Journal of Geographical Sciences

, Volume 28, Issue 6, pp 725–740 | Cite as

Effect of land prices on the spatial differentiation of housing prices: Evidence from cross-county analyses in China

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Abstract

This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014. Multiple theoretical perspectives on housing demand, supply, and market, are combined to establish a housing price model to explore the impact of land prices on housing prices. The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geographical detector technique. Finally, the influencing mechanism of land prices on housing prices is discussed. The main conclusions are as follows. (1) Housing prices have a pyramid- ranked distribution in China, where higher housing prices are linked to smaller urban populations. (2) Land prices are the primary driver of housing prices, and their impacts on housing prices vary over different administrative levels. To be specific, the effect of land prices is the strongest in the urban districts of provincial capital cities. (3) The internal influence mechanisms for land prices driving housing prices are: topographic factors, urban construction level, the agglomeration degree of high-quality public service resources, and the tertiary industrial development level. The urban land supply plan (supply policies) is the intrinsic driver that determines land prices in cities; through supply and demand, cost, and market mechanisms, land prices then impact housing prices.

Keywords

housing prices land prices influencing factors spatial differentiation county unit China 

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Copyright information

© Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and PlanningSun Yat-sen UniversityGuangzhouChina
  2. 2.Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangzhouChina

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