Financial spatial distribution, heterogeneity and industrial layout

ZHANG Hui1 LIU Peng2 YU Tao2 AN Husen2 QI Anbang1

(1.Business School of Nankai University, Tianjin , China 300071)
(2.School of Economics, Nankai University, Tianjin , China 300071)
【Knowledge Link】spatial economics

【Abstract】This paper focuses on the significant practical issue in the current stage of China’s regional coordinated economic development strategy, namely, the ways in which the regional economy uses the finance power to promote the balanced distribution of industries. In addition, it proceeds from the basic category of special financial location and knowledge heterogeneity. Furthermore, this paper analyzes the impact of space differences of the financial services on the layout of the entity industry. From the perspective of financial service efficiency and capital allocation, we theoretically analyze the effect of the financial practitioner scale on industrial agglomeration by constructing a two–region, three–department Footloose Capital model including the financial sector. Numerical simulation indicates that although the financial practitioner scale promotes industrial agglomeration, as an enhancement of financial knowledge heterogeneity and information diffusion, the financial agglomeration’s marginal promotion becomes weaker. As the trade freedom increases, the marginal promotion becomes stronger. Using the data of 31 provinces (municipalities directly under the central government and autonomous regions) between 2005 and 2014, we conduct an empirical test on the numeric simulation results. The policy implications are to speed up financial heterogeneity based on the foundation of advanced development in the existing financial centers and develop multi–level financial system in China. Simultaneously, the openness degree of financial information should be strengthened to ensure that the financial services can effectively cover the central and western regions and achieve coordinated development of the regional economy. Furthermore, it is reasonable to implement the appropriate protective policies for the backward areas at the current stage.

【Keywords】 spatial economics; financial practitioner scale; knowledge heterogeneity; information diffusion; industrial agglomeration;


【Funds】 General Project of National Natural Science Foundation of China (71573142) Project of Special Research Foundation of Doctoral Program of Higher Educational Institution (2013000111036)

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    [1]. ① The data are taken from the WIND database. [^Back]

    [2]. ① As an important financial collateral, real estate is an important financial resource. In this sense, it belongs to the “virtual economy” category; and from its consumption property, real estate depends on the construction industry, so it belongs to the “real economy” category. Indeed, China’s current situation is finance, and the real estate industry is closely linked. The impact of the real estate on the entity industrial economy is no less than that of finance on the real industrial economy. But in this paper, our discussion is based on the “duality” feature [22] of financial resources: production factors with resource attribute, financial capital, resource allocation function, and financial services or financial support. Therefore, in the construction of the theoretical model, the financial sector, on the one hand, provides the financial capital needed by entity industrial production (including the real estate industry), and on the other hand, produces financial contracts to provide a carrier for the flow of financial capital, reflecting its resource allocation function. [^Back]

    [3]. ① Due to data availability, the share of agricultural consumption is measured by the average of the proportion of the output value of the primary industry in the whole GDP during 2005–2014. [^Back]

    [4]. ② Industrial process is generally accompanied by the continuous increase in the degree of geographical agglomeration.[27] In this sense, industrial agglomeration, on the one hand, reflects the industrial layout and the overall development level of the region. Therefore, in this paper, we select the industrial agglomeration, a comprehensive indicator, instead of using the actual economic indicators of industrial share in each region to refer to the regional industrial layout. [^Back]

    [5]. ① This paper does not include the interaction term as a separate variable into the model due to the following reasons. In the theoretical model, the financial practitioner scale is the main determinant of industrial agglomeration, which embodies the mechanism of financial practitioners’ influence on capital allocation efficiency through financial contract design. The impact mechanism of the interaction term on industrial agglomeration is indirectly achieved mainly by influencing the production efficiency of financial contracts. Therefore, the model design is reasonable. [^Back]

    [6]. ② Controversies still exist on the selection of the measurement indicator and method of industrial agglomeration. According to the existing research methods and conclusions,[29–32] considering the spatial scale, the degree of industry refinement, and the theoretical analysis level of this study, we use location entropy to construct the industrial agglomeration index. [^Back]

    [7]. ① The rules of industry merging are as follows: non–metallic mining industry, mining auxiliary activities, and other mining industries are merged into “non–metallic mining industry and other”; food manufacturing, sugar manufacturing industry, and canned manufacturing industry are merged into “food manufacturing”; beverage manufacturing and liquor manufacturing industry are merged into “beverage manufacturing”; automobile manufacturing, railways, ships, aerospace and other transportation equipment manufacturing, and transportation equipment manufacturing industry are merged into a new “transportation equipment manufacturing industry”; rubber products industry and plastic products industry are merged into rubber and plastic products industry; electricity, heat production and supply industry, gas production and supply industry, and water production and supply industry are merged into “electricity, heat and water production, and supply industry”; and metal products, machinery and equipment repair industry, handicrafts, and other manufacturing industry are merged into “handicrafts and other manufacturing industries.” [^Back]

    [8]. ② The discussion on knowledge innovation and knowledge worker heterogeneity refers to the study by Berliant and Fujita,[23, 25] and Fujita.[24] [^Back]

    [9]. ① The Chi2 of the Hausman test is 14.02, and the null hypothesis is rejected at the 5% significance level, so the fixed effect model is adopted. [^Back]

    [10]. ① The model with the interaction term refers to the discussion in the study by Wooldridge.[44] [^Back]


    [1]Mc Kinnon R. I. Money and Capital in Economic Development. New York: Brookings Institution Press, 1973.

    [2]Shaw, E. S. Financial Deepening in Economic Development. Oxford: Oxford University Press, 1973.

    [3] Jiang, S. & Song, Y. Economic Perspectives (经济学动态), (8): 97–104 (2014).

