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Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China

LI Jiaming,  ZHANG Wenzhong,  YU Jianhui,  CHEN Hongxia

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文章导航 > Chinese Geographical Science  > 2015 >  25(6): 698-712
LI Jiaming, ZHANG Wenzhong, YU Jianhui, CHEN Hongxia. Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China[J]. 中国地理科学, 2015, 25(6): 698-712. doi: 10.1007/s11769-015-0770-1
引用本文: LI Jiaming, ZHANG Wenzhong, YU Jianhui, CHEN Hongxia. Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China[J]. 中国地理科学, 2015, 25(6): 698-712. doi: 10.1007/s11769-015-0770-1
shu
LI Jiaming, ZHANG Wenzhong, YU Jianhui, CHEN Hongxia. Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China[J]. Chinese Geographical Science, 2015, 25(6): 698-712. doi: 10.1007/s11769-015-0770-1
Citation: LI Jiaming, ZHANG Wenzhong, YU Jianhui, CHEN Hongxia. Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China[J]. Chinese Geographical Science, 2015, 25(6): 698-712. doi: 10.1007/s11769-015-0770-1
shu

Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China

doi: 10.1007/s11769-015-0770-1
  • 1.

    Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049, China;

  • 3.

    Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

  • 4.

    School of Government, Central University of Finance and Economics, Beijing 100081, China

基金项目: Under the auspices of State Key Program of National Natural Science of China (No. 41230632), National Natural Science Foundation of China (No. 41301123, 41201169)
详细信息
    通讯作者:

    YU Jianhui. E-mail: Yujh@igssnrr.ac.cn

Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China

  • 1.

    Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049, China;

  • 3.

    Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

  • 4.

    School of Government, Central University of Finance and Economics, Beijing 100081, China

Funds: Under the auspices of State Key Program of National Natural Science of China (No. 41230632), National Natural Science Foundation of China (No. 41301123, 41201169)
More Information
    Corresponding author: YU Jianhui. E-mail: Yujh@igssnrr.ac.cn

