|
|
The Influence of Scientific and Technological Innovation and Learning Effect in Central Cities on Regional Common Prosperity |
Li Hongtao,Wang Lili |
(Department of Humanities and Social Sciences, Dalian University of Technology, Dalian 116024, China) |
|
|
Abstract The significance of the leading role of central cities and urban agglomerations is highly stressed in China. It is the key to achieving common regional prosperity in the new era by promoting the balance of regional development in the form of central cities and urban agglomerations. However, due to the endogenous and external influences of scientific and technological innovation on economic growth, the agglomeration-diffusion effect acts on regional economic development at the same time, making it difficult for the central city's scientific and technological innovation to promote the common prosperity of the regional development gap convergence.#br# The scientific and technological innovation of the central city mainly plays a leading role in the cities with the learning effect, that is, other large, medium and small cities in the region with the learning effect can receive the influence of the radiation diffusion effect of the central city's scientific and technological innovation. The path selection of the diffusion effect formed by technological innovation in the central city should be considered. Therefore, the model framework of evolutionary economic geography theory is introduced and the mechanism of central city technological innovation promoting regional common prosperity is analyzed from the perspective of dynamic evolution.#br#In the theoretical analysis, due to the objective existence of central city agglomeration-diffusion effects in the process of central city and regional development, cities will experience increasing returns to scale in the early stage of development, constant returns to scale in the mature stage of development, and constant returns to scale in the later stage of development. The returns to scale exhibit a decreasing nonlinear dynamic evolution, and the development of cities is also restricted by competition from other cities and objective resource endowments. On the basis of the theory of evolutionary economic geography, the study introduces the ecological logistic curve model, and establishes a common prosperity model between cities including the dynamic changes of agglomeration-diffusion effects through mathematical models, so as to integrate the endogenous and external problems of technological innovation in economic growth and it builds a unified analysis model to realize the analysis of the impact mechanism of technological innovation in central cities on regional common prosperity on the conditions of inter-city exchange competition and resource endowment constraints. Through mathematical model derivation and theoretical analysis, the study puts forward two research hypotheses: first, the central city has a leading role in both dimensions of technological innovation and learning effect, and by strengthening the technological innovation and learning effect of the central city, it can promote regional common prosperity; second, the spatial spillover effect of scientific and technological innovation exists in the path selection of location elements, and tends to form a spillover effect to regions with more economic scale, market scale and learning ability.#br#In the empirical analysis, the study takes the 19 largest urban agglomerations in China as the research object, establishes panel data from 2007 to 2020, and verifies the research hypothesis through fixed effects, endogenous tests, counterfactual estimation, and spatial econometric models. The research has found that the technological innovation and learning effect of the central city can significantly promote the common prosperity of the region. Among them, the improvement of central cities through scientific and technological innovation can play a role in promoting the economic growth of other cities in the urban agglomeration, and the expansion of the learning ability and market scale of central cities is