Neighborhood externalities modify the nexus between residential land and housing prices: A joint analysis using regression tree models

Neighborhood externalities influence residential land prices and housing prices simultaneously, contributing to a nexus relationship between them. Most existing studies have focused on the causal relationship between the two, with limited attention to their nexus. This research matched land parcel transactions from 2003 to 2015 and housing transaction records with purchasers' housing purchase records before 2019 to construct a spatialtemporal land-housing dataset in Shanghai. Both spatial statistical tools and regression tree models were employed to explore the underlying mechanism, focusing on proximity to industries. According to the modeling results, residential land prices and housing prices are highly sensitive to polluting industries and producer service industries. The impacts of polluting industries on residential land prices have intensified, but the impacts on housing prices have not. The regression tree models further showed that living service industries were the primary positive contributor to residential land and housing prices. Regarding the social environment, non-local people are taking over communities with high-priced housing on high-value residential land parcels. These research outcomes encourage more efforts to explore the determinants of the nexus between residential land prices and housing prices, rather than discussion of the causality relationship.