地理研究 ›› 2021, Vol. 40 ›› Issue (10): 2808-2822.doi: 10.11821/dlyj020201073

• 研究论文 • 上一篇    下一篇

城市轨道交通对沿线住宅价格的时空效应——以福州地铁1号线为例

黄醇醇1(), 王晓文2, 李琳娜1()   

  1. 1.北京师范大学地理科学学部,北京 100875
    2.福建师范大学地理科学学院,福州 350007
  • 收稿日期:2020-11-04 修回日期:2021-03-12 出版日期:2021-10-10 发布日期:2021-12-10
  • 通讯作者: 李琳娜(1986-),女,湖南邵阳人,博士,讲师,研究方向为城乡可持续发展。E-mail: lilinna@bnu.edu.cn
  • 作者简介:黄醇醇(1998-),女,福建晋江人,硕士研究生,研究方向为城乡可持续发展。 E-mail: huangcc98@mail.bnu.edu.cn
  • 基金资助:
    国家自然科学基金项目(42071227);国家自然科学基金项目(41701119)

The spatio-temporal effects of urban rail transit on housing price: A case study of Fuzhou Metro Line 1

HUANG Chunchun1(), WANG Xiaowen2, LI Linna1()   

  1. 1. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    2. College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China
  • Received:2020-11-04 Revised:2021-03-12 Published:2021-10-10 Online:2021-12-10

摘要:

随着中国城市轨道交通的大力发展,城市轨道交通对沿线住宅价格的影响引起广泛关注,探索其时空效应有助于预测未来新建轨道交通的影响以及帮助政府制定合理的房价调控和城市土地利用政策。以福州地铁1号线为例,探讨城市轨道交通从建设前到建成运营的过程中,对站点周边2 km范围内住宅价格产生的时空效应。结果表明:① 城市轨道交通沿线住宅价格受到区位、邻里、建筑等多方面因素的综合作用,其中,城市轨道交通对沿线住宅价格有显著的增值效应,中高价位住宅市场受到城市轨道交通的影响最为明显。② 空间维度上,住宅价格随着与轨道交通距离的增大而呈现不同程度的递减,至轨道交通站点距离每减少1 km,住宅价格增加5.1 %。轨道交通对沿线住宅价格具有显著的分市场效应,中心城区市场的影响半径大于非中心城区市场,平均空间影响范围为1.5 km;而非中心城区市场的影响强度要远高于中心城区市场,在400 m范围内住宅价格受到轨道交通的影响最大。③ 时间维度上,城市轨道交通在建设期和运营期对沿线住宅价格均呈现出正向影响,且运营期对住宅价格的影响显著高于建设期,运营期相较于建设期平均涨幅达19.63 %;同时,轨道交通的开通给住宅价格带来的效应远大于调控政策以及宏观经济因素的影响。

关键词: 轨道交通, 住宅价格, 时空效应, 特征价格模型, 福州

Abstract:

With the vigorous construction of rail transit, subway houses have become an interesting theme all over the world. Exploring its spatio-temporal effects will help to predict the impact of new rail transit in the future and help the government to formulate reasonable housing price regulation and urban land use policy. Taking Fuzhou Metro Line 1 as an example, this paper discusses the spatio-temporal effects of urban rail transit on housing price within a 2-km distance from stations in the construction stage and operation stage, and uses hedonic price model, quantile regression and GIS spatial analysis techniques based on the ten-year long housing transaction data. In addition, macro factors are included in the time effect measurement of rail transit. The empirical results show that: (1) The housing price along the urban rail transit line is affected by various factors, such as location, neighborhood, architecture, etc. The urban rail transit imposes a statistically significant and positive effect on housing price along the line, and the medium and high price housing market is obviously affected by the urban rail transit. (2) In the spatial dimension, the housing price decreases with the increase of distance from the rail transit station. Usually, 1 km increase in the distance to the rail transit station will lead to a 5.1% increase in housing price. The impact of rail transit on housing price has significant submarket effect. The impact radius of the central urban area market is larger than that of the non-central urban area market, and the average spatial impact range is about 1.5 km. However, the impact intensity of the non-central urban area market is much higher than that of the central urban area market, and the housing price is most affected by rail transit within 400 m. (3) In terms of time dimension, the urban rail transit has a positive effect on the housing price along the line in different stages, and the housing prices in operation stage increases by 19.63% in average, significantly higher than that of the construction stage. Meanwhile, the effect of rail transit on housing price is far greater than that of regulatory policy and macroeconomic background.

Key words: rail transit, housing price, spatio-temporal effect, hedonic price model, Fuzhou