地理学报 ›› 2016, Vol. 71 ›› Issue (8): 1329-1342.doi: 10.11821/dlxb201608004

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中国县域住宅价格的空间差异特征与影响机制

王少剑1(), 王洋2,3(), 蔺雪芹4, 张虹鸥2,3   

  1. 1. 中山大学地理科学与规划学院 广东省城市化与地理环境空间模拟重点实验室,广州 510275
    2. 广州地理研究所,广州 510070
    3. 广东省地理空间信息技术与应用公共实验室,广州 510070
    4. 首都师范大学资源与环境学院,北京 100048
  • 收稿日期:2015-12-09 修回日期:2016-03-06 出版日期:2016-08-25 发布日期:2016-08-30
  • 作者简介:

    作者简介:王少剑(1986-), 男, 河南驻马店人, 博士, 讲师/硕士生导师, 主要研究方向为城市地理、城市与区域规划。E-mail: 1987wangshaojian@163.com

  • 基金资助:
    国家自然科学基金项目(41401164);中央高校基本科研业务费专项资金资助项目(37000-31610426)

Spatial differentiation patterns and influencing mechanism of housing prices in China: Based on data of 2872 counties

Shaojian WANG1(), Yang WANG2,3(), Xueqin LIN4, Hong'ou ZHANG2,3   

  1. 1. Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
    2. Guangzhou Institute of Geography, Guangzhou 510070, China
    3. Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou 510070, China
    4. College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
  • Received:2015-12-09 Revised:2016-03-06 Online:2016-08-25 Published:2016-08-30
  • Supported by:
    National Natural Science Foundation of China, No.41401164;The Fundamental Research Funds for the Central Universities, No.37000-31610426

摘要:

以2014年中国2872个县级单元的住宅平均单价为基本数据,通过空间自相关和核密度函数分析中国住宅价格的差异格局、空间关联特征和分布形态,构建“住宅价格等级金字塔”;根据“需求+供给+市场”的三维理论视角建立包括5大住宅价格差异影响因素在内的价格模型,采用地理探测器分析全国及其区域子市场的影响因素强度差异,并探索其影响机制。结果表明:① 中国区域住宅价格呈现以行政等级性为主、空间集聚性为辅的双重差异格局,其空间关联与集聚性显著;② 中国住宅价格呈现出房价越高,区域越少,所居住城镇人口越少的“金字塔式”等级分布特征。③ 租房户比例、流动人口规模、住房支付能力、住房市场活跃度、土地成本是中国住宅价格差异的5个核心影响因素,不同行政等级子市场的影响因素作用强度各异。

关键词: 住宅价格, 影响因素, 影响机制, 空间差异, 县级单元, 中国

Abstract:

In contemporary China, housing price has become the vital issue, which attracted considerable attention from the governments and inhabitants. However, there are relatively few studies on spatial differentiation of housing prices in China at the county level. In addition, there is no unanimous conclusion on the main factors influencing spatial differentiation of housing price. To meet this deficiency, using spatial autocorrelation and kernel density function, this study examines the spatial differentiation pattern, spatial correlation characteristics and the distribution shape of housing prices in China, and constructs the 'Pyramid of Housing Price Grade' based on the average housing prices of China's counties in 2014. Furthermore, a housing price model is established according to the demand-supply-market theory in order to explore the impact factors, and intensity differences of the influencing factors are also analyzed. The main conclusions are as follows: (1) There exists significant spatial correlation and agglomeration of housing prices in China's counties, and the differentiation patterns are featured by the administrative grade and the spatial agglomeration simultaneously; (2) The housing prices present pyramid-ranked distribution in China. This finding indicates that the higher the housing price, the less the urban population. (3) The proportion of rental households, scale of the floating population, housing affordability, housing market activity and the cost of land are five core influencing factors of housing prices in China's counties. The intensities of these influencing factors vary across administrative grade sub-markets.

Key words: housing prices, influencing factors, influencing mechanism, spatial differentiation, county unit, China