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

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  • Min Hwang

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  • John Quigley

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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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Suggested Citation

  • 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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    References listed on IDEAS

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    1. Englund, Peter & Hwang, Min & Quigley, John M, 2002. "Hedging Housing Risk," The Journal of Real Estate Finance and Economics, Springer, vol. 24(1-2), pages 167-200, Jan.-Marc.
    2. Englund, Peter & Gordon, Tracy M. & Quigley, John M., 1999. "The Valuation of Real Capital: A Random Walk down Kungsgatan," Journal of Housing Economics, Elsevier, vol. 8(3), pages 205-216, September.
    3. Hong, Yongmiao, 1996. "Consistent Testing for Serial Correlation of Unknown Form," Econometrica, Econometric Society, vol. 64(4), pages 837-864, July.
    4. Guntermann, Karl L & Norrbin, Stefan C, 1991. "Empirical Tests of Real Estate Market Efficiency," The Journal of Real Estate Finance and Economics, Springer, vol. 4(3), pages 297-313, September.
    5. K. J. Martijn Cremers & Jianping Mei, 2007. "Turning over Turnover," Review of Financial Studies, Society for Financial Studies, vol. 20(6), pages 1749-1782, November.
    6. John V. Duca, 2005. "Making sense of elevated housing prices," Southwest Economy, Federal Reserve Bank of Dallas, issue Sep, pages 1,7-13.
    7. Malpezzi, Stephen, 1999. "A Simple Error Correction Model of House Prices," Journal of Housing Economics, Elsevier, vol. 8(1), pages 27-62, March.
    8. Sing, Tien Foo, 2001. "Dynamics of the Condominium Market in Singapore," International Real Estate Review, Asian Real Estate Society, vol. 4(1), pages 135-158.
    9. Hill, R. Carter & Sirmans, C. F. & Knight, John R., 1999. "A random walk down main street?," Regional Science and Urban Economics, Elsevier, vol. 29(1), pages 89-103, January.
    10. Quigley, John M., 2002. "Transactions Costs and Housing Markets," Berkeley Program on Housing and Urban Policy, Working Paper Series qt6pz8p6zt, Berkeley Program on Housing and Urban Policy.
    11. Quan, Daniel C & Quigley, John M, 1991. "Price Formation and the Appraisal Function in Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 4(2), pages 127-146, June.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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).
    5. Liang Jiang & Peter C.B. Phillips & Jun Yu, 2014. "A New Hedonic Regression for Real Estate Prices Applied to the Singapore Residential Market," Working Papers 19-2014, Singapore Management University, School of Economics.

    More about this item

    Keywords

    Housing market liquidity; Price discovery; Spatial correlation; E31; C23; R32;

    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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