基于多尺度地理加权回归的深圳市房价影响因素研究

Analysis of Influencing Factors of Housing Prices in Shenzhen Based on Multi-Scale Geographically Weighted Regression

住房价格的空间分异能有效反映居民对特定住房影响因素的需求,同时也体现城市空间资源的分布差异。本文基于多尺度地理加权回归模型(MGWR),从房价影响因素的影响力度、作用尺度和空间分异三个角度对深圳市房价的影响因素进行分析;并归纳其他MGWR模型方法的房价研究,总结房价影响因素的特点。结果表明:1.房价在空间上的不均衡现象,很大程度上受到公共资源配置不均衡的影响,如优质学区和特定的区位因素等。2.深圳房价影响因素的分析结果和以往研究存在一些共性和特殊性。各类型变量对各城市房价的影响方向和作用尺度基本是一致的。但在本研究中,公交站点等生活圈设施,具有空间异质性或仅在局部区域表现出显著效应,反映了更深层次设施布局需求的问题。针对分析结果,文章对未来生活圈的配套设施提出相应的规划策略。

The spatial differentiation of housing prices effectively reflects the demand of residents for specific housing influences,as well as differences in the distribution of urban spatial resources.Based on a multi-scale geographically weighted regression model(MGWR),this study analyses the influencing factors of house prices in Shenzhen from three perspectives:the strength of influence,the scale of action and spatial differentiation of house price influencing factors;and summarises the house price studies of other MGWR models and the characteristics of house price influencing factors.The results show that(1)the spatial imbalance in house prices is largely influenced by the uneven allocation of public resources,such as high-quality school and specific locational factors.(2)There are some commonalities and specificities between the results of the analysis of the factors influencing house prices in Shenzhen and previous studies.The direction and scale of influence of the various types of variables on housing prices are basically consistent across cities.However,in this study,life-circle facilities such as bus stops,which are spatially heterogeneous or show significant effects only in local areas,reflect the issue of deeper facility layout needs.Based on the results of the analysis,the article proposes corresponding planning strategies for the supporting facilities of the future life-circle.