人力资本吸收、外资技术扩散与中国经济增长

引进外资并不意味着东道国一定能够掌握内含在外资中的国外先进技术,成功掌握外资先进技术有一个消化、吸收和创新的技术扩散过程。文章在区别外资技术扩散效应与溢出效应概念的基础上,通过构建衡量外资技术扩散计量模型,从时间和空间的角度检验了以FDI为载体的技术扩散对中国区域经济增长的影响。研究发现,在改革开放以来的不同阶段,尽管外资对中国区域经济增长有明显的促进作用,但各地区并没有能够通过引进大量外资获得内含在外资中的先进技术,外资技术扩散对地区经济增长没有显著的影响。     

中观层面上标准化对经济增长的贡献率分析：基于东中西部省际面板数据

基于2001-2017年我国30个省区市的面板数据,根据我国标准体系的构成和标准研制贡献指数构建地区的标准化水平,通过纳入技术创新要素和标准化要素构建增广的索洛模型,分析包括标准化在内的各投入要素对各省区市经济增长的贡献率。研究结果表明,各要素对各省区市经济增长的贡献率呈现区域差异性,这意味着不同的区域需要实施不同的要素驱动政策。技术创新的要素年均增长率和要素贡献率在东中西部各区域都稳居第一位,意味着我国的创新驱动战略在中观层面发挥了显著影响。资本和劳动要素的年均增长率限制了二者对经济增长的贡献率。区域经济增长中标准化与自主创新的贡献度是相关的,表明标准化对经济增长的要素贡献率仍有较大的发展空间。     

高校专利权转移的网络结构和影响因素分析——基于2016年北京、江苏、陕西高校专利权转移的实证

基于2016年北京市、江苏省、陕西省三个重要区域的高校专利权转移数据,运用社会网络分析方法和多元回归模型,探索不同区域高校科技成果转化的网络结构和影响因素。研究表明,三个重要地区高校科技成果均在本地实现了较高的转化量,其中江苏省在本地的转化率超过了50%;三个重要地区高校均趋向于在经济活力高、创新水平较高的区域进行科技成果转化活动;影响各个区域高校科技成果转化的因素存在着一些差异,不能一概而论。不同发展模式和经济水平的区域要依据自身发展特点,选取合适的参照对象,有针对性的采取一定的措施来刺激本地高校专利的发明和转让。     

Reprint of The new paradigm of economic complexity

Economic complexity offers a potentially powerful paradigm to understand key societal issues and challenges of our time. The underlying idea is that growth, development, technological change, income inequality, spatial disparities, and resilience are the visible outcomes of hidden systemic interactions. The study of economic complexity seeks to understand the structure of these interactions and how they shape various socioeconomic processes. This emerging field relies heavily on big data and machine learning techniques. This brief introduction to economic complexity has three aims. The first is to summarize key theoretical foundations and principles of economic complexity. The second is to briefly review the tools and metrics developed in the economic complexity literature that exploit information encoded in the structure of the economy to find new empirical patterns. The final aim is to highlight the insights from economic complexity to improve prediction and political decision-making. Institutions including the World Bank, the European Commission, the World Economic Forum, the OECD, and a range of national and regional organizations have begun to embrace the principles of economic complexity and its analytical framework. We discuss policy implications of this field, in particular the usefulness of building recommendation systems for major public investment decisions in a complex world.     

The ability of European regions to diversify in renewable energies: The role of technological relatedness

Despite the global consensus about the growing significance of renewables, the regional drivers of innovation in these unique and novel technologies have been widely neglected in the literature. In this paper, we show that renewable energy (RE) inventions differ from other green inventions in the knowledge recombination processes leading to their generation as well as in their impact on subsequent inventions. The evidence on these specificities of RE technologies allows us hypothesizing that regional branching in renewables may rely on relatedness differently than other non-RE green technologies. In checking this hypothesis, we use a data set spanning the period 1981-2015 covering 277 European NUTS2 regions in the EU28 countries plus Norway. We obtain that relatedness is highly relevant in explaining regional specialization in RE, and more relevant than for other green technologies, which we associate to the lower generality in their impact and the narrower scope of the knowledge from which they nurture. This conclusion is maintained when considering separately regions with high and low development levels. However, the impact of relatedness increases for RE as the regional economic development decreases, signalling that a low endowment of resources and capabilities does not allow the region to break from its past technological specialization, depending more on relatedness. This would not be the case for other green technologies, probably due to their higher level of generality and wider scope.     

