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

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  • Hwang, Min
  • Quigley, John M.

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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Bibliographic Info

Paper provided by Berkeley Program on Housing and Urban Policy in its series Berkeley Program on Housing and Urban Policy, Working Paper Series with number qt41k6c76w.

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Date of creation: 22 May 2010
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Handle: RePEc:cdl:bphupl:qt41k6c76w

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Keywords: housing market liquidity; price discovery; spatial correlation; Social and Behavioral Sciences;

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References

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  1. 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 127-46, June.
  2. 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.
  3. 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.
  4. Peter ENGLUND & Min HWANG & John M. QUIGLEY, 2000. "Hedging Housing Risk," FAME Research Paper Series rp26, International Center for Financial Asset Management and Engineering.
  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. 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.
  7. John V. Duca, 2005. "Making sense of elevated housing prices," Southwest Economy, Federal Reserve Bank of Dallas, issue Sep, pages 1, 7-13.
  8. Hong, Yongmiao, 1996. "Consistent Testing for Serial Correlation of Unknown Form," Econometrica, Econometric Society, vol. 64(4), pages 837-64, July.
  9. 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.
  10. Malpezzi, Stephen, 1999. "A Simple Error Correction Model of House Prices," Journal of Housing Economics, Elsevier, vol. 8(1), pages 27-62, March.
  11. 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.
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Cited by:
  1. 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.
  2. 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.
  3. Randal Verbrugge & Thesia I. Garner, 2009. "Reconciling User Costs and Rental Equivalence: Evidence from the U.S. Consumer Expenditure Survey," Working Papers 427, U.S. Bureau of Labor Statistics.

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