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Clustering in Real Estate Prices: Determinants and Consequences

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Author Info

  • Oded Palmon

    ()
    (Rutgers University)

  • Barton A. Smith
  • Ben J. Sopranzetti
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    Abstract

    We examine the determinants and consequences of price clustering. Real estate list and transaction prices exhibit two price-ending characteristics: even (000-ending) and just-below-even (900-ending). The use of even-ending prices is negatively related to the precision of the price estimates and the cost of rounding. However, the tendency to use just-below-even-ending prices is related to the cost of rounding and to listing agency characteristics. The transaction price and the number of days on market are associated with list price clustering and with listing agency characteristics. Most properties are listed at just-below-even-ending prices, but those listed at even-ending prices sell faster and at a higher price. Finally, better transaction outcomes are positively associated with the number of area-properties listed by the seller?s real-estate agency.

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    File URL: http://aux.zicklin.baruch.cuny.edu/jrer/papers/pdf/past/vol26n02/01.115_136.pdf
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    Bibliographic Info

    Article provided by American Real Estate Society in its journal Journal of Real Estate Research.

    Volume (Year): 26 (2004)
    Issue (Month): 2 ()
    Pages: 115-136

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    Handle: RePEc:jre:issued:v:26:n:2:2004:p:115-136

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    Postal: American Real Estate Society Clemson University School of Business & Behavioral Science Department of Finance 401 Sirrine Hall Clemson, SC 29634-1323
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    Web page: http://www.aresnet.org/

    Order Information:
    Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323
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    Web: http://aux.zicklin.baruch.cuny.edu/jrer/about/get.htm

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    Cited by:
    1. Franz Hackl & Michael E. Kummer & Rudolf Winter-Ebmer, 2010. "99 cent: Price Points in E-Commerce," Economics working papers 2010-02, Department of Economics, Johannes Kepler University Linz, Austria.
    2. Aerts, Walter & Campenhout, Geert Van & Caneghem, Tom Van, 2008. "Clustering in dividends: Do managers rely on cognitive reference points?," Journal of Economic Psychology, Elsevier, vol. 29(3), pages 276-284, June.
    3. Bharati, Rakesh & Crain, Susan J. & Kaminski, Vincent, 2012. "Clustering in crude oil prices and the target pricing zone hypothesis," Energy Economics, Elsevier, vol. 34(4), pages 1115-1123.
    4. Mitchell, Jason & Izan, H.Y., 2006. "Clustering and psychological barriers in exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(4), pages 318-344, October.
    5. Kirsten Rüchardt & Bodo Vogt, 2009. "Comparison of the Stock Price Clustering of stocks which are traded in the US and Germany—Is XETRA more efficient than the NYSE?," FEMM Working Papers 09016, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    6. Sean Salter & Ken Johnson & Ernest King, 2010. "Listing Specialization and Pricing Precision," The Journal of Real Estate Finance and Economics, Springer, vol. 40(3), pages 245-259, April.
    7. Ahn, Hee-Joon & Cai, Jun & Cheung, Yan Leung, 2005. "Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong," Journal of Financial Markets, Elsevier, vol. 8(4), pages 421-451, November.

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