conducive to narrowing the income gap between cities in the urban agglomeration. Second, scientific and technological innovation in central cities mainly forms spatial spillover effects through the economic connection and learning ability between cities.It is concluded that central city technological innovation can significantly promote the narrowing of urban agglomeration development gaps and achieve regional common prosperity. Meanwhile there is a path choice for the spatial spillover effect of scientific and technological innovation in the central city. The main path is the economic connection and learning ability between cities to form a driving effect on other large, medium and small cities in the urban agglomeration. Therefore, it is essential to expand the spatial pattern of mutual integration between cities, and enhance the coordinated development of scientific and technological innovation in urban agglomerations for the high-quality development of large, medium and small urban agglomerations.#br#
|
Received: 06 July 2022
|
|
|
|
|
[1] MARTIN R, SUNLEY P. Towards a developmental turn in evolutionary economic geography[J]. Regional Studies, 2015, 49(5):712-732. [2] COMMENDATORE P, KUBIN I, PETRAGLIA C, et al. Regional integration, international liberalisation and the dynamics of industrial agglomeration[J]. Journal of Economic Dynamics and Control, 2014, 48:265-287. [3] COENEN L, ASHEIM B, BUGGE M M, et al. Advancing regional innovation systems: what does evolutionary economic geography bring to the policy table[J]. Environment and Planning C: Government and Policy,2017,35(4):600-620. [4] BALLAND P A, RIGBY D. The geography of complex knowledge[J]. Economic Geography,2017,93(1):1-23. [5] 陈昭,刘珊珊,邬惠婷,等.创新空间崛起、创新城市引领与全球创新驱动发展差序格局研究[J].经济地理,2017,37(1):23-31,9. [6] 刘安国,张越,张英奎.新经济地理学理论扩展视角下的区域协调发展理论研究——综述与展望[J].经济问题探索,2014,35(11):184-190. [7] COOKE P. Evolutionary complexity geography and the future of regional innovation and growth policies[J]. Resilience and Regional Dynamics,2018,5(2):1-30. [8] AGHION P, JARAVEL X. Knowledge spillovers, innovation and growth[J]. The Economic Journal,2015,125(583):533-573. [9] TRIGUERO A, FERNNDEZ, SARA. Determining the effects of open innovation: the role of knowledge and geographical spillovers[J]. Regional Studies, 2018,52(5):632-644. [10] 吕拉昌,孙飞翔,黄茹.基于创新的城市化——中国270个地级及以上城市数据的实证分析[J].地理学报,2018,73(10):1910-1922. [11] 曹清峰,倪鹏飞,马洪福.科技创新对中国城市群协调发展的影响研究——基于城市可持续竞争力的分析[J].北京工业大学学报(社会科学版),2020,20(2):51-58. [12] 李洪涛,王丽丽.中心城市科技创新对城市群结构体系的影响[J].中国科技论坛,2020,36(7):170-179. [13] 李洪涛,王丽丽.中心城市科技创新与城市群产业高级化及多样化[J].科研管理,2022,43(1):41-48. [14] FLETCHER J A. Evolutionary game theory, natural selection, and darwinian dynamics[J]. Journal of Mammalian Evolution, 2006, 13(2):157-159. [15] 王钦.技术范式、学习机制与集群创新能力——来自浙江玉环水暖阀门产业集群的证据[J].中国工业经济,2011,28(10):141-150. [16] 黄凯南.演化博弈与演化经济学[J].经济研究,2009,44(2):132-145. [17] ROGERS E M . Diffusion of innovations[M].Free Press,2003. [18] 黄凯南.制度演化经济学的理论发展与建构[J].中国社会科学,2016,37(5):65-78. [19] 黄凯南.演化经济学的数学模型评析[J].中国地质大学学报(社会科学版),2013,13(3):83-90. [20] 陈平.劳动分工的起源和制约:从斯密困境到广义斯密原理[J].经济学(季刊), 2002,1(1):227-248. [21] 黄凯南,乔元波.产业技术与制度的共同演化分析——基于多主体的学习过程[J].经济研究,2018,53(12):161-176. [22] 高培勇,樊丽明,洪银兴,等.深入学习贯彻习近平总书记重要讲话精神加快构建中国特色经济学体系[J].管理世界,2022,38(6):1-56. [23] 曾鹏,李洪涛.城市行政级别、贸易开放度对区域收入的影响及其空间效应[J].云南师范大学学报(哲学社会科学版),2020,52(2):111-122. [24] 湛泳,李珊.金融发展、科技创新与智慧城市建设——基于信息化发展视角的分析[J].财经研究,2016,42(2):4-15. [25] 杨明海,张红霞,孙亚男,等.中国八大综合经济区科技创新能力的区域差距及其影响因素研究[J]. 数量经济技术经济研究,2018,35(4):3-19. [26] 姚东旻,宁静,韦诗言.老龄化如何影响科技创新[J].世界经济,2017,40(4):105-128. [27] 郭峰,洪占卿.贸易开放、地区市场规模与中国省际通胀波动[J].金融研究,2013,56(3):73-86. [28] 李海超,范诗婕.我国学习型区域创新系统成熟度评价[J].现代经济探讨,2012,31(9):29-33. [29] 邓明,钱争鸣.我国省际知识生产及其空间溢出的动态时变特征——基于Spatial SUR模型的经验分析[J].数理统计与管理,2013,32(4):571-585. [30] 方创琳.中国城市发展方针的演变调整与城市规模新格局[J].地理研究,2014,33(4):674-686. [31] 柯善咨,赵曜.产业结构、城市规模与中国城市生产率[J].经济研究,2014,49(4):76-88,115. [32] 蒋伏心,高丽娜.区际知识溢出不对称、产业区位与内生经济增长[J].财贸经济,2012,33(7):118-125. [33] SREDOJEVIC,DRAGOSLAVA,SLOBODAN CVETANOVIC,et al.Technological changes in economic growth theory: neoclassical,endogenous,and evolutionary-institutional approach[J].Economic Themes, 2016, 54(2):177-194.
|
|
|
|