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Fooled by Search: Housing Prices, Turnover and Bubbles

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  • Brian Peterson

Abstract

This paper develops and estimates a model to explain the behaviour of house prices in the United States. The main finding is that over 70% of the increase in house prices relative to trend during the increase of house prices in the United States from 1995 to 2006 can be explained by a pricing mechanism where market participants are ‘Fooled by Search.’ Trading frictions, also known as search frictions, have been argued to affect asset prices, so that asset markets are constrained efficient, with shocks to liquidity causing prices to temporarily deviate from long run fundamentals. In this paper a model is proposed and estimated that combines search frictions with a behavioural assumption where market participants incorrectly believe that the efficient market theory holds. In other words, households are ‘Fooled by Search.’ Such a model is potentially fruitful because it can replicate the observation that real price growth and turnover are highly correlated at an annual frequency in the United States housing market. A linearized version of the model is estimated using standard OLS and annual data. In addition to explaining over 70% of the housing bubble in the United States, the model also predicts and estimation confirms that in regions with a low elasticity of supply, price growth should be more sensitive to turnover. Using the lens of turnover, a supply shock is identified and estimated that has been responsible for over 80% of the fall in real house prices from the peak in 2006 to 2010.

Suggested Citation

  • Brian Peterson, 2012. "Fooled by Search: Housing Prices, Turnover and Bubbles," Staff Working Papers 12-3, Bank of Canada.
  • Handle: RePEc:bca:bocawp:12-3
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    References listed on IDEAS

    as
    1. Antonia Díaz & Belén Jerez, 2013. "House Prices, Sales, And Time On The Market: A Search‐Theoretic Framework," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54, pages 837-872, August.
    2. Mark Andrew & Geoffrey Meen, 2003. "House Price Appreciation, Transactions and Structural Change in the British Housing Market: A Macroeconomic Perspective," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(1), pages 99-116, March.
    3. Jim Clayton & Norman Miller & Liang Peng, 2010. "Price-volume Correlation in the Housing Market: Causality and Co-movements," The Journal of Real Estate Finance and Economics, Springer, vol. 40(1), pages 14-40, January.
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. The housing bubble: fooled by efficiency
      by Economic Logician in Economic Logic on 2012-02-22 21:11:00

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    Cited by:

    1. Masanori Kashiwagi, 2014. "Sunspots and Self-Fulfilling Beliefs in the U.S. Housing Market," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(4), pages 654-676, October.
    2. 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.
    3. Gaetano Lisi, 2013. "Matching Models and Housing Markets: the Role of the Zero-Profit Condition," Economic Research Guardian, Weissberg Publishing, vol. 3(1), pages 54-60, June.
    4. Gaetano Lisi, 2013. "On the Functional Form of the Hedonic Price Function: A Matching-theoretic Model and Empirical Evidence," International Real Estate Review, Global Social Science Institute, vol. 16(2), pages 189-207.
    5. Pascal Towbin & Sebastian Weber, 2015. "Price Expectations and the U.S. Housing Boom," IMF Working Papers 2015/182, International Monetary Fund.
    6. Han, Lu & Strange, William C., 2015. "The Microstructure of Housing Markets," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 813-886, Elsevier.
    7. Duncan Maclennan & Anthony O’Sullivan, 2012. "Housing markets, signals and search," Journal of Property Research, Taylor & Francis Journals, vol. 29(4), pages 324-340, July.

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    More about this item

    Keywords

    Asset pricing; Business fluctuations and cycles;

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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