The Measurement of Neighborhood Dynamics in Urban House Prices
引入地理视角扩展传统特征价格模型，研究住房属性对房价的影响是否随位置变化，并使用俄亥俄州哥伦布市数据验证了扩展方法更准确反映市场运行。
This paper introduces an explicit geographic perspective for modeling the housing price determination process. The traditional econometric models that utilize the hedonic price regression are accepted but are extended to incorporate spatial neighborhood dynamics. The expansion method is used as the general modeling framework. The question posed by this research is: Do housing attributes produce different pricing differentials depending on location? Consequently, the models that are generated are characterized by spatial variation with respect to the influence of housing attributes on housing prices. In addition to its conceptual concern, this paper also deals with spatial dependence, an issue that has not been addressed in the previous empirical investigations. The empirical segment of this research uses data for the Columbus, Ohio MSA. The results suggest that the models constructed using the expansion method more accurately mirror the workings of the residential real estate markets.