Spatially-Adjusted Real Estate Price Indices

Housing price discovery reduces housing price distortions in the market. Spatial dimension has been neglected in many housing price models; and modeling spatial heterogeneity into housing price models help better understand local market variations in prices. Exploring different pricing index methodologies is one research agenda of IREUS.

IREUS research team comprising Sing Tien Foo and Fan Ying together with Professor McMillen, Daniel P. from University of Illinois at Chicago is developing a new spatial heat map of real estate prices for the non-landed private residential market in Singapore (see Figure 1) using locally weighted regression (LWR) method. With the LWR model, 22 sub-indices by the planning region are also estimated to capture spatial heterogeneity in private housing prices (Figure 2). The team is also working on the digitized and interactive version of the spatial real estate price heatmap.

Figure 1

Figure 2: Housing Price Indices by the Planning Region (1995Q1 = 1000)