The new paradigm of economic complexity

Economic complexity offers a potentially powerful paradigm to understand key societal issues and challenges of our time. The underlying idea is that growth, development, technological change, income inequality, spatial disparities, and resilience are the visible outcomes of hidden systemic interactions. The study of economic complexity seeks to understand the structure of these interactions and how they shape various socioeconomic processes. This emerging field relies heavily on big data and machine learning techniques. This brief introduction to economic complexity has three aims. The first is to summarize key theoretical foundations and principles of economic complexity. The second is to briefly review the tools and metrics developed in the economic complexity literature that exploit information encoded in the structure of the economy to find new empirical patterns. The final aim is to highlight the insights from economic complexity to improve prediction and political decision-making. Institutions including the World Bank, the European Commission, the World Economic Forum, the OECD, and a range of national and regional organizations have begun to embrace the principles of economic complexity and its analytical framework. We discuss policy implications of this field, in particular the usefulness of building recommendation systems for major public investment decisions in a complex world.     

技术流动、创新网络对区域创新能力的影响研究

基于中国2013-2018年的省级面板数据,构建模型讨论了区域创新网络、高技术企业技术流动对区域创新能力的作用机制,进一步分析了不同创新网络水平地区,高技术企业技术流动对区域创新发展的作用力,利用门槛回归探究了随着区域网络水平的演进,技术市场中高技术企业技术输出和吸纳的变化态势。实证结果表明：（1）区域创新网络、高技术企业技术输出和技术吸纳均有助于区域创新能力的提升,但作用机制和强度不同;（2）相对创新网络欠发达地区,在创新网络发达地区的高技术企业的技术创新具有正向的自我强化机制,但创新网络的作用力稍弱;（3）无论创新网络发达/欠发达地区,高技术企业技术吸纳对区域创新能力的促进作用均大于技术输出;（4）随着创新网络水平的提升,高技术企业技术流动对区域创新能力的影响作用逐渐减弱。     

The complex nature of regional knowledge production: Evidence on European regions

Knowledge creation is widely considered as the central driver for innovation, and accordingly, for creating competitive advantage. However, most measurement approaches have so far mainly focused on the quantitative dimension of knowledge creation, neglecting that not all knowledge has the same value (Balland and Rigby, 2017). The notion of knowledge complexity has come into use in this context just recently as an attempt to measure the quality of knowledge in terms of its uniqueness and its replicability. The central underlying assumption is that more complex knowledge is more difficult to be replicated, and therefore provides a higher competitive advantage for firms, or at an aggregated level, regions and countries. The objective of this study is to advance and apply measures for regional knowledge complexity to a set of European regions, and to highlight its potential in a regional policy context. This is done by, first, characterising the spatial distribution of complex knowledge in Europe and its dynamics in recent years, second, establishing that knowledge complexity is associated with future regional economic growth, and third, illustrating the usefulness of the measures by means of some policy relevant example applications. We proxy the production of complex knowledge with a regional knowledge complexity index (KCI) that is based on regional patent data of European metropolitan regions from current EU and EFTA member countries. The results are promising as the regional KCI unveils knowledge creation patterns not observed by conventional measures. Moreover, regional complexity measures can be easily combined with relatedness metrics to support policy makers in a smart specialisation context.     

Science–technology flows in Spanish regions: An analysis of scientific citations in patents

Many regions of the European Union with a high degree of autonomy have elected very clearly to stimulate scientific research and technological development (R&D) as a specific means of promoting economic growth and the welfare of their citizens. In Spain, several autonomous regions have organised their efforts in science and technology by means of the adoption of regional R&D plans. In some cases, particular concern is taken to link the scope of scientific research with that of technology, but even in these few cases, it is acknowledged that little is known of the mechanisms by which the results of scientific research are translated into technological development, and how this latter in turn influences the objectives of scientific research. Our aim in this article is to study in greater depth the relationship between science and technological development in the various regions of Spain. The methodology that we apply to investigate the links between science and technology is based on an analysis of scientific citations in patent documents (non-patent citation (NPC)). The results obtained from this study provide some relevant data on the interconnection between the scientific and technological systems from a regional perspective.     

Systemic technology innovation management and analysis of other forms of IP protection

Industry 4.0 and the pandemic have caused recent changes in innovative development, economic situations, and restrictions in various companies and regions of the world, with new stricter legislation related to working conditions, hygiene standards, and health requirements. New technologies are a challenge to the transformation of problem companies and regions, as they often significantly impact economic development. Technological emissions, growing information on dementia among young people, cyber risks, and the risks of so-called advanced technologies (e.g., bio- and nanotechnologies, Industry 4.0 tech) may raise societal concerns about technological progress. This study is part of our long-term research into technological innovation in different companies and regions. Its primary goal is to methodically emphasize the importance and role of the systemic management of technological innovation in companies and regions and analytically compare the innovation success of differently developed regions from a global perspective¹. This research deals with an important aspect of technology management, namely, the processes of technological identification and the protection of related intellectual property (IP). The primary research question is: How has technological development been distributed across different regions over the last two decades? We hypothesize that Asian countries are increasingly moving away from Europe and North America in terms of technological innovation, other forms of technological IP protection, and overall access to innovation, while the focus is on the development of three non-patent forms of technological innovation protection: industrial designs, trademarks, and utility models. The results of our study reveal a significant difference in the approach to technological innovation management and the form of IP protection between so-called advanced and problem companies and regions. This study was conducted between 2018 and 2022.     