    [4] Laulajainen (Swenden). Financial Geography: from the Perspective of Financier (金融地理学: 金融家的视角), Meng, X. (trans), Beijing: China Commerce and Trade Press, (2001).

    [5] Wang, Z. The Regional Asymmetric Effect of Chinese Monetary Policy (中国货币政策区域非对称性效应), Beijing: Social Sciences Academic Press, (2011).

    [6] Song, C. The Journal of Quantitative & Technical Economics (数量经济技术经济研究), (10): 120–130 (2007).

    [7] Zhang, J. China Regional Finance Analysis (中国区域金融分析), Beijing: China Economic Publishing House, (1995).

    [8] Li, X. & Li, Z. On Economics Problems (经济问题), (8): 19–21 (2003).

    [9] Qi, A. Project Management (Second Version) (项目管理学 (第2版)), Beijing: China Science Publishing & Media Ltd. (2012).

    [10] Zhang, J. & Zeng, Y. Journal of Finance and Economics (财经研究), (4): 37–45 (2005).

    [11] Tang, P. & Yang, S. China Industrial Economics (中国工业经济), (7): 109–126 (2016).

    [12] Yao, Y. Journal of Finance and Economics (财经研究), (12): 129–139 (2009).

    [13] Jachapala, A. (US), Knowledge Management: an Itengration Method (知识管理:一种集成方法), An, X. (trans), Beijing: China Renmin University Press, (2011).

    [14] Bian, Y. Social Sciences in China (中国社会科学), (3): 136–146 (2004).

    [15] Granovetter, M. (US) & Swedberg, R. (Sweden) The Sociology of Economic Life (经济生活中的社会学), Qu, T. et al. (trans), Shanghai: Century Publishing Group, (2014).

    [16] Che, X., Bu, H., Liang, X., Wang, S., Wang, T. et al. Journal of Management Sciences in China (管理科学学报), (3): 16–29 (2012).

    [17] Li, L., Ding, Y. & Liu, Z. Journal of Financial Research (金融研究), (5): 113–123 (2011).

    [18] Yu, Y., Xuan, Y. & Shen, Y. The Journal of World Economy (世界经济), (2): 93–116 (2013).

    [19]Clark, G. Money Flows like Mercury:the Geography of Global Finance. Geografiska Annaler, 2005, 87 (2): 99–112.

    [20] Yan, C. Economic Research Journal (经济研究), (11) : 48–60 (2012).

    [21] An, H. Principles of New Economic Geography (新经济地理学原理), Beijing: Economic Science Press, (2009).

    [22] Bai, Q. Introduction to Sustainable Development of Finance (金融可持续发展研究导论), Beijing: China Financial Publishing House, (2001).

    [23] Berliant, M., and M., Fujita. Dynamics of Knowledge Creation and Transfer: The Two Person Case. MPRAWorking Paper, 2007.

    [24]Fujita, M. Towards the New Economic Geography in the Brain Power Society. Regional Science and Urban Economics, 2007, 37 (4): 482–490.

    [25]Berliant, M., and M., Fujita. Culture and Diversity in Knowledge Creation. Regional Science&Urban Economics, 2012, 42 (4): 648–662.

    [26] An, H. & Liu, J. Journal of Finance and Economics (财经研究), (10): 84–96 (2014).

    [27] Wang, Y. & Sheng, D. Management World (管理世界). (1): 101–114 (2013).

    [28] Long, X., Zhang, J. & Zhang, X. China Economic Quarterly (经济学季刊), (3): 1563–1590 (2015).

    [29] Zhang, X. & Wang, Y. The Journal of World Economy (世界经济), (9): 15–26 (2009).

    [30] Zhou, B., Zhang, Q. & Zhang, C. Management World (管理世界), (1): 172–173 (2012).

    [31] Yuan, H., Zhang, H. & Zeng, H. China Industrial Economics (中国工业经济) (9): 38–50 (2014).

    [32] Sun, X. & Guo, X. China Industrial Economics (中国工业经济), (11): 78–93 (2015).

    [33] Yin, G. Doctoral thesis, Nankai University, (2009).

    [34] Wang, S. Journal of Finance and Economics (财经研究), (4): 59–68(2012).

    [35] Huang, J. Journal of Regional Finance Research (区域金融研究), (3): 26–30(2011).

    [36] Li, J. Nankai Economics Studies (南开经济研究, (3): 87–107(2009).

    [37] Chen, F. Doctoral thesis, Nankai University, (2009).

    [38]Poncet, S. Measuring Chinese Domestic and International Integration. China Economic Review, 2003, 14 (1): 1–22.

    39. Ni, P., Liu, W. & Huang, S. Economic Research Journal (经济研究), (5): 121–132 (2014).

    40. Xian, G. & Wen, D. Management World (管理世界), (12): 18–31 (2006).

    [41] Jin, Y., Chen, Z. & Lu, M. Economic Research Journal (经济研究), (4): 79–89 (2006).

    [42] Zhan, X. China Soft Science (中国软科学), (8): 166–177 (2012).

    [43] Chen, Z. & Ma, H.The Journal of Quantitative & Technical Economics (数量经济技术经济研究), (6): 21–36 (2011).

    [44]Wooldridge, J. M. Introductory Econometrics:A Modern Approach (5th Edition).Beijing: Tsinghua University Press, 2014.

    [45] An, H. & Li, J. Academic Monthly (学术月刊), (1): 73–79 (2010).

This Article


CN: 11-3536/F

Vol , No. 12, Pages 40-57

December 2016


Article Outline



  • 1 Introduction
  • 2 Theoretical model
  • 3 Econometric model and data description
  • 4 Conclusions and inspirations
  • Footnote