PROGRESS IN GEOGRAPHY ›› 2023, Vol. 42 ›› Issue (1): 27-41.doi: 10.18306/dlkxjz.2023.01.003

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Spatiotemporal variation of housing price in megacities based on household registration: Taking Changsha City as an example

HUANG Tuofu1(), HE Tian2,*(), ZHU Xiang2   

  1. 1. School of Engineering Management, Hunan University of Finance and Economics, Changsha 410205, China
    2. College of Geography Science, Hunan Normal University, Changsha 410081, China
  • Received:2022-06-07 Revised:2022-08-23 Online:2023-01-28 Published:2023-03-28
  • Contact: HE Tian;
  • Supported by:
    Major Program of the National Social Science Foundation of China(18ZDA040)


In order to reveal the differences in the spatial pattern of housing prices among different buyers in China's megacities, this study divided the household registration of housing buyers from Changsha City into two categories and depicted the spatial and temporal evolution of housing price patterns for these two groups of buyers respectively. A spatiotemporal auto regression model (STAR) was employed to analyze the influence of location, landscape, neighborhood, and other factors on the housing prices. We found that: 1) The housing price gradient of Changsha's non-registered household buyers has fallen faster than others while their space is more smooth. 2) The overall pattern of Changsha housing price space with "one river, two banks, and two centers" has gradually emerged. The influence of traditional central business district (CBD)—the Wuyi Square—on housing prices is declining, but it maintains a high level of housing price gradient and price elasticity for the locals. The sub-center Meixi Lake New City has a greater impact on the housing prices for outside buyer. 3) Outside buyers have a higher propensity to pay for housing quality and neighboring facilities. 4) In the period of prosperity and regulation of the housing market, the transaction prices of surrounding housing projects have different effects on the two types of housing buyers. This study explored the causes of the spatial differentiation of housing prices between the two types of buyers from four aspects: Functional requirements, subjective factors, differences of policy, and economic motivations. In the context of "housing for living not for speculation", paying attention to the spatial structure of housing price of different groups of people and the changing trends of influencing factors will help to develop a deeper understanding of the housing regulation policy in megacities.

Key words: household registration, spatial structure of housing price, housing price impact factor, spatiotemporal auto regression hedonic model, Changsha City