Urban Studies Lunchtime Workshop: Spatiotemporal Analysis of House Prices in Fife, Scotland, 2003-2012
- Monday, 2nd March
- 1:00pm - 2:00pm
- Urban Studies Boardroom, 29 Bute Gardens, University of Glasgow, Glasgow, G12 8RS GET DIRECTIONS
Lecturer in Urban Big Data and Quantitative Methods, Urban Big Data Centre, University of Glasgow
The real estate market has long provided an active application area for spatial-temporal modelling and analysis. It is well known that house prices tend to be not only spatially but also temporally correlated. In the spatial dimension, nearby properties tend to have similar values because they share similar characteristics; meanwhile house prices also tend to vary over space due to differences in these characteristics. In the temporal dimension, current house prices tend to be affected by property values from previous years. To date, however, most research on house prices has adopted either a spatial perspective or a temporal one; relatively little effort has been devoted to situations where both spatial and temporal effects coexist. Using 10-years of house price data in Fife, Scotland (2003-2012), this research applies a mixed model approach, semi-parametric geographically weighted regression (GWR), to explore, model and analyse the spatiotemporal variations in the relationships between house prices and associated determinants. The study demonstrates the mixed modelling technique provides better results than standard approaches in terms of house price prediction by accounting for spatiotemporal relationships at both global and local scales.