城市空气质量对住宅价格的影响研究——基于广州市二手房的大数据分析  

The Impact of Air Quality on Housing Prices: An Analysis of Second-hand Housing Big Data in Guangzhou

作　　者：武婷 沈静[2] Wu Ting;Shen Jing

机构地区：[1]北京大学城市与环境学院 [2]中山大学地理科学与规划学院

出　　处：《规划师》2019年第10期47-52,共6页Planners

基　　金：国家自然科学基金项目(41871111、 41371138)

摘　　要：空气质量作为城市中最普遍的公共资源,研究其对住宅价格的影响不但有助于认识购房者的住房偏好,而且可以为城市规划管理、城市空间布局提供新思路。文章以广州市中心城区二手房市场为例,通过爬取链家网住宅样本数据,运用Hedonic特征价格模型的方法,围绕建筑结构、交通区位、邻里环境和空气质量四方面,选择17个特征变量,建立特征价格解释模型,结果显示:①PM10浓度对住宅价格有负面影响,PM10浓度每下降1微克/立方米,住宅价格上升0.92%;②PM2.5浓度与住宅价格呈现正相关关系。分析空气质量影响住宅价格的可能原因,发现其与城市空间布局息息相关,因此最后从优化城市空间布局角度提出空气质量改善建议。Air is the most common public resource in the city, and the effect of air quality on housing prices will re flect purchasers' preference and inspire management of urban planning. Based on the study of second-hand housing market in the downtown area of Guangzhou, this article uses the Hedonic price model to quantify the relationship between air quality and housing prices. With residential data from www.lianjia.com, 17 housing attributes from four categories (structure, location, neighborhood environment and air quality) are quantified. The results illustrate that PM10 concentration has a negative impact on housing prices. The price rises by 0.92% upon one unit decrease in PM10, while PM2.5 concentration is positively correlated with housing prices. The mechanism of this results is closely related to urban space layout. Therefore, the paper proposes air quality improvement suggestions from the perspective of optimizing urban space layout.

关 键 词：Hedonic特征价格模型 住宅价格 空气质量 城市空间布局 

分 类 号：TU984[建筑科学—城市规划与设计]