Spatial structure characteristics and influencing factors of financial network of China based on geodetectors
Received date: 2022-11-08
Revised date: 2022-12-13
Online published: 2023-09-28
This study uses data on the geographical distribution of financial institutions in multiple industries and applies social network analysis methods to examine Chinese financial networks. Additionally, a geographic detector model is applied to explore the factors influencing the formation of the networks’ spatial structure. The results showed that: (1) Financial networks were found to be characterized by a “core-edge” structure, with core cities located mainly in the eastern region and peripheral cities located mainly in the central and western regions, while a decreasing degree of network spatial differentiation was found. In addition, the existence of spatial directionality was identified in the networks’ spatial structure. The development of financial networks in the central and western regions and peripheral cities was found to be dependent on a “radiation” process arising from the eastern regions and core cities, in which the “trickle-down effect” on the extra-territorial cities is fully exploited. In the eastern region, infrastructure is well developed and the business environment and other related conditions are relatively good due to the region’s high level of economic development and the presence of many financial enterprise headquarters. (2) The factors that influence the development of financial networks differ across the country, eastern and central and western regions, and core and peripheral cities, being closely related to the respective economic development level, market potential, key resources, locational conditions, and operating costs. The factors affecting the development of financial networks are more diverse and the interactions between the influencing factors are more balanced in the central and western regions and peripheral cities than those in the eastern region and core cities. (3) Merit selection, path dependence, and network proximity are the inherent mechanisms followed in the formation of the networks’ spatial structure; merit selection determines the spatial directionality of financial markets, while path dependency drives the formation of the networks’ spatial structure and determines “core-edge” characteristics. In addition, the stronger the financial linkages between cities, the greater the capability of cities with higher network accessibility to utilize network resources. The study contributes to the theory of “space flows” and, in the context of increasing economic and financial integration, points to the need for governments at all levels to strengthen financial cooperation between cities, and to do so at a larger scale. While promoting financial and economic development, attention should be paid to unbalanced spatial structures, with particular recognition of the importance of promoting the coordinated development of cities in the central and western regions and of further leveraging the role of core cities as “radiation” drivers. Through its examination of the characteristics of the spatial structure of China’s financial network and its influencing factors, the study provides both policy recommendations regarding the optimization of financial resources allocation and a scientific basis for the formulation of policies aimed at promoting coordinated intercity development.
Key words: geodetector; financial network; spatial structure; influencing factors
Yu YANG , Futie SONG , Jie ZHANG . Spatial structure characteristics and influencing factors of financial network of China based on geodetectors[J]. Arid Land Geography, 2023 , 46(9) : 1524 -1535 . DOI: 10.12118/j.issn.1000-6060.2022.581
