An empirical analysis on spatial effects of the housing price based on spatial econometric models:Evidence from Hangzhou City
Ling Zhang
Abstract
Ling Zhang
Abstract
Applying spatial autocorrelation Moran's index and techniques of spatial econometrics,the spatial effects and determinants of urban housing prices were studied.With micro housing data of 317 communities in Hangzhou in 2008,the spatial lag model and spatial error model based on hedonic price method were constructed.The results show that significant spatial effects exist in housing prices,and the results derived from spatial econometric models are apparently superior to that traditional model. Accordingly,spatial econometric models improve the effectiveness and robustness of the hedonic price model.
OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Applying spatial autocorrelation Moran's index and techniques of spatial econometrics,the spatial effects and determinants of urban housing prices were studied.With micro housing data of 317 communities in Hangzhou in 2008,the spatial lag model and spatial error model based on hedonic price method were constructed.The results show that significant spatial effects exist in housing prices,and the results derived from spatial econometric models are apparently superior to that traditional model. Accordingly,spatial econometric models improve the effectiveness and robustness of the hedonic price model.
Key concepts: Econometrics, Spatial econometrics, Spatial analysis, Econometric model, Lag, Economics, Spatial dependence, Robustness (evolution)