区域科技创新、经济发展与生态环境的协调发展研究——基于省级面板数据的实证分析

运用熵值法、变异系数和耦合协调模型对我国2002-2016年区域科技创新、经济和环境水平进行分析,研究发现,科技创新、经济和环境总体上不断发展并呈现阶段性特征;它们的区域差异在波动中下降;科技创新、经济和环境的两元系统跟三元系统协调均呈上升趋势。直到2016年全国各地区三元系统协调等级未达到优质耦合协调等级;科技创新、经济和环境的三元系统耦合协调增长在2009年之前主要是由环境和经济的协调发展引领,在2009年之后主要是由科技和经济的协调发展引领。未来需加大对科技、经济和生态环境保护的支持力度以实现三者的协调发展并缩小区域差异。     

知识溢出、高校创新投入与经济增长——基于包含创新部门的新经济地理增长模型及检验

通过包含创新部门的新经济地理增长模型,分析发现知识溢出和高校创新投入对经济增长具有正向影响作用。在此基础上,选取2004—2015年我国省级面板数据,通过构建空间动态面板杜宾模型并采用系统GMM方法,在结构视角下考察高校创新投入对经济增长的影响。结果表明,时间维度上,高校创新投入对经济增长具有促进效应;空间维度上,高校创新投入对经济增长影响具有外部性特征,高校基础研究经费内部支出、高校应用研究经费内部支出对经济增长具有正向溢出效应,且知识溢出和高校创新投入对经济增长的影响在不同区域存在差异性。     

从专利信息分析看北部湾经济区技术创新能力

随着经济全球化的深入发展,区域技术创新能力逐渐成为区域经济增长的源泉和核心竞争优势。在北部湾经济区这一区域合作中,评价和提升区域技术创新能力是实现该区域经济发展的重要手段。本文从专利信息分析的角度,研究了北部湾经济区技术创新能力的现状和存在问题,并提出几点相关建议。     

中国传统产业和高技术产业技术创新效率变动趋势研究——基于时空双维度视角

随着新型经济增长和技术创新的不断革新,地区产业转型升级,产业创新发展地区间不平衡现象严重。本文运用SUPER-SBM模型对我国29个省市传统产业和高技术产业十年前后的技术创新效率进行测算,并结合变异系数与自然间断点法刻画产业区域创新效率空间分布图,从时空维度进行比较研究。研究发现：中国大中型传统产业和高技术产业的区域创新效率整体水平十年间总提升幅度约为20%,十年后两大产业创新效率均值约为0.7,距高效率仍有较大的提升空间。空间维度来看,四大经济区之间的产业创新效率差异有所减弱,但中部地区内部省份之间创新发展不均衡；传统产业创新效率的提升主要表现为各省在原有基础上不断进步,高技术产业创新效率的变化呈现出东部沿海省份向中西部地区转移的现象,高效率在空间上呈现出由纵向上的山西、河南、江西、广东四省与横向上属于长江经济带的上海、江苏、安徽、湖北、重庆、四川六省组成的“十”字型分布。     

知识产权保护与企业出口技术复杂度:基于中国企业微观数据的实证分析

通过多维度固定效应模型研究中国知识产权保护对企业出口技术复杂度的影响.结果 发现,(1)整体来看,中国知识产权保护与企业出口技术复杂度之间存在显著的倒U型关系;(2)从不同所有制企业来看,相比于内资企业,外资企业中知识产权保护与企业出口技术复杂度之间倒U型关系较强;(3)从不同地区企业来看,东部地区知识产权保护与企业出口技术复杂度之间仍存在倒U型关系,中部和西部地区呈现线性促进关系.综合而言,由于中国的特殊国情和地区发展不平衡的现实背景,中国应适当地提高知识产权保护力度但又不能太过激进.     

