PROGRESS IN GEOGRAPHY ›› 2018, Vol. 37 ›› Issue (9): 1268-1276.doi: 10.18306/dlkxjz.2018.09.009

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Spatiotemporal differentiation and influencing factors of housing selling and rental prices: A case study of Nanjing City

Weixuan SONG1,2(), Yuzhu MA1,3, Yanru CHEN1,3   

  1. 1. Nanjing Institute of Geography and Limnology, CAS, Nanjing 210008, China
    2. Key Laboratory of Watershed Geographic Sciences, CAS, Nanjing 210008, China
    3. University of Chinese Academy of Sciences, Beijing 101407, China
  • Received:2017-11-15 Revised:2018-01-12 Online:2018-09-28 Published:2018-09-28
  • Supported by:
    National Natural Science Foundation of China, No.41771184


Under the background of rapid urbanization and housing market reform, urban housing and housing price have become a major issue related to the national economy and people's livelihood in China. The spatial differentiation of housing prices has become an important topic of research, which has been concerned by Chinese urban geographer and economic geographer in recent years. Few of the existing studies in China relied on long time series data to compare the spatial pattern, location influencing factors, and mechanism of change of urban housing selling and rental prices. As Nanjing City can represent the general development path of China's big cities, this study took 4560 residential communities in Nanjing as the total sample, and collected the average housing selling and rental prices for 30 quarters of 2009-2017. Data analyses show that there is a causality between the selling and rental prices, and the selling price shows a clear pattern that "fast rise" alternates with "relatively smooth," price levels whereas the rental price shows a more stable trend. The study chose areas where the sample communities are concentrated as focused research area and 6 characteristic time intervals to analyze the spatiotemporal differentiation and characteristics of change of housing selling and rental prices by employing the Kriging interpolation method. The results show that the spatial differentiation of housing selling price significantly intensified and high-value areas are more concentrated in Hexi New Town, Jiangxinzhou, and elite school districts in Gulou District; and based on the current situation of development, the high-value areas continue to transfer to the periphery of the city. Meanwhile, the spatial pattern of rental price shifted from gradually decreasing from city center toward outskirts to a more balanced structure of multi-centers both in the old and the new city areas. On this basis, an indicator system of location influence coefficient on housing selling and rental prices was built, focusing on the characteristics of houses and the "location" property. Through multiple stepwise regression analysis, it was found that central geographical variable has the highest degree of explanation power on selling and rental prices, while the explanatory power of supporting services on selling and rental prices is decreasing. With rapidly rising housing selling price in Nanjing, the significance of normal "location" coefficient on housing price differentiation is continually abating, but the decisive effect of some special "location" coefficients (such as school district and policy preferences) on selling price is becoming more prominent, further expanding the price-to-rent ratio, which also indicates the overall increase of housing price "risk" in Nanjing.

Key words: housing, location, selling price, rental price, spatiotemporal differentiation, influencing factors, price-to-rent ratio, Nanjing