房地产
数据库事务
集聚经济
计量经济学
跟踪(教育)
交易数据
时间分辨率
商业周期
扩散
经济
可视化
3D城市模型
交易成本
计算机科学
微观经济学
数据挖掘
数据库
财务
宏观经济学
物理
热力学
量子力学
教育学
心理学
作者
Sumit Agarwal,Ying Fan,Daniel P. McMillen,Tien Foo Sing
摘要
Abstract This paper proposes the use of a semiparametric model based on a locally weighted approach that controls for dynamic agglomeration and diffusion effects in constructing localized housing price indices. Based on residential transaction records in Singapore, we create three‐dimensional interactive heat maps that allow for better measurement and visualization of spatial variations and heterogeneity in price appreciation. The heat map captures regional variations and temporal dispersions in price appreciation rates in the business cycle. Our methodology provides high‐resolution information about price dynamics that could aid individual buyers, investors, and policy makers in making objective and informed decisions.
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