城市群经济网络与经济增长——基于大数据与网络分析方法的研究

借助大数据时代下获得的海量数据，本文分析了长三角城市群的经济网络特征，重点研究了城市群经济网络的增长效应。首先，构建了长三角城市群的人口流动网络、企业组织网络与电子商务网络，对其各自的网络结构特征进行了对比。其次，将网络分析方法与空间计量模型结合起来，使用扩展的J检验方法对不同网络结构下的模型设定方法进行了识别，考察了经济网络带来的溢出效应对于城市群经济增长的影响。分析结果显示，三种经济网络下长三角城市群均呈现出了“中心-外围”的网络结构，其中上海、杭州、苏州、南京及无锡位于城市群经济网络的核心圈层。对网络结构的模型识别结果显示，中心城市在长三角城市群经济网络的溢出效应中扮演着重要角色。具体而言，在人口流动网络下，资本、政府行为存在显著为负的网络溢出效应；在企业组织网络下，人口规模、对外开放呈现出显著为正的网络溢出效应；在电子商务网络下，政府行为存在显著为负的网络溢出效应，对外开放呈现出显著为正的网络溢出效应。

Economic Networks and Economic Growth of Urban Agglomeration: An Integrated Approach of Big Data and Network Analysis

With the vast amounts of data obtained under the age of Big Data, this paper analyses the economic network character of the Yangtze River Delta, and focuses on the growth effect of economic networks. Firstly, we construct the population migration network, enterprise organization network and E-commerce network, and compare their network characters. Secondly, combining the network analysis method and spatial econometric model, using the extension of J test to choose two social network models that apply to different network structures, we investigate the impacts of the spillover effect caused by economic network on the economic growth of the urban agglomeration. Research shows that all the three kinds of economic network of Yangtze River Delta have "center - periphery" structures, and Shanghai, Hangzhou, Suzhou, Nanjing, Wuxi locate at the core circle of the three networks. Regression results show that, center cities play an important role in the spillover effect under economic networks. Specifically, capital factor and local government have a negative spillover effect in the population flow network; for the enterprise organization network, population and openness have a positive spillover effect; for the E-commerce network, local government shows a negative spillover effect and openness shows a positive spillover effect.