自然资源学报 ›› 2020, Vol. 35 ›› Issue (12): 2888-2900.doi: 10.31497/zrzyxb.20201206

• 其他研究论文 • 上一篇    下一篇

中国资源型城市房价时空变化与影响因素分析

湛东升1(), 吴倩倩1, 余建辉2,3,4(), 张文忠2,3,4, 张娟锋1   

  1. 1.浙江工业大学管理学院,杭州 310023
    2.中国科学院地理科学与资源研究所,北京 100101
    3.中国科学院区域可持续发展分析与模拟重点实验室,北京 100101
    4.中国科学院大学资源与环境学院,北京 100049
  • 收稿日期:2019-09-06 修回日期:2019-11-11 出版日期:2020-12-28 发布日期:2021-02-28
  • 作者简介:湛东升(1987- ),男,安徽寿县人,博士,副教授,硕士生导师,主要从事宜居城市与区域发展研究。E-mail: zhands@126.com
  • 基金资助:
    教育部哲学社会科学研究重大课题攻关项目(18JZD033);国家自然科学基金项目(41671166);国家自然科学基金项目(42001120)

Spatiotemporal change and influencing factors of resource-based cities' housing prices in China

ZHAN Dong-sheng1(), WU Qian-qian1, YU Jian-hui2,3,4(), ZHANG Wen-zhong2,3,4, ZHANG Juan-feng1   

  1. 1. School of Management, Zhejiang University of Technology, Hangzhou 310023, China
    2. Institute of Geographic Science and Natural Resources Research, CAS, Beijing 100101, China
    3. Key Laboratory of Regional Sustainable Development Modeling, CAS, Beijing 100101, China
    4. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-09-06 Revised:2019-11-11 Online:2020-12-28 Published:2021-02-28

摘要:

基于禧泰数据库的全国城市二手房价监测数据,利用描述统计和GIS空间分析方法详细分析了2011—2018年126个中国资源型城市房价时空变化特征,并采用空间杜宾模型进一步揭示了其影响因素。研究结果表明:(1)2011年和2018年中国资源型城市平均房价分别为4105元/m2和5675元/m2,再生型城市、成熟型城市、成长型城市和衰退型城市的平均房价依次递减;(2)2011—2018年中国资源型城市平均房价呈现出波动上升的态势,房价增长率为38.2%,远低于全国城市平均房价增长幅度55.3%,且不同类型资源型城市房价的增长幅度有所差异,以成熟型和再生型城市的房价增幅相对较大;(3)中国资源型城市房价和变化存在显著的空间集聚特征,房价热点区主要集中在东部地区和中部地区城市,房价冷点区主要以东北地区和西部地区城市为主;(4)空间杜宾模型显示,人均GDP、人均住房开发投资、多样化指数、专业化指数和工业废水排放强度是影响中国资源型城市房价空间差异的主要因素。

关键词: 资源型城市, 房价, 时空变化, 影响因素, 空间杜宾模型, 中国

Abstract:

Based on national second-hand housing price monitoring data from CityRE database, spatiotemporal change characteristics of 126 resource-based cities' housing prices in China during 2011 to 2018 are analyzed in detail using descriptive statistics and GIS spatial analysis method, and its influencing factors are further revealed by Spatial Durbin Model. The results show that: (1) The average housing prices of resource-based cities in 2011 and 2018 are 4105 and 5675 yuan per square metre respectively, and average housing prices of regenerative cities, mature cities, growing cities and declining cities decrease in turn. (2) Average housing prices of resource-based cities in China fluctuated upward from 2011 to 2018 with a growth rate of 38.2%, which is lower than that of the national average housing prices. In addition, the growth rate of housing price varies across different types of resource-based cities, while mature and regenerative cities have relatively large values. (3) There are significant spatial agglomeration characteristics of housing prices and the price change in resource-based cities. Hot spots of housing prices are mainly concentrated in the eastern and central regions, while cold spots of housing prices are mainly distributed in the northeastern and western regions. (4) Spatial Durbin Model suggests that per capita GDP, per capita investment in housing development, diversity index, specialization index and industrial wastewater discharge intensity are the main factors affecting housing prices' spatial differentiation of resource-based cities in China.

Key words: resource-based cities, housing prices, spatiotemporal change, influencing factor, Spatial Durbin Model, China