资源科学 ›› 2017, Vol. 39 ›› Issue (2): 335-345.doi: 10.18402/resci.2017.02.15

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重庆市主城区住房价格影响因子的空间异质性

李颖丽(), 刘勇(), 刘秀华   

  1. 西南大学资源环境学院,重庆 400715
  • 收稿日期:2016-06-20 修回日期:2016-12-05 出版日期:2017-02-25 发布日期:2017-02-20
  • 作者简介:

    作者简介:李颖丽,女,河北唐山人,硕士生,研究方向为土地利用规划。E-mail:liyingli201011@163.com

  • 基金资助:
    国家自然科学基金项目(41101568);重庆市自然科学基金项目(cstcjjA00008)

Spatial heterogeneity in factors affecting Chongqing housing prices

Yingli LI(), Yong LIU(), Xiuhua LIU   

  1. College of Resources and Environment,Southwest University,Chongqing 400715,China
  • Received:2016-06-20 Revised:2016-12-05 Online:2017-02-25 Published:2017-02-20

摘要:

以2015年重庆市主城区2449个住宅小区均价数据为基础,通过比较特征价格模型、空间扩展模型和地理加权回归模型,对住房市场进行模拟,寻求探索多中心山地城市住房价格影响因子空间异质性的最佳方法,进而对其空间异质性进行研究,以期为多中心城市的房地产市场管理提供有益借鉴。结果表明:①空间扩展模型和地理加权回归模型均对特征价格模型有所改进,地理加权回归模型在模拟效果与估计精度两个方面均优于空间扩展模型,并可将具体空间模式可视化,是探索空间异质性的最佳方法;②房龄、到城市中心的距离、到城市次中心的距离是影响住房价格最为重要的因子;地形位指数显著影响住房价格,且地形愈趋于平坦,房价越高;③各影响因子对住房价格的影响在不同空间有显著差异。重庆住房价格影响因子的空间格局相比单中心城市更为复杂,主要与重庆山水分割和“多中心、组团式”的城市格局密切相关;④多中心结构减弱了住房子市场的垄断,增加了住房的有效供给。优质公共设施在中梁山、铜锣山之间的狭长地带聚集,而郊区公共设施供应不足,需加大资金投入来改善郊区住房对优质公共设施的可达性。

关键词: 住房价格, 影响因子, 空间异质性, 空间扩展模型, 地理加权回归模型, 重庆市主城区

Abstract:

Based on price data of 2,449 housing projects in the main district of Chongqing in 2015,we used hedonic price modeling,spatial expansion modeling and geographically weighted regression (GWR)modeling to simulate the spatial heterogeneity in impact factors of housing price for this polycentric mountainous city. After comparing the three models,we found that the spatial expansion model and the GWR model performed better than the hedonic price model,and the GWR model performed better than the spatial expansion model when considering effectiveness and accuracy. In addition,the GWR model proved to be an effective method to explore spatial heterogeneity,which can reflect the spatial patterns of heterogeneity visually. A few variables,such as building age,distance to city center,and distance to city subcenters,were the most important factors affecting housing prices. The variable of TPI had a significant effect on housing price. When the terrain was flatter,the price would get higher,too. The effect of each factor on housing price varied spatially and significantly. The spatial pattern of polycentric cities such as Chongqing was more complex than for monocentric cities. The complexity was mainly considered to be closely related to the constraints of natural barriers and strategies of polycentric urban development in Chongqing. Polycentric development broke the monopoly of the housing submarket and increased the effective supply of housing in limited spaces of Chongqing. However,high-profile houses are still concentrated in the narrow valley floors between Zhongliang and the Tongluo Mountains where high-quality public facilities are located. Considering the lag in supply of public facilities in suburbs,substantial funds are needed to improve the accessibility of suburban housing to better public facilities.

Key words: housing price, impact factors, spatial heterogeneity, spatial expansion model, geographically weighted regression model, the main district of Chongqing