地理科学 ›› 2013, Vol. 33 ›› Issue (10): 1157-1165.doi: 10.13249/j.cnki.sgs.2013.010.1157

• •    下一篇

中国城市住宅价格的空间分异格局及影响因素

王洋1(), 王德利2(), 王少剑3,4   

  1. 1.广州地理研究所,广东 广州510070
    2.北京市社会科学院,北京100101
    3.中国科学院地理科学与资源研究所,北京100101
    4.中国科学院大学,北京100049
  • 收稿日期:2012-12-19 修回日期:2013-06-20 出版日期:2013-10-20 发布日期:2013-10-20
  • 作者简介:

    作者简介:王 洋(1984-),男,黑龙江黑河人,博士,助理研究员,研究方向为经济地理、城市与区域规划。E-mail: wyxkwy@163.com

  • 基金资助:
    国家自然科学基金项目(41201154)资助

Spatial Differentiation Patterns and Impact Factors of Housing Prices of China′s Cities

Yang WANG1(), De-li WANG2(), Shao-jian WANG3,4   

  1. 1. Guangzhou Institute of Geography, Guangzhou, Guangdong 510070, China
    2. Beijing Academy of Social Sciences, Beijing 100101, China
    3.Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    4. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2012-12-19 Revised:2013-06-20 Online:2013-10-20 Published:2013-10-20

摘要:

分别研究2009年中国286个地级以上城市住宅均价和房价收入比的空间分异格局、总体趋势、空间异质性和相关性;根据供需理论和城市特征价格理论建立了影响中国城市住宅价格空间分异的初选因素,并根据半对数模型分析主要影响因素。结果表明:① 中国城市住宅价格空间分异显著,呈现出空间集聚性分异(东南沿海三大城市群与内陆城市之间)和行政等级性分异(省会与地级市之间)的双重格局;② 房价收入比较高的城市数量更多,分布范围更广,购房难度较大的城市已超过一半;③ 住宅均价的总体分异趋势和空间异质性都强于房价收入比;④ 城市居民收入与财富水平和城市区位与行政等级特征是住宅价格空间分异的两大核心影响因素。

关键词: 住宅价格, 房价收入比, 空间分异, 影响因素, 半变异函数, 半对数模型, 中国

Abstract:

In China′s high housing price times, housing price has become the core issue which was paid close attention by government and inhabitant. However, relatively little analysis is available on spatial differentiation patterns of housing prices in China′s cities according to taking more cities as analysis units in geographic field. And there is not unanimous conclusion in the main impact factors on spatial differentiation of housing price. In light of this, taking the housing prices and housing price-to-income ratio of 286 cities in China as basic data, we studied spatial differentiation patterns, global trends, spatial heterogeneities and correlations of housing prices and housing price-to-income ratio respectively. Furthermore, based on the law of supply-demand and urban hedonic price theory, we selected hypothetical 10 impact factors including 30 indicators on spatial differentiation for housing prices in China′s cities. Finally, the main impact factors were selected and analyzed according to regression analysis based on semilogarithmic model. The results show that: 1) There exist obviously spatial differentiation patterns for housing prices in China′s cities, and these differentiation patterns have features of the spatial agglomeration (between inland areas and three urban agglomerations of southeast coastal areas) and urban administrative level (between provincial capital and prefecture-level cities) simultaneously. 2) There are more number and larger scope with higher housing price-to-income ratio than that of housing prices. The number of cities of high housing affordability has been more than a half; 3) Both global differentiation trend and spatial heterogeneity of housing prices are stronger than that of housing price-to-income ratio; 4) Both the law of supply-demand and urban hedonic price theory can explain the phenomenon of spatial differentiation for housing prices in China′s cities. 5) The main impact factors on spatial differentiation of housing prices in China′s cities based on law of supply-demand are as follows: urban resident income and wealth level, urban housing price expectation and demand potential, urban residential construction cost. The main impact factors based on urban hedonic price theory are urban location and administrative level, urban natural environment, urban economic and producer environment, and urban infrastructure. Therein, urban resident income and wealth level and urban location and administrative level are two core impact factors on spatial differentiation for housing prices in China′s cities.

Key words: housing prices, housing price-to-income ratio, spatial differentiation, impact factors, semivariogram, semilogarithmic model, China

中图分类号: 

  • F293.3