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Hedonic versus repeat-sales housing price indexes for measuring the recent boom-bust cycle

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  • Dorsey, Robert E.
  • Hu, Haixin
  • Mayer, Walter J.
  • Wang, Hui-chen
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    Abstract

    Standard housing price indexes rely on strong constant-quality assumptions and often conflict. Hedonic price indexes overcome limitations of median price and repeat-sales indexes but their implementation has been limited by a lack of data. This paper constructs hedonic indexes at the zip code level for the Los Angeles and San Diego metropolitan areas using considerably more detailed data than previously available. Our sample was collected by a mortgage technology firm, and consists of almost 1.1 million transactions during the boom-bust cycle since 2000. Our hedonic regressions include new spatial models that capture correlations within submarkets (using zip codes as proxies) and allow temporal asymmetry. Compared to a repeat-sales price index constructed from the same data, the hedonic indexes indicate that the market peaked about 11Â months later in Los Angeles and about 2Â months earlier in San Diego, show less pre-peak appreciation and post-peak depreciation in low-tier housing and more pre-peak appreciation in high-tier housing. We also find that the intensity of the cycle varies greatly across zip codes and price-tiers in a pattern consistent with foreclosure activity.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Housing Economics.

    Volume (Year): 19 (2010)
    Issue (Month): 2 (June)
    Pages: 75-93

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    Handle: RePEc:eee:jhouse:v:19:y:2010:i:2:p:75-93

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    Web page: http://www.elsevier.com/locate/inca/622881

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    Keywords: Hedonic housing price indexes Repeat-sales indexes;

    References

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    Cited by:
    1. Fabian Y.R.P. Bocart & Christian M. Hafner, 2012. "Volatility of price indices for heterogeneous goods," SFB 649 Discussion Papers SFB649DP2012-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Angjellari-Dajci, Fiorentina & Boylan, Robert & Cebula, Richard, 2014. "Firm Size, Dual Brokerage, and National Franchise Affiliation of Real Estate Brokerage Firms: Unexpected Results from 2008 to 2013," MPRA Paper 55897, University Library of Munich, Germany.
    3. Robert J. Hill & Michael Scholz, 2014. "Incorporating Geospatial Data in House Price Indexes: A Hedonic Imputation Approach with Splines," Graz Economics Papers 2014-05, University of Graz, Department of Economics.
    4. Andrea Chegut & Piet Eichholtz & Paulo Rodrigues, 2013. "The London Commercial Property Price Index," The Journal of Real Estate Finance and Economics, Springer, vol. 47(4), pages 588-616, November.
    5. Jing Wu & Yongheng Deng & Hongyu Liu, 2014. "House Price Index Construction in the Nascent Housing Market: The Case of China," The Journal of Real Estate Finance and Economics, Springer, vol. 48(3), pages 522-545, April.
    6. Diewert, W. Erwin & Nishimura , Kiyohiko & Shimizu, Chihiro & Watanabe, Tsutomu, 2014. "Residential Property Price Indexes for Japan: An Outline of the Japanese Official RPPI," Economics working papers erwin_diewert-2014-17, Vancouver School of Economics, revised 27 Mar 2014.
    7. Liao, Wen-Chi & Wang, Xizhu, 2012. "Hedonic house prices and spatial quantile regression," Journal of Housing Economics, Elsevier, vol. 21(1), pages 16-27.
    8. Esmeralda Ramalho & Joquim Ramalho, 2014. "Convenient links for the estimation of hedonic price indexes:the case of unique, infrequently traded assets," CEFAGE-UE Working Papers 2014_01, University of Evora, CEFAGE-UE (Portugal).

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