2005to2008,
Fourthly, all technology sectors can classified into four categories, leadingtechnology, pervasive technology, mature technology and lock-in technology bytechnological concentration and opportunities based on China patents data. According tothe similarity of revealed technological advantage index in the four technology categories,29provinces can be classified into four groups through multi-dimensional scaling analysis.Beijing, Shanghai and Guangdong provinces have technological advantage in leading andpervasive technology, while Jiangsu and Zhejiang provinces concentrate their technologycapacity in mature technology. And other eleven provinces have technological advantageonly in lock-in sector, with the rest thirteen focusing in mature and lock-in sectors. Therelationships between the degrees of regional technological specialization, which isidentified the degree of concentration and the degree of convergence and the scale oftechnology and economics in China are studied by regression models. There is aconsistent inverse relationship between the scale of regional technology and economy andthe degree of concentration and convergence. The U-shaped relationship between theconvergence and the technology scale is found, which can not be found between theconcentration and the scale. There are significant positive relationships among allindicators of the degree of concentration and convergence.
Finally, the impact of ICT (Information and Communication Technology)technological specialization degree and technology capacity upon China economic growthis studied. The negative long-term relationships between ICT technological specializationdegree and technology capacity and GDP are found by employing the newly developedautoregressive distributed lag (ARDL)-bounds testing approach, which means the development of ICT may hinder GDP and technology growth. Meanwhile, there isU-shaped relationship between technological specialization and GDP, as well astechnology capacity and GDP, which has a critical point emerging in2001-2003. Afterincreasesd over this point, technology capacity and the degree of technologicalspecialization GDP will boost economic development. The results shows that there exitsproductivity paradox in China.
(1)基于中国发明专利授权数据构建的技术专业化模式指标——显性技术优势(RTA)值，对中国各省区技术专业化模式的情况进行比较分析，发现省区间技术专业化模式各不相同，经济较发达的东部省区，其技术布局差异比中西部省区更为显著。以专利增长速度作为技术机会的指标，发现不同技术领域的发展机会存在很大差异，并且只有广东和北京等极少数省区有能力在拥有最高技术机会的技术领域实现专业化。
(2)通过聚类分析和多维尺度分析，可以将加入WTO前后，中国各区域按照技术专业化模式的差异划分到不同类别。K-means聚类和多维尺度分析的分类结果完全一致。加入WTO之后，湖南、吉林、甘肃、江苏和浙江等省区技术布局的变化较显著。通过技术专业化模式之间的相似性分析，发现加入WTO之前，北京、上海、江苏、福建、广东、湖北和陕西与大多数省区技术布局都不相似，而其他省区技术相似程度较高。加入WTO之后，在ICT领域仅广东有明显的技术优势。
(3)通过双变量Galtonian回归模型，分析中国各省区技术专业化模式与程度的变迁和稳定性。发现加入WTO后，我国绝大多数省区技术专业化模式有显著的稳定性，而且相隔时间越短，稳定性越显著。国内大多数省区的技术收敛度和全球技术收敛度都存在先增加后降低的规律，而技术集中度在2000-2004年间没有明显变化趋势，但是在2005-2008年间大多数省份技术集中度都在降低。
(4)基于技术集中度和技术机会的不同，将技术分为领先技术、普及技术、成熟技术和锁定技术四类。依据技术能力在这四个分类中分布的相似性，通过多维尺度分析，可将29个中国各省区分为四组，其中北京、上海和广东主要在领先技术和普及技术中有相对优势，江苏和浙江的优势则集中于成熟技术领域，其他省区的技术优势多集中于成熟技术和锁定技术。通过回归分析探讨了专业化程度与规模的关系，发现中国各省区技术专业化程度与经济和技术规模之间都存在显著线性关系。同时，技术收敛度与技术规模之间还存在U型关系，所有技术专业化指标之间都高度相关。
(5)通过自回归分布滞后-边界检验模型分析中国信息及通信技术(ICT)领域技术能力和专业化对经济增长的影响，结果发现，ICT技术专业化程度和技术能力与GDP之间存在长期负相关关系，即ICT技术的发展会阻碍经济增长。同时，GDP与ICT技术专业化程度和技术能力之间还存在U型关系，而且U型关系存在临界点，越过临界点之后，ICT技术发展对GDP的增长效应才能体现，临界点出现在2001-2003年。上述研究表明生产率悖论在中国是存在的。
In recent years, with the rapid development of Chinese economy, nationaltechnological innovation capability has been remarkably improved. As a developingcountry at the stage of transition, China has significant variance of innovation capacitybetween regions. So it is not suitable to analyze technological innovation only at nationallevel. The study of innovation at regional level is not only the hot spot of researchers, butalso has significance for innovation policymaker. In this context, the paper studiestechnological distribution in the regions of China, especially patterns and degrees ofregional technological specialization of different provinces by literature research,statistical analysis and econometrics models. The following is the main achievements ofthis dissertation:
