Center for Spatial Studies

The urban real estate market is shaped by spatially varying environmental and social determinants, such as the valuation of green spaces, proximity to transport, and distance to central business districts. Among all the spatially varying relationships between prices and housing characteristics, some tend to vary at a global spatial scale, whereas others vary at a local spatial scale. This study applies a random model to specify multi-scale spatial heterogeneity in the rental housing market by utilizing residential rent data in the Tokyo metropolitan area from 2017. The results show that spatially varying determinants impact rental housing prices at the global, moderate, and local scales. Further, we find that the estimation is flexible because the random model determines the spatial scale of each regression coefficient.