  • 摘要: To study the difference of industrial location among different industries, this article is to test the spatial agglomeration across industries and firm sizes at the city level. Our research bases on a unique plant-level data set of Beijing and employs a distance-based approach, which considers space as continuous. Unlike previous studies, we set two sets of references for service and manufacturing industries respectively to adapt to the investigation in the intra-urban area. Comparing among eight types of industries and different firm sizes, we find that: 1) producer service, high-tech industries and labor-intensive manufacturing industries are more likely to cluster, whereas personal service and capital-intensive industries tend to be randomly dispersed in Beijing; 2) the spillover of the co-location of firms is more important to knowledge-intensive industries and has more significant impact on their allocation than business-oriented services in the intra-urban area; 3) the spatial agglomeration of service industries are driven by larger establishments, whereas manufacturing industries are mixed.
    Abstract: To study the difference of industrial location among different industries, this article is to test the spatial agglomeration across industries and firm sizes at the city level. Our research bases on a unique plant-level data set of Beijing and employs a distance-based approach, which considers space as continuous. Unlike previous studies, we set two sets of references for service and manufacturing industries respectively to adapt to the investigation in the intra-urban area. Comparing among eight types of industries and different firm sizes, we find that: 1) producer service, high-tech industries and labor-intensive manufacturing industries are more likely to cluster, whereas personal service and capital-intensive industries tend to be randomly dispersed in Beijing; 2) the spillover of the co-location of firms is more important to knowledge-intensive industries and has more significant impact on their allocation than business-oriented services in the intra-urban area; 3) the spatial agglomeration of service industries are driven by larger establishments, whereas manufacturing industries are mixed.
  • [1] Alfaro L, Chen M, 2014. The global agglomeration of multinational firms. Journal of International Economics, 94(2): 263-276. doi:  10.1016/j.jinteco.2014.09.001
    [2] Anselin L, 1995. Local indicators of spatial association—LISA. Geographical Analysis, 27(2): 93-115. doi:  10.1111/j.1538-4632.1995.tb00338.x
    [3] Arbia G, Espa G, Quah D, 2008. A class of spatial econometric methods in the empirical analysis of clusters of firms in the space. Empirical Economics, 34(1): 81-103. doi: 10.1007/ s00181-007-0154-1
    [4] Barlet M, Briant A, Crusson L, 2013. Location patterns of service industries in France: a distance-based approach. Regional Science and Urban Economics, 43(2): 338-351. doi:  10.1080/00343400500151806
    [5] Bertinelli L, Decrop J, 2005. Geographical agglomeration: Ellison and Glaeser's index applied to the case of Belgian manufacturing industry. Regional Studies, 39(5): 567-583. doi: 10. 1080/00343400500151806
    [6] Braunerhjelm P, Borgman B, 2004. Geographical concentration, entrepreneurship and regional growth: evidence from regional data in Sweden, 1975-1999. Regional Studies, 38(8): 929-947. doi:  10.1080/0034340042000280947
    [7] Briant A, Combes P P, Lafourcade M, 2010. Dots to boxes: do the size and shape of spatial units jeopardize economic geography estimations? Journal of Urban Economics, 67(3): 287-302. doi:  10.1080/0034340042000280947
    [8] Brülhart M, Sbergami F, 2009. Agglomeration and growth: Cross-country evidence. Journal of Urban Economics, 65(1): 48-63. doi:  10.1016/j.jue.2008.08.003
    [9] Carlos G R, José A, Álvarez L et al., 2013. Calculating intraurban agglomeration of economic units with planar and network K-functions: a comparative analysis. Urban Geography, 34: 2, 261-286. doi:  10.1080/02723638.2013.778655
    [10] Carod J M A, Antolín M C M, 2004. Firm size and geographical aggregation: an empirical appraisal in industrial location. Small Business Economics, 22(3-4): 299-312. doi: 10.1023/ B:SBEJ.0000022216.09083.76
    [11] Chen Hongxia, Li Guoping, 2011. Empirical study on effect of industrial structure change on regional economic growth of Beijing-Tianjin-Hebei Metropolitan Region. Chinese Geographical Science, 21(6): 708-714. doi:  10.1007/s11769-011-0478-9
    [12] Ciccone A, 2002. Agglomeration effects in Europe. European Economic Review, 46(2): 213-227. doi: 10.1016/S0014-2921 (00)00099-4
    [13] Clark G L, Gertler M S, Feldman M P, 2003. The Oxford Handbook of Economic Geography. Oxford: Oxford University Press.
    [14] Coe N M, 2001. A hybrid agglomeration? The development of a satellite-Marshallian industrial district in Vancouver's film industry. Urban Studies, 38(10): 1753-1775. doi: 10.1080/ 00420980120084840
    [15] Coe N M, Kelly P F, Yeung H W C, 2007. Economic Geography: A Contemporary Introduction. Oxford: Blackwell.
    [16] Devereux M P, Griffith R, Simpson H, 2004. The geographic distribution of production activity in the UK. Regional Science and Urban Economics, 34(5): 533-564. doi:  10.1016/S0166-0462(03)00073-5