Firstly, regional patterns of technological specialization are compared and analyzed,based on Revealed Technological Advantage index (RTA) constructed on the data ofgranted invention patents in China. There are significant differences in patterns oftechnological specialization among provinces, and differences among better developedprovinces in East China are far greater than those in Midwest. Guangdong province andBeijing city enjoy better capability to grasp the technological opportunity, and theopportunity varies among technological sectors which is the result analyzed throughcorrelation analysis upon the index constructed by the data of patent growth rates.
Secondly, all provinces can be classified into several different categories accordingto their patterns of technological specialization through K-means cluster analysis andmulti-dimensional scaling method, and the same result can be obtained through either ofthe two methods. The distributions of technology have notably changed in Hubei, Jilin,Gansu, Jiangsu and Zhejiang provinces after China joined WTO. Through correlationanalysis between patterns of technological specialization of provinces, it is found thatsome provinces or cities, including Beijing, Shanghai, Jiangsu, Fujian, Guangdong, Hubeiand Shaanxi, have major difference with most other provinces which enjoy greatsimilarities in technological distribution before China joined WTO. And Guangdong is the only province which has technology advantage in information and communicationtechnology sector after China entering WTO.
Thirdly, the transition and stability of pattern and degree of technologicalspecialization are analyzed among China provinces using Galtonian regression model. Theresult shows that patterns of the majority of China provinces are stable, and the stability ismore significant with shorter time interval. In most provinces, both the national and globaltechnological convergence degrees first increase and then decrease. Technologicalconcentration had no obvious tendency during year2000to2004, but it decreased in mostprovinces during year2005to2008,
Fourthly, all technology sectors can classified into four categories, leadingtechnology, pervasive technology, mature technology and lock-in technology bytechnological concentration and opportunities based on China patents data. According tothe similarity of revealed technological advantage index in the four technology categories,29provinces can be classified into four groups through multi-dimensional scaling analysis.Beijing, Shanghai and Guangdong provinces have technological advantage in leading andpervasive technology, while Jiangsu and Zhejiang provinces concentrate their technologycapacity in mature technology. And other eleven provinces have technological advantageonly in lock-in sector, with the rest thirteen focusing in mature and lock-in sectors. Therelationships between the degrees of regional technological specialization, which isidentified the degree of concentration and the degree of convergence and the scale oftechnology and economics in China are studied by regression models. There is aconsistent inverse relationship between the scale of regional technology and economy andthe degree of concentration and convergence. The U-shaped relationship between theconvergence and the technology scale is found, which can not be found between theconcentration and the scale. There are significant positive relationships among allindicators of the degree of concentration and convergence.
Finally, the impact of ICT (Information and Communication Technology)technological specialization degree and technology capacity upon China economic growthis studied. The negative long-term relationships between ICT technological specializationdegree and technology capacity and GDP are found by employing the newly developedautoregressive distributed lag (ARDL)-bounds testing approach, which means the development of ICT may hinder GDP and technology growth. Meanwhile, there isU-shaped relationship between technological specialization and GDP, as well astechnology capacity and GDP, which has a critical point emerging in2001-2003. Afterincreasesd over this point, technology capacity and the degree of technologicalspecialization GDP will boost economic development. The results shows that there exitsproductivity paradox in China.
引文
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