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This study investigates the spatial statistics of house prices in Beijing, China. We examine whether the house prices in one region is affected by the house price in neighbouring regions. We also investigate how the house prices in one region is affected by unknown characteristics of the neighbouring regions. Moreover, we analyse whether the explanatory factors of house prices in one region are affected by explanatory factors of house prices in neighbouring regions. Subsequently, we attempt to investigate the spatial spill-over effects of explanatory factors. Initially, we use Lagrange Multiplier (LM) test to examine the significance of spatial autocorrelation. After this we apply the spatial autoregressive model (SAR), spatial Durbin model (SDM), spatial autoregressive model with autoregressive disturbances (SAC) and spatial error model (SEM) into spatial regression methods. The paper overcomes the shortcomings of the previous studies by extending the range of examining spatial models, providing reasonable spatial model selection procedures, and employing improved spatial weights to analysing spillover effects of explanatory factors. On the aspect of analysing direct and indirect (spill-over) effects, this study examines the partitioning of direct and indirect effects and finds out the impacts of the neighbouring factors. Evidence is found for spatial dependence of house prices: house prices in one region are influenced by the house prices in neighbouring regions positively and significantly. Evidence is found for spatial heterogeneity of house prices across the space: house prices in neighbouring regions spill over more in times of increasing neighbouring house prices, then when neighbouring house prices are declining. Evidence is found for spatial spillover effects of explanatory factors: increases of average wage of real estate staff, income , tax, urban population and the house prices of the previous year increases the house prices positively in neighbouring regions; a decrease of unemployment drives down the house prices in neighbouring regions. |
