城市轨道交通新建线路对沿线住宅价格增值的时空效应

定量分析城市轨道交通对沿线土地价值的影响，是通过土地价值捕获将外部效益内部化，解决中国新型城镇化过程中城市轨道交通财务可持续的关键问题。本文在开源数据环境下，获 取2011—2016年北京市二手房交易数据，采用特征价格模型(HPM)分析北京城市轨道交通新建线路对沿线住宅价格增值的时空效应。研究表明：与全局常参数的多元线性回归模型(MLR)、空间滞后模型(SLM)、空间误差模型(SEM)和空间杜宾模型(SDM)相比，局部变参数的地理加权回归模型(GWR)拟合效果更优，可以更好地消除残差的空间效应，刻画轨道交通与土地价值关系的空间异质性。城市轨道交通带来的可达性提升对沿线80%以上住宅小区的房价具有显著的正效应，住宅价格增值比率随地铁站距离递远递减，且具有显著的空间异质性。轨道交通对住宅价格的影响在空间上具有网络化效应，新建线路不仅会改变周边房价，对城轨网络其他位置的住宅也具有影响。城市轨道交通对住宅价格的影响范围为1 km，在该范围内，住宅价格受到的增值效应在 2011—2016 年基本稳定，约为 3%；受新线直接影响区域的住宅价格会产生相对更大的提升(0.02%~0.22%)。

Spatial and Temporal Effects of New Urban Rail Transit Lines on Residential Property Value Uplift

A quantitative analysis of the impact of urban rail transit on land value along the rail transit line is critical tointernalize the external benefits and promote the financial sustainability of urban rail transit in China's newurbanization process. Using the open data resources, this study collected 361053 second-hand real estate transactionsamples in Beijing from 2011 to 2016 and investigated the spatial and temporal effects of Beijing urban rail transit onthe residential property prices along the rail transit lines through the Hedonic Price Model. The analysis results suggestthat the proximity to rail transit station has a significant impact on property prices based on both Global model andLocal model. Compared with Multi-variable Linear Regression(MLR), Spatial Lag Model(SLM), Spatial Error Model(SEM) and Spatial Durbin Model(SDM) which are based on global constant parameters regression, GeographicallyWeighted Regression(GWR) based on local variable parameters regression shows a better fitting effect and canpreferably eliminate the spatial effect of residuals and depict the spatial heterogeneity of the relationship between urbanrail transit and land value. The residential property prices of more than 80% residential units along the line wouldbenefit from the provision of urban rail transit system. The uplift of the property price shows an obvious spatialheterogeneity and less increases of the prices are observed for the properties located further from the rail transitstations. The impact of rail transit on property prices also has a network effect. The new line will not only change theresidential property prices in surrounding areas, but also the properties in other locations in the urban rail transitnetwork. The spatial range of the impact of urban rail transit on residential property value is about 1 km from railtransit stations. Within this range, the land value uplift caused by the new rail transit line is relatively consistent from2011 to 2016, which is about 3% . The land value uplifts in the area directly affected by the new line are 0.02% to0.22% higher than the wider area.