Accounting for Spatial Variation of Land Prices in Hedonic Imputation House Price Indices: a Semi-Parametric Approach

Gong Yunlong () and Jan de Haan ()
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Gong Yunlong: Department of Land Resource Management, China University of Mining and Technology, Daxue Road 1, 221116Xuzhou, China.
Jan de Haan: OTB-Research for the Built Environment, Delft University of Technology, Juliannalaan 134, 2628 BLDelft, The Netherlands.

Journal of Official Statistics, 2018, vol. 34, issue 3, 695-720

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.

Keywords: Geospatial information; hedonic modeling; land and structure prices; mixed geographically weighted regression; residential property (search for similar items in EconPapers)
JEL-codes: C14 C33 C43 E31 R31 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:34:y:2018:i:3:p:695-720:n:6

DOI: 10.2478/jos-2018-0033

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