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Residential Property Price Indexes: Spatial Coordinates versus Neighbourhood Dummy Variables

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  • Diewert, Erwin
  • Shimizu, Chihiro
Abstract
The paper addresses the following question: can satisfactory residential property price indexes be constructed using hedonic regression techniques where location effects are modeled using local neighbourhood dummy variables or is it necessary to use spatial coordinates to model location effects. Hill and Scholz (2018) addressed this question and found, using their hedonic regression model, that it was not necessary to use spatial coordinates to obtain satisfactory property price indexes for Sydney. However, their hedonic regression model did not estimate separate land and structure price indexes for residential properties. In order to construct national balance sheet estimates, it is necessary to have separate land and structure price indexes. The present paper addresses the Hill and Scholz question in the context of providing satisfactory residential land price indexes. The spatial coordinate model used in the present paper is a modification of Colwell’s (1998) spatial interpolation method. The modification can be viewed as a general nonparametric method for estimating a function of two variables.

Suggested Citation

  • Diewert, Erwin & Shimizu, Chihiro, 2019. "Residential Property Price Indexes: Spatial Coordinates versus Neighbourhood Dummy Variables," Microeconomics.ca working papers erwin_diewert-2019-11, Vancouver School of Economics, revised 10 Jan 2020.
    • Handle: RePEc:ubc:pmicro:erwin_diewert-2019-11
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    File URL: https://econ2017.sites.olt.ubc.ca/files/2020/01/pdf_paper_erwin-diewert-19-08RPPISpatialCoordetc.pdf
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    References listed on IDEAS

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    1. W. Erwin Diewert & Kevin J. Fox & Chihiro Shimizu, 2016. "Commercial Property Price Indexes And The System Of National Accounts," Journal of Economic Surveys, Wiley Blackwell, vol. 30(5), pages 913-943, December.
    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, The National Association of Authorized Romanian Valuers, vol. 6(1), pages 58-105.
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    5. Burnett-Isaacs Kate & Huang Ning & Diewert W. Erwin, 2020. "Developing Land and Structure Price Indices for Ottawa Condominium Apartments," Journal of Official Statistics, Sciendo, vol. 36(4), pages 763-802, December.
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    8. Diewert, W. Erwin & Fox, Kevin J., 2017. "Substitution Bias in Multilateral Methods for CPI Construction using Scanner Data," Microeconomics.ca working papers erwin_diewert-2017-3, Vancouver School of Economics, revised 23 Mar 2017.
    9. 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.
    10. Burnett-Isaacs,, Kate & Diewert, Erwin & Huang, Ning, 2017. "Alternative Approaches for Resale Housing Price Indexes," Microeconomics.ca working papers erwin_diewert-2017-6, Vancouver School of Economics, revised 08 May 2017.
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    17. Schwann, Gregory M, 1998. "A Real Estate Price Index for Thin Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 16(3), pages 269-287, May.
    18. Colwell, Peter F, 1998. "A Primer on Piecewise Parabolic Multiple Regression Analysis via Estimations of Chicago CBD Land Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 87-97, July.
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    Cited by:

    1. Chihiro Shimizu & Erwin Diewert, 2023. "Scanner Data, Product Churn and Quality Adjustment," Working Papers e185, Tokyo Center for Economic Research.
    2. Michał Hebdzyński, 2024. "Price-setting factors or revealed preferences? How to understand the results of hedonic models and hedonic indices of the housing rental market that base on listings data?," Bank i Kredyt, Narodowy Bank Polski, vol. 55(4), pages 519-550.

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    More about this item

    Keywords

    Residential property price indexes; System of National Accounts; Balance Sheets; methods of depreciation;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • 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
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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