Geographically Weighted Regression for Official Land Prices and their Temporal Variation in Tokyo

This chapter establishes Tokyo official land price data using geographically weighted regression (GWR) and multi‐scale GWR (MGWR) models. The GWR model spatially explores the varying relationships between land prices and the exploratory variables. LeSage and Pace derived estimates focusing on the results of spatiotemporal long‐term equilibrium with regard to the use of cross‐sectional data and focusing on the dynamics embodied by time‐dependent parameters with regard to the use of spatiotemporal data. The chapter explains the GWR model, which is a spatial econometric model that considers both spatial dependence and spatial heterogeneity, and its extension, the MGWR model. It presents the data used to obtain the land price function. The chapter estimates the non‐spatial model by ordinary least squares, GWR and MGWR using published land prices. It considers secular changes by visualizing the spatial prediction distribution of the parameters.