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has been cited by the following article:

• TITLE: Spatiotemporal Evolution Characteristics and Influencing Factors of China’s Automobile Market since Joining the WTO

  AUTHORS: Xibo Wu, Peiying Lyu, Changqiang Lai

  KEYWORDS: Automobile Market, Spatiotemporal Evolution, Spatial Separation of Production and Sales, DTW Cluster Analysis, Space Spillover Effect

  JOURNAL NAME: Journal of Geographic Information System, Vol.14 No.5, October 12, 2022

  ABSTRACT: Since joining the WTO, China’s automobile market has shown a rapid development trend, and the automobile market is becoming more and more important to China’s economic recovery and high-quality development. The automobile manufacturing industry is one of the pillar industries of China, but facing downward pressure since 2018. The paper studies spatiotemporal evolution characteristics and influencing factors of automobile market since WTO Accession using methods including ESDA, DTW cluster analysis and Spatial panel Dubin model. The result shows that: 1) China’s automobile sales have grown rapidly and three development stages have occurred since WTO Accession; 2) Four types of China’s automobile markets have significant spatial differentiation, while the same pattern present spatial agglomeration characteristics; 3) The crucial reasons for spatial separation of production and sales in China’s automobile market include implementation of purchase restrictions in more and more cities, gradual consolidation of spatial pattern of automobile production, and the fact that some automobile production areas are far away from consumer market; 4) The provincial spatial weighted average centers of automobile sales are mainly distributed in southeast Henan, and show a trend of moving to the southwest; 5) The estimated coefficients of factors such as GDP, financial added value, the proportion of highway, the volume of highway freight, and implementation of automobile consumption incentive policies are all significantly positive, and some factors have positive spatial spillover effects. Existing research on the automobile market lacks analysis based on long-time series data. This study uses long-time series data to provide a certain reference for future research in related directions.