地理科学 ›› 2017, Vol. 37 ›› Issue (4): 573-584.doi: 10.13249/j.cnki.sgs.2017.04.011

• 论文 • 上一篇    下一篇

中国住宅出让地价发育特征及其影响因素分析

韩娟1(), 金晓斌1,2(), 张志宏1,3, 孙伟1, 徐心茹1, 周寅康1,2   

  1. 1.南京大学地理与海洋科学学院,江苏 南京 210023
    2.南京大学自然资源研究中心,江苏 南京 210023
    3.中国土地勘测规划院,北京 100029
  • 收稿日期:2016-04-24 修回日期:2016-06-07 出版日期:2017-04-25 发布日期:2017-04-25
  • 作者简介:

    作者简介:韩娟(1991-),女,安徽合肥人,博士研究生,主要从事土地利用规划与管理研究。E-mail:15261873019@163.com

  • 基金资助:
    教育部博士点基金项目 (20120091110014)资助

Development Characteristics and Factors Analysis of Residential Land Price in China

Juan Han1(), Xiaobin Jin1,2(), Zhihong Zhang1,3, Wei Sun1, Xinru Xu1, Yinkang Zhou1,2   

  1. 1.College of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, Jiangsu, China
    2. Research Center of Nature Resources, Nanjing University, Nanjing 210023, Jiangsu, China
    3. China Land Surveying and Planning Institute, Beijing 100029, China
  • Received:2016-04-24 Revised:2016-06-07 Online:2017-04-25 Published:2017-04-25
  • Supported by:
    Ph.D. Programs Foundation of Ministry of Education of China(20120091110014)

摘要:

基于中国土地市场网2009~2013年招、拍、挂出让的住宅用地数据,以县级行政区域作为研究单元,建立区域住宅地价综合模型,选取地价水平、地价增长率和交易宗数作为评价指标,采用Ward系统聚类法,综合分析了中国住宅出让地价的发育特征,利用多分类Logistic回归模型探索了各类地价发育形态的潜在影响因素。结果表明:研究期内中国住宅出让地价总体呈现东高西低、沿海高于内陆、城市群带动周边区域发展、城市群内部围绕中心城市增长等空间格局特征;中西部地价高增长的单元多于东部,西北、东北中南部、四川盆地、河西走廊以及长江中下游地区是地价高增长的聚集区;住宅市场活跃度呈阶梯状变化,活跃度较高的地区主要分布在山东半岛、长三角、长江中游、辽宁中部、哈尔滨、成渝、滇中、呼包鄂等城市群。根据综合特征,中国住宅出让地价空间发育可分为成熟稳健型、发展完善型、成长发展型、萌芽起步型和成长受阻型5类,相邻发育形态在空间关系上表现出互为邻里的特征。各类发育区的主要影响因素差异显著。区位条件、居民收入和财政收入是地价发育成熟度的主要影响因素;人均GDP、国土开发度提升将促进地价形态发育程度;而人口吸引力不足、基础设施建设相对滞后等将导致地价形态发育受阻。

关键词: 住宅出让地价, 发育形态, Ward聚类, Logistic回归, 县域

Abstract:

In order to identify the spatial characteristics of residential land price in China, this article establishes such a method so as to calculate residential land prices in China at the county level by integrating land transaction data from 2009 to 2013, and chooses three indicators to evaluate the development of the residential land market. Then, Ward’s hierarchical clustering is used to classify the regions into different types of development status in the residential land market and logistic regression model is used to explore potential factors and their impacts on each development type. Several results were acquired: 1) Residential land prices in China decrease along gradients from east to west and from the coast to inland. Urban agglomeration promotes surrounding regions, and a central city promotes surrounding cities. The main areas with high price growth rate are concentrated in the west-north zones, middle-south in the north-east zones, Sichuan Basin, Hexi Corridor, and the middle and lower reaches of the Yangtze River. The activity level of residential market transactions appears stepped change. The counties with high-active market transactions are mainly concentrated in Shandong peninsula, the Yangtze River Delta, the middle of the Yangtze River, Central Liaoning, Harbin, Chengdu and Chongqing, Yunnan, and Hohhot-Baotou-Rrdos urban agglomeration, and so on. 2) The development of the land market can be classified as ‘mature,’ ‘improving,’ ‘growing,’ ‘germinating’ or ‘blocked’. The neighboring types also appear neighborhood relation in spatial. 3) The main factors of each type differ significantly. The location condition, resident income and revenue are the main factors affecting the development maturity of price. The increase of gross domestic product (GDP) per capita, and the level of development of the land promotes the development of land price, while a lack of population, and a lack of infrastructure results in the development of land price being blocked.

Key words: residential land price, developmental status, Ward hierarchical clustering, logistic regression, county level

中图分类号: 

  • F301