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

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  • Gong Yunlong

    (Department of Land Resource Management, China University of Mining and Technology, Daxue Road 1, 221116Xuzhou, China.)

  • de Haan Jan

    (OTB-Research for the Built Environment, Delft University of Technology, Juliannalaan 134, 2628 BLDelft, The Netherlands.)

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.

Suggested Citation

  • Gong Yunlong & de Haan Jan, 2018. "Accounting for Spatial Variation of Land Prices in Hedonic Imputation House Price Indices: a Semi-Parametric Approach," Journal of Official Statistics, Sciendo, vol. 34(3), pages 695-720, September.
  • Handle: RePEc:vrs:offsta:v:34:y:2018:i:3:p:695-720:n:6
    DOI: 10.2478/jos-2018-0033
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    1. Alicia Rambaldi & Prasada Rao, 2011. "Hedonic Predicted House Price Indices Using Time-Varying Hedonic Models with Spatial Autocorrelation," Discussion Papers Series 432, School of Economics, University of Queensland, Australia.
    2. W. Erwin DIEWERT & Jan de HAAN & Rens HENDRIKS, 2011. "The Decomposition of a House Price Index into Land and Structures Components: A Hedonic Regression Approach," The Valuation Journal, National Association of Romanian Valuers, vol. 6(1), pages 58-105.
    3. Davis, Morris A. & Heathcote, Jonathan, 2007. "The price and quantity of residential land in the United States," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2595-2620, November.
    4. Henri L.F. de Groot & Gerard Marlet & Coen Teulings & Wouter Vermeulen, 2015. "Cities and the Urban Land Premium," Books, Edward Elgar Publishing, number 16515, September.
    5. Alicia N. Rambaldi & D.S. Prasada Rao, 2013. "Econometric Modeling and Estimation of Theoretically Consistent Housing Price Indexes," CEPA Working Papers Series WP042013, School of Economics, University of Queensland, Australia.
    6. Robert J. Hill & Daniel Melser, 2008. "Hedonic Imputation And The Price Index Problem: An Application To Housing," Economic Inquiry, Western Economic Association International, vol. 46(4), pages 593-609, October.
    7. Eurostat, 2013. "Handbook on Residential Property Prices Indices," World Bank Publications, The World Bank, number 17280, July.
    8. W. Erwin Diewert & Jan de Haan & Rens Hendriks, 2015. "Hedonic Regressions and the Decomposition of a House Price Index into Land and Structure Components," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 106-126, February.
    9. Yong Tu & Shi‐Ming Yu & Hua Sun, 2004. "Transaction‐Based Office Price Indexes: A Spatiotemporal Modeling Approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(2), pages 297-328, June.
    10. Davis, Morris A. & Palumbo, Michael G., 2008. "The price of residential land in large US cities," Journal of Urban Economics, Elsevier, vol. 63(1), pages 352-384, January.
    11. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.
    12. John M. Clapp, 2004. "A Semiparametric Method for Estimating Local House Price Indices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(1), pages 127-160, March.
    13. Dorsey, Robert E. & Hu, Haixin & Mayer, Walter J. & Wang, Hui-chen, 2010. "Hedonic versus repeat-sales housing price indexes for measuring the recent boom-bust cycle," Journal of Housing Economics, Elsevier, vol. 19(2), pages 75-93, June.
    14. Hua Sun & Yong Tu & Shi-Ming Yu, 2005. "A Spatio-Temporal Autoregressive Model for Multi-Unit Residential Market Analysis," The Journal of Real Estate Finance and Economics, Springer, vol. 31(2), pages 155-187, September.
    15. Pace, R Kelley & Barry, Ronald & Clapp, John M. & Rodriquez, Mauricio, 1998. "Spatiotemporal Autoregressive Models of Neighborhood Effects," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 15-33, July.
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    Cited by:

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    More about this item

    Keywords

    Geospatial information; hedonic modeling; land and structure prices; mixed geographically weighted regression; residential property;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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