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Disaggregated property price appreciation: The mixed repeat sales model

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  • Melser, Daniel
Abstract
Real estate is, by its nature, a highly heterogeneous asset class with most investors owning a single property rather than a diversified portfolio. As a result their returns are likely to reflect not only the overall dynamics of the asset class but also the way these interact with the unique features of the property. Yet the way that property characteristics influence price dynamics is not well measured or understood. We propose a Mixed Repeat Sales (MRS) model which allows for the nature of the asset to influence price dynamics. This is illustrated empirically using a large data set for the state of New South Wales in Australia (of which Sydney city is the capital) from 2000-2014. The MRS approach enables us to estimate returns at a disaggregated level based upon property characteristics. We find significant dispersion in appreciation rates across locations and that returns were higher for separate houses compared with both apartments and attached houses. However, the size of the dwelling, reflected in the number of bedrooms and bathrooms, and the land area play a lesser role in price developments.

Suggested Citation

  • Melser, Daniel, 2017. "Disaggregated property price appreciation: The mixed repeat sales model," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 108-118.
    • Handle: RePEc:eee:regeco:v:66:y:2017:i:c:p:108-118
    DOI: 10.1016/j.regsciurbeco.2017.05.007
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    References listed on IDEAS

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    Cited by:

    1. Jaromir Vrbka & Tomas Krulicky & Tomas Brabenec & Jan Hejda, 2020. "Determining the Increase in a Building’s Appreciation Rate Due to a Reconstruction," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    2. Daniel Melser, 2017. "Residential Real Estate, Risk, Return and Home Characteristics: Evidence from Sydney 2002-14," ERES eres2017_296, European Real Estate Society (ERES).
    3. Melser, Daniel & Moallemi, Morteza & Kim, Jun Sung, 2021. "Preferences for single-sex schools: Evidence from the housing market," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 710-726.
    4. Melser, Daniel, 2020. "Estimating the housing capitalization effects of new infrastructure: Should we be using rents instead of prices?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 402-421.
    5. Daniel Melser & Robert J. Hill, 2019. "Residential Real Estate, Risk, Return and Diversification: Some Empirical Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 59(1), pages 111-146, July.
    6. Morteza Moallemi & Daniel Melser & Xiaoyan Chen & Ashton Silva, 2022. "The Globalization of Local Housing Markets: Immigrants, the Motherland and Housing Prices in Australia," The Journal of Real Estate Finance and Economics, Springer, vol. 65(1), pages 103-126, July.
    7. Robert J. Hill & Norbert Pfeifer & Miriam Steurer & Radoslaw Trojanek, 2021. "Warning: Some Transaction Prices can be Detrimental to your House Price Index," Graz Economics Papers 2021-11, University of Graz, Department of Economics.
    8. Daniel Melser, 2023. "Selection Bias in Housing Price Indexes: The Characteristics Repeat Sales Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 623-637, June.

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    More about this item

    Keywords

    Repeat sales index; Price index; Real estate; Mixed model;
    All these keywords.

    JEL classification:

    • 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
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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