Land price polarization and dispersion in Tokyo: a spatial model approach

Abstract

Intensifying spatial inequality in housing markets is of great concern for urban planners and policymakers. This study employed a year-on-year analysis using universal kriging to fit the official land price data in Tokyo over the period 1997–2021. By comparing estimated regression coefficients with the estimated spatial variogram parameters, we found evidence of rising spatial polarization and dispersion in land prices of Tokyo. This was confirmed via price differences between western and central Tokyo that are becoming larger with each passing year. The determinants of the land price have different impacts on prices in western and central Tokyo. As for the variogram parameter, the nugget effects of the residuals in spatial models are increasing for the non-central region and decreasing in central Tokyo, which indicates that the degree of spatial dispersion is increasing.

Spatial and Temporal Evolutionary Characteristics and Its Influencing Factors of Economic Spatial Polarization in the Yangtze River Delta Region

“…It also determines a variety of explanation mechanisms for spatial polarization, such as factor flow, urban prejudice, agglomeration economy, and knowledge spillover [ 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. Other scholars study the spatial polarization of Japanese land price evolution and Ukrainian public opinion polls with the help of the spatial variation function model, micro-dynamic model, and exploratory spatial analysis [ 42 , 43 ]. Additionally, some scholars measure and explore the level of spatial polarization in the development of urbanization, railway transportation, and scientific and technological innovation, and have found that the regional labor market, economic structure, settlement structure, population density, transportation infrastructure, etc., all affect the development of regional imbalances from different aspects [ 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 ].…”

An Assessment of the Accessibility of Multiple Public Service Facilities and Its Correlation with Housing Prices Using an Improved 2SFCA Method—A Case Study of Jinan City, China

“…The resulting mismatch between the supply and demand of public service facilities makes the housing prices in the dominant areas of a city remain high. Such housing prices have become a common phenomenon in the city of Los Angeles, Paris, Tokyo [3][4][5] and many other cities and even around the world. The spatial allocation pattern of public service resources dominates the formation and evolution of the space of urban housing prices by affecting the housing choice behavior of house buyers, making housing prices increasingly differentiated and further reshaping the urban landscape through the selection of housing buyers.…”