Journal
TRANSPORT POLICY
Volume 117, Issue -, Pages 48-59Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.tranpol.2022.01.004
Keywords
Nonlinearity; Public transit accessibility; Residential property value; Inequity; Machine learning; Shanghai (China)
Categories
Funding
- Research Foundation - Flanders (FWO) [1257022N]
- China Scholarship Council [202008320289]
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This study investigates the complicated relationships between public transit accessibility and housing prices in Shanghai using gradient boosting regression trees. It finds that the impact of public transit accessibility on housing prices varies across different price segments, with high-priced houses benefiting more from proximity to the central business district and the systemwide metro accessibility.
Although numerous studies have been conducted to analyze the relationship between public transit accessibility and housing prices, they often assumed a linear relationship. Using a dataset of 196,232 s-hand residential properties in Shanghai (China), this study applies the gradient boosting regression trees (GBRT) method to investigate the complicated relationships between public transit accessibility and housing prices across price segments. The results show that for low- and median-priced houses, the travel time by public transit to the central business district (CBD) contributes the most to housing prices while for high-priced houses, the systemwide metro accessibility contributes the most. Public transit accessibility has significant nonlinear and threshold effects on housing prices. Public transit accessibility has an overall positive effect on housing prices, though some negative effects occur within certain intervals. Different patterns are observed across price segments. High-priced houses receive a much larger premium from the closeness to CBD and systemwide metro accessibility but are more negatively affected by both local and systemwide bus accessibility, compared to low-and median-priced houses. The differences in transit's value-added effects across price segments may bring about inequity in accessibility across different income groups. Relevant policies on how to reduce such an inequity issue are finally discussed.
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