Local House Price Modeling

Real estate market analysis has long been an active area of inquiry and one that reveals much about people’s preferences regarding housing attributes. It is well-known that house prices tend to exhibit strong spatial dependency and that they vary across space due to differences in structural and neighborhood characteristics. It is perhaps less well-known but gaining recognition that the influence of various structural and neighborhood characteristics on house prices might vary over space. However, very few, if any, applications in real estate research have recognized and measured the spatial scales over which different factors affect house prices or been able to quantify the ‘intangible’ impacts certain locations have on house prices. Using house price data in King County, WA, this research applies a multiscale extension to GWR, multiscale geographically weighted regression (MGWR), to measure and investigate spatial variations in the processes affecting house prices at varying scales. In a novel attempt, this research quantifies the intrinsic value certain locations have beyond the determinants used to define traditional hedonic price models. The research also demonstrates the utility of MGWR to hedonic price analysis and its ability to identify intricate housing submarkets often overlooked by other techniques.

Please use the link here if the pdf embed does not load: Project presentation