地理科学进展 ›› 2017, Vol. 36 ›› Issue (8): 995-1005.doi: 10.18306/dlkxjz.2017.08.008

• 研究论文 • 上一篇    下一篇

空间功能视角下的公共服务对房价的影响——以成都市为例

张少尧1,2(), 宋雪茜3, 邓伟1,2,**()   

  1. 1. 中国科学院水利部成都山地灾害与环境研究所/山区发展研究中心,成都 610041
    2. 中国科学院大学,北京 100049
    3. 成都信息工程大学管理学院,成都 610225
  • 出版日期:2017-08-31 发布日期:2017-08-28
  • 通讯作者: 邓伟 E-mail:zhangsyxs@163.com;dengwei@imde.ac.cn
  • 作者简介:

    作者简介:张少尧(1993-),四川巴中人,博士研究生,主要研究方向为山区聚落与城镇化,E-mail: zhangsyxs@163.com

  • 基金资助:
    国家自然科学基金项目(41471469,41601141);中国科学院院长基金(2017);四川省软科学研究计划项目(2015ZR0115)

Impact of public services on housing prices in different functional spaces:A case study of metropolitan Chengdu

Shaoyao ZHANG1,2(), Xueqian SONG3, Wei DENG1,2,*()   

  1. 1. Institute of Mountain Hazards and Environment/ Research Center for Mountain Development,CAS, Chengdu 610041, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3.College of Management, Chengdu University of Information Technology, Chengdu 610225, China
  • Online:2017-08-31 Published:2017-08-28
  • Contact: Wei DENG E-mail:zhangsyxs@163.com;dengwei@imde.ac.cn
  • Supported by:
    National Natural Science Foundation of China, No.41471469, No.41601141;Presidential Foundation of the Chinese Academy of Sciences, China(2017);Soft Science Research Projects of Science and Technology Office of Sichuan Province, No.2015ZR0115

摘要:

房价的快速上涨和城市内部房价的巨大差异引起社会广泛关注,调控房价,防止局部区域房价过热势在必行。本文从城市空间功能的视角出发,以成都市2016年房价为例,基于地理探测器分析公共服务对房价的影响。结果表明:成都平均房价为8480元/m2,并从市中心沿交通环线和放射状干线同时向郊区递减,形成圈层加放射格局,总体上呈现西高东低、南高北低的特点。公共服务(主要包括医疗、金融和教育服务)对房价的影响以第三圈层和西南方最为显著,且高于城市层面上整体的影响。公共服务对房价的影响显著受不同区域的空间功能差异的影响,公共服务和空间功能差异会加剧房价的分异格局,并推动局部房价过热。因此,显著地受到在房价调控中,不仅要有传统的金融、经济政策,还要注重空间功能和公共服务的优化。

关键词: 房价, 公共服务, 空间功能, 地理探测器, 成都

Abstract:

In China, the rise of housing prices has become one of the most pressing issues that residents encountered in recent years and received considerable attention. Regulating housing prices and preventing them from overheating have become an urgent question in some regions. This study examined the impact of public service provision on the spatiotemporal patterns of housing prices and its explanatory power in Chengdu City, Sichuan Province. A dataset of Chengdu housing prices and selected public service factors were constructed for the year 2016, and geographical detector technique was adopted in this study. The results indicate that the average housing price was 8480 yuan/m2 in Chengdu in 2016, and it showed a progressive decrease from the city center to the suburbs between the traffic circles and along the radial arteries, forming the circular and radial patterns. In general, housing prices were high in the western and southern parts while low in the eastern and north parts of the city. The impact of public service provision (mainly health care, financing, and education services) on housing prices was most pronounced in the third circular zone and southwest of the downtown area, where it was higher than the overall impact in Chengdu downtown areas. The impact of public services on housing prices was significantly affected by the difference of spatial functions in different zones. Differences in public service provision and spatial functions will further deepen the differentiation pattern of housing prices, and promote the overheating of local property prices. We argue that a better understanding of the influence of public services on housing prices will help Chinese policymakers not only to formulate traditional financial and economic policies, but also to optimize spatial functions and public services.

Key words: housing price, public service, spatial function, geographical detector technique, Chengdu City