The effects of locational factors on the housing prices of residential communities: The case of Ningbo, China

被引:68
|
作者
Liang, Xiaojin [1 ]
Liu, Yaolin [1 ,2 ,3 ]
Qiu, Tianqi [1 ]
Jing, Ying [1 ]
Fang, Feiguo [1 ]
机构
[1] Wuhan Univ, Sch Resources & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
[2] Wuhan Univ, Minist Educ, Key Lab Geog Informat Syst, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
[3] Wuhan Univ, Collaborat Innovat Ctr Geospatial Informat Techno, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
关键词
Residential communities; Housing prices; Locational factors; Geographic field model; Geographically weighted regression; Spatially non-stationary; GEOGRAPHICALLY WEIGHTED REGRESSION; ORDINARY LEAST-SQUARES; PROPERTY-VALUES; AMENITY VALUE; OPEN SPACES; LAND-USE; MODEL; HANGZHOU; IMPACT; LANDSCAPE;
D O I
10.1016/j.habitatint.2018.09.004
中图分类号
F0 [经济学]; F1 [世界各国经济概况、经济史、经济地理]; C [社会科学总论];
学科分类号
0201 ; 020105 ; 03 ; 0303 ;
摘要
Residential communities are the basic living units in Chinese cities. Housing prices are closely associated with the community location and surrounding support facilities. When selecting satisfactory residential accommodation, potential real estate purchasers prioritize the community location in a city at the macro-level and then consider other micro-factors (i.e., the floor, orientation, structure, etc.). This paper attempts to explore the relationship between housing prices and locational factors at the community level. We collect the current market prices of 545 residential communities built in the last decade in Ningbo, the second largest city in Zhejiang Province. Then, thirteen locational factors of five dimensions are identified to research their influences on housing prices. In the process of selecting certain locational variables, both extant features and additional features (i.e., planned ones) are considered. The geographic field model is introduced to quantify the external effects of locational factors, due to its advantages of producing more accurate results than that of traditional distance-based measure methods. Then, regression analysis is performed based on the average housing prices of residential communities and explanatory variables by the ordinary least squares model and the geographically weighted regression. The regression coefficients demonstrate that the externalities of parks, lakes, department stores, banks, secondary schools and rail transit have significant but spatially non-stationary effects on housing prices. The results provide references for local real estate planning departments and potential real estate purchasers.
引用
收藏
页码:1 / 11
页数:11
相关论文
共 50 条
  • [1] Rural Migrants' Residential Mobility: Housing and Locational Outcomes of Forced Moves in China
    Huang, Xu
    Dijst, Martin
    van Weesep, Jan
    [J]. HOUSING THEORY & SOCIETY, 2018, 35 (01): : 113 - 136
  • [2] Impacts of urban environmental elements on residential housing prices in Guangzhou (China)
    Jim, C. Y.
    Chen, Wendy Y.
    [J]. LANDSCAPE AND URBAN PLANNING, 2006, 78 (04) : 422 - 434
  • [3] The Impacts of Locational and Neighborhood Environmental Factors on the Spatial Clustering Pattern of Small Urban Houses: A Case of Urban Residential Housing in Seoul
    Shin, Myung-Cheul
    Shin, Gwang-Mun
    Lee, Jae-Su
    [J]. SUSTAINABILITY, 2019, 11 (07)
  • [4] Relationship between Indoor Living Environment and Housing Prices: A Case Study of the Taojinjiayuan Residential Quarter in Guangzhou, China
    Wang, Yang
    Wang, Min
    Wu, Yingmei
    Yue, Xiaoli
    Li, Xueying
    Zhang, Hong'ou
    [J]. INDOOR AIR, 2023, 2023
  • [5] EVALUATING THE EFFECTS OF LANDSCAPE ON HOUSING PRICES IN URBAN CHINA
    Du, Qingyun
    Wu, Chao
    Ye, Xinyue
    Ren, Fu
    Lin, Yongjun
    [J]. TIJDSCHRIFT VOOR ECONOMISCHE EN SOCIALE GEOGRAFIE, 2018, 109 (04) : 525 - 541
  • [6] Effects of Urban Expressways on Housing Prices: A Case Study of Qiushi Highway, Hangzhou, China
    Zhang, Ling
    Shen, Rui
    Li, Tianqi
    Zhou, Qingfeng
    [J]. TRANSPORTATION RESEARCH RECORD, 2022, 2676 (08) : 697 - 713
  • [7] Using a system model to decompose the effects of influential factors on locational marginal prices
    Wang, Lizhi
    Mazurridar, Mainak
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (04) : 1456 - 1465
  • [8] Effects of socioeconomic factors on regional housing prices in the USA
    Lin, Wei-Shong
    Tou, Jen-Chun
    Lin, Shu-Yi
    Yeh, Ming-Yih
    [J]. INTERNATIONAL JOURNAL OF HOUSING MARKETS AND ANALYSIS, 2014, 7 (01) : 30 - 41
  • [9] Impact of Urban Green Space on Residential Housing Prices: Case Study in Shenzhen
    Wu, Jiansheng
    Wang, Meijuan
    Li, Weifeng
    Peng, Jian
    Huang, Li
    [J]. JOURNAL OF URBAN PLANNING AND DEVELOPMENT, 2015, 141 (04)
  • [10] Are there Irrational Bubbles under the High Residential Housing Prices in China's Major Cities?
    Arestis, Philip
    Zhang, Sixia
    [J]. PANOECONOMICUS, 2020, 67 (01) : 1 - 26