中国35个大中城市房价空间关联及其解释

Spatial Correlation and Explanation of Housing Prices in 35 Large and Medium-sized Chinese Cities

文章基于2010—2017年中国35个大中城市商品住宅价格数据,运用社会网络分析方法对城市房价空间关联的网络结构特征及其影响因素进行了经验考察。结果显示:从整体网络结构来看,35个大中城市房价空间关联存在逐渐上升的趋势,网络结构越来越稳定,而且越来越多的城市位于网络的边缘位置。从个体网络结构特征来看,深圳、北京、上海、天津、广州、青岛、沈阳这7个城市的度数中心度高于平均值,位于网络的中心位置。深圳、上海、广州等城市在房价网络中能够快速地与其他城市产生联系。城市间经济发展水平的差异、产业结构差异和人口数量差异均是房价空间关联的原因,差异越大,对城市间房价发生关联的影响越大。

Based on the commodity housing price data of 35 large and medium-sized cities in China from 2010 to 2017,this paper makes an empirical study on the network structure characteristics of spatial correlation of urban housing prices and its influencing factors by using social network analysis method.The conclusions are shown as follows:From the perspective of the overall network structure,the spatial correlation of housing prices in 35 large and medium-sized cities has a gradual upward trend,with the network structure more and more stable,and more and more cities located at the edge of the network.From the perspective of individual network structure characteristics,the degree centrality of Shenzhen,Beijing,Shanghai,Tianjin,Guangzhou,Qingdao,Shenyang and other seven cities is higher than the average,located in the center of the network.Shenzhen,Shanghai,Guangzhou and other cities can quickly connect with other cities in the housing price network.The inter-city differences in the level of economic development,industrial structure and population are all the reasons for the spatial correlation of housing prices.The greater the difference,the greater the impact on the correlation of inter-city housing prices.