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.