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Housing Price Dynamics in Time and Space: Predictability, Liquidity and Investor Returns

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  • Min Hwang
  • John Quigley

Abstract

It is widely accepted that aggregate housing prices are predictable, but that excess returns to investors are precluded by the transactions costs of buying and selling property. We examine this issue using a unique data set -- all private condominium transactions in Singapore during an eleven-year period. We model directly the price discovery process for individual dwellings. Our empirical results clearly reject a random walk in prices, supporting mean reversion in housing prices and diffusion of innovations over space. We find that, when house prices and aggregate returns are computed from models that erroneously assume a random walk and spatial independence, they are strongly autocorrelated. However, when they are calculated from the appropriate model, predictability in prices and in investment returns is completely absent. We show that this is due to the illiquid nature of housing transactions. We also conduct extensive simulations, over different time horizons and with different investment rules, testing whether better information on housing price dynamics leads to superior investment performance.
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  • Min Hwang & John Quigley, 2010. "Housing Price Dynamics in Time and Space: Predictability, Liquidity and Investor Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 41(1), pages 3-23, July.
    • Handle: RePEc:kap:jrefec:v:41:y:2010:i:1:p:3-23
    DOI: 10.1007/s11146-009-9207-x
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    Cited by:

    1. Andrew Coleman & Grant Scobie, 2009. "A Simple Model of Housing Rental and Ownership with Policy Simulations," Working Papers 09_08, Motu Economic and Public Policy Research.
    2. Marius Claudy and Claus Michelsen, 2016. "Housing Market Fundamentals, Housing Quality and Energy Consumption: Evidence from Germany," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    3. Garner, Thesia I. & Verbrugge, Randal, 2009. "Reconciling user costs and rental equivalence: Evidence from the US consumer expenditure survey," Journal of Housing Economics, Elsevier, vol. 18(3), pages 172-192, September.
    4. Holly, Sean & Hashem Pesaran, M. & Yamagata, Takashi, 2011. "The spatial and temporal diffusion of house prices in the UK," Journal of Urban Economics, Elsevier, vol. 69(1), pages 2-23, January.
    5. Liang Jiang & Peter C.B. Phillips & Jun Yu, 2014. "A New Hedonic Regression for Real Estate Prices Applied to the Singapore Residential Market," Cowles Foundation Discussion Papers 1969, Cowles Foundation for Research in Economics, Yale University.
    6. Stanley McGreal & Paloma Taltavull de La Paz, 2013. "Implicit House Prices: Variation over Time and Space in Spain," Urban Studies, Urban Studies Journal Limited, vol. 50(10), pages 2024-2043, August.
    7. Paloma Taltavull de La Paz, 2021. "Predicting housing prices. A long term housing price path for Spanish regions," LARES lares-2021-4dra, Latin American Real Estate Society (LARES).
    8. Robert J. Hill & Norbert Pfeifer & Miriam Steurer & Radoslaw Trojanek, 2024. "Warning: Some transaction prices can be detrimental to your house price index," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 70(2), pages 320-344, June.
    9. L. Li & K. W. Chau, 2019. "What Motivates a Developer to Sell before Completion?," The Journal of Real Estate Finance and Economics, Springer, vol. 59(2), pages 209-232, August.

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    More about this item

    Keywords

    Housing market liquidity; Price discovery; Spatial correlation; E31; C23; R32;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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