JOURNAL OF NATURAL RESOURCES ›› 2020, Vol. 35 ›› Issue (12): 2888-2900.doi: 10.31497/zrzyxb.20201206

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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
  • Contact: Jian-hui YU E-mail:zhands@126.com;yujh@igsnrr.ac.cn

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