Accounting for Spatial Variation of Land Prices in Hedonic Imputation House Price Indices

A Semi-Parametric Approach

Journal Article (2018)
Author(s)

Y Gong (China University of Mining and Technology, TU Delft - OLD Housing Systems)

Jan de Haan (TU Delft - OLD Housing Systems, Statistics Netherlands (CBS))

Research Group
OLD Housing Systems
Copyright
© 2018 Y. Gong, J. de Haan
DOI related publication
https://doi.org/10.2478/jos-2018-0033
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 Y. Gong, J. de Haan
Research Group
OLD Housing Systems
Issue number
3
Volume number
34
Pages (from-to)
695-720
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Abstract

Location is capitalized into the price of the land the structure of a property is built on, and land prices can be expected to vary significantly across space. We account for spatial variation of land prices in hedonic house price models using geospatial data and a semi-parametric method known as mixed geographically weighted regression. To measure the impact on aggregate price change, quality-adjusted (hedonic imputation) house price indices are constructed for a small city in the Netherlands and compared to price indices based on more restrictive models, using postcode dummy variables, or no location information at all. We find that, while taking spatial variation of land prices into account improves the model performance, the Fisher house price indices based on the different hedonic models are almost identical. The land and structures price indices, on the other hand, are sensitive to the treatment of location.