[1] | 李小建. 金融地理学理论视角及中国金融地理研究[J]. 经济地理, 2006, 23(5): 721-725. |
[1] | [Li Xiaojian. A theoretical review of financial geography and study of financial geography in China[J]. Economic Geography, 2006, 23(5): 721-725.] |
[2] | 王修华, 黄明. 金融资源空间分布规律: 一个金融地理学的分析框架[J]. 经济地理, 2009, 29(11): 1808-1811, 1815. |
[2] | [Wang Xiuhua, Huang Ming. Spatial distribution regularity of finance resource: An analytical framework of finance geography[J]. Economic Geography, 2009, 29(11): 1808-1811, 1815.] |
[3] | Kriljenko M J I C, Khandelwal P, Lehmann A. Financial integration in central America: Prospects and adjustment needs[J]. IMF Policy Discussion Papers, 2003: 2003/003, doi: 10.5089/97814 51974195.003. |
[4] | 王金哲, 王军, 余声启, 等. 城市网络视角下金融网络与经济增长质量: 影响效应与作用机制[J]. 统计与信息论坛, 2020, 35(3): 69-76. |
[4] | [Wang Jinzhe, Wang Jun, Yu Shengqi, et al. Research on financial development and economic performance from the perspective of urban network: Influence effect and mechanism[J]. Statistics & Information Forum, 2020, 35(3): 69-76.] |
[5] | 张虎, 周迪. 城市群金融等别视角下的长三角金融资源流动研究——以城市商业银行异地扩张为例[J]. 地理研究, 2016, 35(9): 1740-1752. |
[5] | [Zhang Hu, Zhou Di. Financial resource flows in Yangtze River Delta from the perspective of financial gradation city in urban agglomerations: A case study of city commercial banks’ expansion[J]. Geographical Research, 2016, 35(9): 1740-1752.] |
[6] | 张杰, 盛科荣, 王传阳. 中国城市网络的核心-边缘结构演化研究——基于证券服务联系的视角[J]. 干旱区地理, 2022, 45(5): 1659-1670. |
[6] | [Zhang Jie, Sheng Kerong, Wang Chuanyang. Core-periphery dynamics of the urban network in China: A study based on securities service relationships[J]. Arid Land Geography, 2022, 45(5): 1659-1670.] |
[7] | 章屹祯, 汪涛, 张晗. 基于金融细分行业的长三角城市网络的组织模式及驱动因素[J]. 地理科学进展, 2022, 41(4): 567-581. |
[7] | [Zhang Yizhen, Wang Tao, Zhang Han. Organizational models and driving factors of the Yangtze River Delta urban network based on different financial industries[J]. Progress in Geography, 2022, 41(4): 567-581.] |
[8] | 任会明, 叶明确, 余运江. 中国三大城市群金融网络空间结构与演化特征[J]. 经济地理, 2021, 41(12): 63-73. |
[8] | [Ren Huiming, Ye Mingque, Yu Yunjiang. Spatial structure and evolution characteristics of financial network in three major urban agglomerations of China: A case study of Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta[J]. Economic Geography, 2021, 41(12): 63-73.] |
[9] | 季菲菲, 陈雯, 魏也华, 等. 长三角一体化下的金融流动格局变动及驱动机理——基于上市企业金融交易数据的分析[J]. 地理学报, 2014, 69(6): 823-837. |
[9] | [Ji Feifei, Chen Wen, Wei Yehua, et al. Changing financial flow patterns and driving mechanisms of financial flows under the integration of the Yangtze River Delta: An analysis of the financial transaction data of listed companies[J]. Acta Geographica Sinica, 2014, 69(6): 823-837.] |
[10] | 赵金丽, 盛彦文, 张璐璐, 等. 基于细分行业的中国城市群金融网络演化[J]. 地理学报, 2019, 74(4): 723-736. |
[10] | [Zhao Jinli, Sheng Yanwen, Zhang Lulu, et al. Evolution of urban agglomeration financial network in China based on subdivision industry[J]. Acta Geographica Sinica, 2019, 74(4): 723-736.] |
[11] | 王劲峰, 徐成东. 地理探测器: 原理与展望[J]. 地理学报, 2017, 72(1): 116-134. |
[11] | [Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134.] |
[12] | 李佳洺, 陆大道, 徐成东, 等. 胡焕庸线两侧人口的空间分异性及其变化[J]. 地理学报, 2017, 72(1):148-160. |
[12] | [Li Jiaming, Lu Dadao, Xu Chengdong, et al. Spatial heterogeneity and its changes of population on the two sides of Hu Line[J]. Acta Geographica Sinica, 2017, 72(1): 148-160.] |
[13] | Porteous D J. The geography of finance: Spatial dimensions of intermediary behavior[M]. Vermont: Avebury, 1995. |
[14] | 武巍, 刘卫东, 刘毅. 西方金融地理学研究进展及其启示[J]. 地理科学进展, 2005, 24(4): 19-27. |
