Space-varying regression coefficients: A semi-parametric approach applied to real estate markets

被引:71
作者
Pavlov, AD [1 ]
机构
[1] Concordia Univ, Montreal, PQ H3G 1M8, Canada
关键词
D O I
10.1111/1540-6229.00801
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper presents a method for estimating home Values by non-parametrically incorporating the physical location of the properties. Specifically, I allow the parameters of the observed covariates to vary in space. This approach mitigates one of the biggest deficiencies inherent in hedonic pricing models-omitted variables. I demonstrate the advantages of the proposed method using real estate transaction data from Los Angeles County. The estimation finds a substantial spatial Variation of the marginal values of the hedonic characteristics and provides an insight into the segmentation of the market. The proposed method is an extension of semi-parametric multi-dimensional k-nearest-neighbor smoothing. It alleviates a fundamental problem known as the curse of dimensionality by incorporating parametric components into a non-parametric estimation.
引用
收藏
页码:249 / 283
页数:35
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