Detecting Automobile Clustering in China by Using Firm-Level Di* Statistic

DOI

Bibliographic Information

Other Title
  • 中国自動車企業の集積―企業レベル統計量Di*による検出

Abstract

<p>Which Chinese automobile firms participated in the clustering? This paper introduces the Di* statistic, a modification of the firm-level Di statistic, which Scholl and Brenner (2016) proposed to identify industrial clusters without predetermined borders to address the Modifiable Areal Unit Problem (MAUP). Utilizing this MAUP-free method and a meticulously constructed micro-geographic dataset based on the firm-level dataset of the 2008 China Economic Census, this paper detects clustered automobile firms across mainland China for the first time.</p><p>The geographical distribution of automobile industry clusters indicates that clustering of the automobile firms is not limited to the well-known six major automobile industry clustering areas but also extends to most other regions of mainland China. It is noteworthy that automobile firms do not widely agglomerate throughout these regions but rather cluster in select prefectures, counties, towns, or villages. The “Major Six” areas are too vast for effective automobile cluster analysis.</p><p>Domestic private enterprises play a significantly important role in China’s automobile clustering. However, foreign-funded enterprises and large state-holding enterprises have also contributed to automobile clustering in China.</p><p>Provincial-level regions are categorized based on the ownership types of clustered automobile firms, with a primary focus on large and medium-sized enterprises. These regions can generally be classified into: (i) clustering regions dominated by domestic non-state-holding enterprises (Zhejiang, Henan, Jiangsu, Shandong, Hebei), (ii) clustering regions dominated by state-holding enterprises (Hubei, Anhui, Heilongjiang, Jiangxi, Sichuan, Guizhou, Inner Mongolia), (iii) clustering regions dominated by foreign-funded enterprises (Guangdong, Beijing, Tianjin, Shanghai, Liaoning), and (iv) mixed type clustering regions (Chongqing, Jilin, Fujian, Hunan, Guangxi, Shaanxi, Hainan).</p><p>However, automobile firms only cluster in specific areas within each province, and the clustering in these areas exhibits various distinct characteristics. As an example of detailed analysis of clustering within a province, the clustering patterns of automobile firms within Jiangsu Province are examined by plotting clustered firms on the map of Jiangsu Province. In Jiangsu Province, automobile firms predominantly cluster along the Shanghai-Nanjing railway. While majority of clustered firms are domestic non-state-holding enterprises in Jiangsu Province overall, there are regions like Nanjing where subsidiaries of major state-holding automobile groups such as SAIC play a significant role, as well as regions like the eastern area of Suzhou where foreign enterprises dominate, located close to the cluster areas in the northwest of Shanghai.</p>

Journal

  • Asian Studies

    Asian Studies advpub (0), 2024

    Japan Association for Asian Studies

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