TY - JOUR
T1 - From Proximity to Quality
T2 - The Capitalization of Public Facilities into Housing Prices
AU - Tong, De
AU - Shen, Yue
AU - Wang, Xiaoguang
AU - Sun, Yiyu
AU - MacLachlan, Ian
AU - Li, Xin
PY - 2023/8/10
Y1 - 2023/8/10
N2 - Housing prices are significantly influenced by the presence of public facilities, such as schools, parks, and transport infrastructure. Whereas existing literature has mainly focused on the proximity of public facilities, this study goes beyond proximity and introduces the concept of quality metrics to evaluate public facilities. By employing the gradient-boosting decision trees approach, we analyze the nonlinear relationships between public facilities and property values in Shenzhen, China. Our study not only quantifies the extent to which the quality of these facilities is capitalized in housing prices, but also examines the interaction effects of quality and proximity on housing prices. Our results reveal that quality variables exhibit a greater relative importance than proximity variables in determining housing prices, and this relationship follows a nonlinear pattern. Furthermore, we investigate the moderating effects of quality on the relationship between proximity and housing prices. We find that the amplifying effects of higher quality are particularly evident in metro stations and public middle schools, whereas the impact of park quality on housing prices is less pronounced. These findings highlight the need to consider both quality and proximity in the supply of public facilities, as they have synergistic effects on housing prices. The nonlinear effects observed in our study can serve as a valuable tool for identifying deficiencies in the supply of public facilities. Additionally, the distinction between proximity and quality, as well as their interaction effects, contributes to our understanding of how the value of public facilities is capitalized in housing markets. © 2023 by American Association of Geographers.
AB - Housing prices are significantly influenced by the presence of public facilities, such as schools, parks, and transport infrastructure. Whereas existing literature has mainly focused on the proximity of public facilities, this study goes beyond proximity and introduces the concept of quality metrics to evaluate public facilities. By employing the gradient-boosting decision trees approach, we analyze the nonlinear relationships between public facilities and property values in Shenzhen, China. Our study not only quantifies the extent to which the quality of these facilities is capitalized in housing prices, but also examines the interaction effects of quality and proximity on housing prices. Our results reveal that quality variables exhibit a greater relative importance than proximity variables in determining housing prices, and this relationship follows a nonlinear pattern. Furthermore, we investigate the moderating effects of quality on the relationship between proximity and housing prices. We find that the amplifying effects of higher quality are particularly evident in metro stations and public middle schools, whereas the impact of park quality on housing prices is less pronounced. These findings highlight the need to consider both quality and proximity in the supply of public facilities, as they have synergistic effects on housing prices. The nonlinear effects observed in our study can serve as a valuable tool for identifying deficiencies in the supply of public facilities. Additionally, the distinction between proximity and quality, as well as their interaction effects, contributes to our understanding of how the value of public facilities is capitalized in housing markets. © 2023 by American Association of Geographers.
KW - China
KW - gradient-boosting decision trees
KW - housing prices
KW - nonlinear effects
KW - public facilities
UR - http://www.scopus.com/inward/record.url?scp=85167617546&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85167617546&origin=recordpage
U2 - 10.1080/24694452.2023.2227683
DO - 10.1080/24694452.2023.2227683
M3 - RGC 21 - Publication in refereed journal
SN - 2469-4452
JO - Annals of the American Association of Geographers
JF - Annals of the American Association of Geographers
ER -