Space-Varying Regression Coefficients: A Semi-parametric Approach Applied to Real Estate Markets |
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Authors: | Andrey D Pavlov |
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Institution: | Concordia University, Montreal, PQ H3G 1M8, Canada or . |
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Abstract: | 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. |
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