    [17] Duranton G, Overman H G, 2005. Testing for localization using micro-geographic data. Review of Economic Studies, 72(4): 1077-1106. doi:  10.1111/0034-6527.00362
    [18] Ellison G, Glaeser E L, 1997. Geographic concentration in US manufacturing industries: a dartboard approach. Journal of Political Economy, 105(5): 889-927. doi:  10.1086/262098
    [19] Ellison G, Glaeser E L, Kerr W, 2010. What causes industry agglomeration? Evidence from coagglomeration patterns. American Economic Review, 100(3): 1195-1213. doi: 10.1257/aer. 100.3.1195
    [20] Fischer M M, Getis A, 2009. Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications. Berlin: Springer Science & Business Media.
    [21] Fujita M, 1988. A monopolistic competition model of spatial agglomeration: differentiated product approach. Regional Science and Urban Economics, 18(1): 87-124. doi: 10.1016/ 0166-0462(88)90007-5
    [22] Guillain R, Le Gallo J, 2010. Agglomeration and dispersion of economic activities in and around Paris: an exploratory spatial data analysis. Environment and planning B, 37(6): 961-981. doi:  10.1068/b35038
    [23] Goetz S J, Rupasingha A, 2002. High-tech firm clustering: implications for rural areas. American Journal of Agricultural Economics, 84(5): 1229-1236. doi:  10.1111/1467-8276.00383
    [24] Glaeser E L, Kallal H D, Scheinkman J A et al., 1992. Growth in cities. Journal of Political Economy, 100(6): 1126-1152.
    [25] Haining R P, 2003. Spatial Data Analysis. Cambridge: Cambridge University Press.
    [26] Henderson J V, 2003. Marshall's scale economies. Journal of Urban Economics, 53(1): 1-28. doi: 10.1016/S0094-1190(02) 00505-3
    [27] HUallachain B O, Leslie T F, 2009. Postindustrial manufacturing in a Sunbelt Metropolis: where are factories located in Phoenix? Urban Geography, 30(8): 898-926. doi:  10.2747/0272-3638.30.8.898
    [28] Krugman P, 1991a. Increasing returns and economic geography. Journal of Political Economy, 99(3): 483-499.
    [29] Krugman P, 1991b. Geography and Trade. Cambridge: MIT press.
    [30] Lin H L, Li H Y, Yang C H, 2011. Agglomeration and productivity: firm-level evidence from China's textile industry. China Economic Review, 22(3): 313-329. doi: 10.1016/j.chieco. 2011.03.003
    [31] Logan J R, Spielman S, Xu H et al., 2011. Identifying and bounding ethnic neighborhoods. Urban Geography, 32(3): 334-359. doi:  10.2747/0272-3638.32.3.334
    [32] Marcon E, Puech F, 2003. Evaluating the geographic concentration of industries using distance-based methods. Journal of Economic Geography, 3(4): 409-428. doi:  10.1093/jeg/lbg016
    [33] Marcon E, Puech F, 2010. Measures of the geographic concentration of industries: improving distance-based methods. Journal of Economic Geography, 10(8): 745-762. doi: 10.1093/jeg/ lbp056
    [34] Marshall A, 1890. Principles of Economics. London: Macmillan and Company, limited.
    [35] Mitchell A, 2005. The ESRI Guide to GIS Analysis. Redlands, CA: ESRI Press.
    [36] Morphet C S, 1997. A statistical method for the identification of spatial clusters. Environment and Planning A, 29(6): 1039-1055. doi:  10.1068/a291039
    [37] Ripley B D, 1976. The second-order analysis of stationary point processes. Journal of Applied Probability, 13(2): 255-266.
    [38] Ripley B D, 1977. Modelling Spatial Patterns. Journal of the Royal Statistical Society B, 39(2): 172-212.
    [39] Silverman B W, 1986. Density estimation for statistics and data analysis. New York: Chapman and Hall.
    [40] Van Oort F G, Atzema O A L C, 2004. On the conceptualization of agglomeration economies: the case of new firm formation in the Dutch ICT sector. The Annals of Regional Science, 38(2): 263-290. doi:  10.1007/s00168-004-0195-8
    [41] Venables A J, 1996. Equilibrium locations of vertically linked industries. International Economic Review, 37(2): 341-359.
    [42] Yang D Y R, Wang H K, 2008. Dilemmas of local governance under the development zone fever in China: a case study of the Suzhou region. Urban Studies, 45(5-6): 1037-1054. doi: 10. 1177/0042098008089852
    [43] Yeh A G O, Li X, 1999. Economic development and agricultural land loss in the Pearl River Delta, China. Habitat international, 23(3): 373-390. doi:  10.1016/S0197-3975(99)00013-2
    [44] Zhang Jingqiu, Chen Yelong, 2011. Industrial distribution and clusters of urban office space in Beijing. Acta Geopraphica Sinca, 66(10): 1299-1308. (in Chinese)
    [45] Zhang Xiaoping, Sun Lei, 2012. Manufacture restructuring and main Determinants in Beijing. Acta Geopraphica Sinca, 67(10): 1308-1316. (in Chinese)
    [46] Zhou Shangyi, Ji Limei, 2009. Commercial space succession in old city of Beijing-case of survey line of inner city in Beijing from 1996 to 2006. Scienta Geographica Sinica, 29(4): 493-499. (in Chinese)Acta Geopraphica Sinca, 66(10): 1299-1308. (in Chinese)
    [47] Zhang Xiaoping, Sun Lei, 2012. Manufacture restructuring and main Determinants in Beijing. Acta Geopraphica Sinca, 67(10): 1308-1316. (in Chinese)
    [48] Zhou Shangyi, Ji Limei, 2009. Commercial space succession in old city of Beijing-case of survey line of inner city in Beijing from 1996 to 2006. Scienta Geographica Sinica, 29(4): 493-499. (in Chinese)
    [49]  
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出版历程
  • 收稿日期:  2014-08-26
  • 修回日期:  2014-11-21
  • 刊出日期:  2015-06-27

Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China

doi: 10.1007/s11769-015-0770-1
  • 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China;
  • 3. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
  • 4. School of Government, Central University of Finance and Economics, Beijing 100081, China
    • 基金项目:  Under the auspices of State Key Program of National Natural Science of China (No. 41230632), National Natural Science Foundation of China (No. 41301123, 41201169)
    通讯作者: YU Jianhui. E-mail: Yujh@igssnrr.ac.cn
  • 收稿日期: 2014-08-26
  • 修回日期: 2014-11-21
  • 刊出日期: 2015-06-27

摘要: To study the difference of industrial location among different industries, this article is to test the spatial agglomeration across industries and firm sizes at the city level. Our research bases on a unique plant-level data set of Beijing and employs a distance-based approach, which considers space as continuous. Unlike previous studies, we set two sets of references for service and manufacturing industries respectively to adapt to the investigation in the intra-urban area. Comparing among eight types of industries and different firm sizes, we find that: 1) producer service, high-tech industries and labor-intensive manufacturing industries are more likely to cluster, whereas personal service and capital-intensive industries tend to be randomly dispersed in Beijing; 2) the spillover of the co-location of firms is more important to knowledge-intensive industries and has more significant impact on their allocation than business-oriented services in the intra-urban area; 3) the spatial agglomeration of service industries are driven by larger establishments, whereas manufacturing industries are mixed.

English Abstract

LI Jiaming, ZHANG Wenzhong, YU Jianhui, CHEN Hongxia. Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China[J]. 中国地理科学, 2015, 25(6): 698-712. doi: 10.1007/s11769-015-0770-1
引用本文: LI Jiaming, ZHANG Wenzhong, YU Jianhui, CHEN Hongxia. Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China[J]. 中国地理科学, 2015, 25(6): 698-712. doi: 10.1007/s11769-015-0770-1
shu
LI Jiaming, ZHANG Wenzhong, YU Jianhui, CHEN Hongxia. Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China[J]. Chinese Geographical Science, 2015, 25(6): 698-712. doi: 10.1007/s11769-015-0770-1
Citation: LI Jiaming, ZHANG Wenzhong, YU Jianhui, CHEN Hongxia. Industrial Spatial Agglomeration Using Distance-based Approach in Beijing, China[J]. Chinese Geographical Science, 2015, 25(6): 698-712. doi: 10.1007/s11769-015-0770-1
shu

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