[14] | [Wu Wei, Liu Weidong, Liu Yi. Progress in financial geography in western countries and its implications for Chinese geographers[J]. Progress in Geography, 2005, 24(4): 19-27.] |
[15] | 贺灿飞, 刘浩. 银行业改革与国有商业银行网点空间布局——以中国工商银行和中国银行为例[J]. 地理研究, 2013, 32(1): 111-122. |
[15] | [He Canfei, Liu Hao. Banking reform and locational strategy of state-owned commercial banks in China: An empirical study of Industrial and Commercial Bank of China and Bank of China[J]. Geographical Research, 2013, 32(1): 111-122.] |
[16] | Wójcik D. Securitization and its footprint: The rise of the US securities industry centres1998—2007[J]. Journal of Economic Geography, 2011, 11(6): 925-947. |
[17] | Clark G L, Almond S, Strauss K. The home, pension savings and risk aversion: Intentions of the defined contribution pension plan participants of a London-based investment bank at the peak of the bubble[J]. Social Science Electronic Publishing, 2012, 49(6): 1251-1273. |
[18] | Wray F. Rethinking the venture capital industry: Relational geographies and impacts of venture capitalists in two UK regions[J]. Journal of Economic Geography, 2012, 12(1): 297-319. |
[19] | 王艳华, 赵建吉, 刘娅娜, 等. 中国金融产业集聚空间格局与影响因素——基于地理探测器模型的研究[J]. 经济地理, 2020, 40(4): 125-133. |
[19] | [Wang Yanhua, Zhao Jianji, Liu Ya’na, et al. The spatial pattern of China’s financial industry agglomeration and its influencing factors: A study based on the geographical detector model[J]. Economic Geography, 2020, 40(4): 125-133.] |
[20] | 朱向东, 周心怡, 朱晟君, 等. 中国城市绿色金融及其影响因素——以绿色债券为例[J]. 自然资源学报, 2021, 36(12): 3247-3260. |
[20] | [Zhu Xiangdong, Zhou Xinyi, Zhu Shengjun, et al. The development of Chinese urban green finance and its influencing factors: An empirical analysis based on green bond[J]. Journal of Natural Resources, 2021, 36(12): 3247-3260.] |
[21] | Borgatti S P, Everett M G. A graph-theoretic perspective on centrality[J]. Social Networks, 2006, 28(4): 466-484. |
[22] | Mahutga M C, Ma X, Smith D A, et al. Economic globalisation and the structure of the world city system: The case of airline passenger data[J]. Urban Studies, 2010, 47(9): 1925-1947. |
[23] | Amiti M, Javorcik B. Trade costs and location of foreign firms in China[J]. Journal of Development Economics, 2010, 85(1): 129-149. |
[24] | 盛科荣, 杨雨, 孙威. 中国城市网络中心性的影响因素及形成机理——基于上市公司500强企业网络视[J]. 地理科学进展, 2019, 38(2): 248-258. |
[24] | [Sheng Kerong, Yang Yu, Sun Wei. Determinates and mechanisms of degree centrality in the urban network in China: A study based on corporate networks of the largest 500 listed companies[J]. Progress in Geography, 2019, 38(2): 248-258.] |
[25] | 任英华, 徐玲, 游万海. 金融集聚影响因素空间计量模型及其应用[J]. 数量经济技术经济研究, 2010, 27(5): 104-115. |
[25] | [Ren Yinghua, Xu Ling, You Wanhai. A spatial econometric model and its application on the factors of financial industry agglomeration[J]. The Journal of Quantitative & Technical Economics, 2010, 27(5): 104-115.] |
[26] | 潘峰华, 夏亚博, 刘作丽. 区域视角下中国上市企业总部的迁址研究[J]. 地理学报, 2013, 68(4): 449-463. |
[26] | [Pan Fenghua, Xia Yabo, Liu Zuoli. The relocation of headquarters of public listed firms in China: A regional perspective study[J]. Acta Geographica Sinica, 2013, 68(4): 449-463.] |
[27] | 吴卫星, 张旭阳, 吴锟. 金融素养对家庭负债行为的影响——基于家庭贷款异质性的分析[J]. 财经问题研究, 2019(5): 57-65. |
[27] | [Wu Weixing, Zhang Xuyang, Wu Kun. The impact of financial literacy on household debt behavior: An analysis based on the heterogeneity of household loans[J]. Research on Financial and Economic Issues, 2019(5): 57-65.] |
[28] | 刘军. 整体网分析——UCINET软件实用指南[M]. 第二版. 上海: 格致出版社, 2014. |
[28] | [Liu Jun. Lectures on whole network approach: A practice guide to UCINET[M]. 2nd ed. Shanghai: Truth & Wisdom Press, 2014.] |
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