我国区域创新能力变化的新特征、新趋势

区域创新是创新驱动发展的重要载体,对区域经济增长具有重要的引领作用。区域创新能力的评估可为中央和地方政策制定提供决策参考。文章基于《中国区域创新能力评价报告2020》评价结果,梳理和分析了我国区域创新能力呈现出的新特点:以北京、上海、广东等为中心的创新集聚区初步形成;具有全球影响力的三大科技创新中心(北京、上海、粤港澳大湾区)建设取得重要进展;南方地区的创新能力在快速上升。同时,我国区域创新能力依然面临挑战:创新能力发展不平衡问题依然严峻;科教资源不平衡,高校和科研院所与地区经济发展联系不紧密。文章提出未来依靠优化战略布局,提升我国区域创新能力的对策建议。     

环境规制是否倒逼了创新驱动的地区产业转型升级？

   本文借助于“两控区”政策冲击,选取1994—2010年中国地级市面板数据和国家专利数据,运用倍差法,研究了环境规制对地区产业转型升级的影响及其机制。研究发现：环境规制显著地促进了地区产业转型升级,且在长期内其政策效应呈现出逐渐减弱的趋势。使用不同的产业转型升级指标等稳健性检验表明,我们的结论基本不变。同时,政策效应存在地区异质性,即它只是显著地促进了中部地区的产业转型升级。进一步机制研究发现：环境规制并不是通过资本深化渠道和外资溢出效应渠道,而是通过技术创新渠道倒逼了地区产业转型升级。     

合作网络、知识产权能力与区域自主创新程度：一个有调节的中介模型

随着区域经济竞争的加剧，创新已经成为区域保持经济持续增长的驱动力。在此背景下，从区域创新合作网络和知识产权能力的视角，研究影响区域自主创新发展的因素是具有重要意义的。首先，本文根据区域之间的创新合作矩阵，计算31个省份的网络特征指标值；然后，从知识产权创造、运用、保护、管理和服务等五个方面构建区域知识产权能力评价指标体系，借助主成分方法计算各省份的知识产权综合能力；最后，利用回归分析验证合作网络通过知识产权能力影响区域自主创新的路径以及开放度与制度因素的调节效应。结果发现：知识产权能力以及表征合作网络特征的集聚性、结构洞、度数中心性、接近中心性和中间中心性正向影响区域自主创新程度；知识产权能力在集聚性、结构洞、度数中心性、接近中心性和中间中心性对区域自主创新的影响中均起到部分中介作用；开放度正向调节知识产权能力与区域自主创新程度之间的关系，制度因素负向调节知识产权能力对自主创新程度的影响。本文的研究不仅理清了区域创新合作网络、知识产权能力影响区域自主创新的机制，而且为促进区域自主创新发展政策的制定提供了参考和借鉴。     

要素流动、产业结构调整与区域经济分化

本文从理论模型分析、中国实际数据模拟两个角度解析了地区间要素流动、产业结构变迁以及区域经济差距之间的关系。本文构建的两地区、三部门的理论模型揭示了地区间经济差距演化的原因在于地区间产业结构的调整,而地区间产业结构调整的根源在于资本、异质性劳动流动过程中表现出的相依性。本文提出的理论模型及分析过程可用于探究任意经济体任意时期的经济结构特征。将该理论与方法应用于中国实际,得到的模拟结果表明,以现代化技术为生产特征的产业结构调整造成了中国地区间经济差距的扩大,而不同产业结构对生产要素流动的引致需求又进一步造成了地区间产业结构发展不平衡,进而形成正反馈机制,即“要素追逐技术”现象。此外,在要素流动背景下,产业间的协调发展是决定地区经济持续增长的关键,高新技术产业的发展需要相应规模的传统服务业支持,同时传统服务业的发展对高新技术产业形成反哺机制。因此,加大技术性资源引进力度,弥补地区间技术差异,引导地区间工业、服务业协调布局与发展,方能有效缩小地区间经济差异。     

合作网络、知识产权能力与区域自主创新程度:一个有调节的中介模型

随着区域经济竞争的加剧,创新已经成为区域保持经济持续增长的驱动力。在此背景下,从区域创新合作网络和知识产权能力的视角,研究影响区域自主创新发展的因素是具有重要意义的。首先,本文根据区域之间的创新合作矩阵,计算31个省份的网络特征指标值;然后,从知识产权创造、运用、保护、管理和服务等五个方面构建区域知识产权能力评价指标体系,借助主成分方法计算各省份的知识产权综合能力;最后,利用回归分析验证合作网络通过知识产权能力影响区域自主创新的路径以及开放度与制度因素的调节效应。结果发现：知识产权能力以及表征合作网络特征的集聚性、结构洞、度数中心性、接近中心性和中间中心性正向影响区域自主创新程度;知识产权能力在集聚性、结构洞、度数中心性、接近中心性和中间中心性对区域自主创新的影响中均起到部分中介作用;开放度正向调节知识产权能力与区域自主创新程度之间的关系,制度因素负向调节知识产权能力对自主创新程度的影响。本文的研究不仅理清了区域创新合作网络、知识产权能力影响区域自主创新的机制,而且为促进区域自主创新发展政策的制定提供了参考和借鉴。