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Temporal and Spatial Information Diffusion in Real Estate Price Changes and Variances

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  • Walter Dolde
  • Dogan Tirtiroglu
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    Abstract

    This article examines patterns of temporal and spatial diffusion of real estate price changes. In addition to means, changes in volatility are tracked in reaction to substantial new information, estimated with GARCH-M methods. The data covers towns in Connecticut and near San Francisco. There is evidence of negative feedback at short lags, contrary to previous research on housing and other assets. There is also evidence of a moving average error process which tends to reverse recent shocks. Significantly positive spatial information diffusion is found from neighboring towns in Connecticut but none in control tests on nonneighboring towns. The results also include evidence of a risk-reward tradeoff in housing price changes in the San Francisco area. Copyright American Real Estate and Urban Economics Association.

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    Bibliographic Info

    Article provided by American Real Estate and Urban Economics Association in its journal Real Estate Economics.

    Volume (Year): 25 (1997)
    Issue (Month): 4 ()
    Pages: 539-565

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    Handle: RePEc:bla:reesec:v:25:y:1997:i:4:p:539-565

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    Cited by:
    1. S. Wong & K. Chau & C. Yiu, 2007. "Volatility Transmission in the Real Estate Spot and Forward Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 35(3), pages 281-293, October.
    2. Costello, Greg & Fraser, Patricia & Groenewold, Nicolaas, 2011. "House prices, non-fundamental components and interstate spillovers: The Australian experience," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 653-669, March.
    3. Hong Miao & Sanjay Ramchander & Marc W. Simpson, 2011. "Return and Volatility Transmission in U.S. Housing Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 39(4), pages 701-741, December.
    4. Chen, Pei-Fen & Chien, Mei-Se & Lee, Chien-Chiang, 2011. "Dynamic modeling of regional house price diffusion in Taiwan," Journal of Housing Economics, Elsevier, vol. 20(4), pages 315-332.
    5. Franz Fuerst, 2008. "Office Rent Determinants: a Hedonic Panel Analysis," Real Estate & Planning Working Papers rep-wp2008-12, Henley Business School, Reading University.
    6. Oikarinen, Elias, 2005. "The Diffusion of Housing Price Movements from Centre to Surrounding Areas," Discussion Papers 979, The Research Institute of the Finnish Economy.
    7. Michail Karoglou & Bruce Morley & Dennis Thomas, 2013. "Risk and Structural Instability in US House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 424-436, April.
    8. Mei-Se Chien, 2010. "Structural Breaks and the Convergence of Regional House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 40(1), pages 77-88, January.
    9. Simlai, Prodosh, 2014. "Estimation of variance of housing prices using spatial conditional heteroskedasticity (SARCH) model with an application to Boston housing price data," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 17-30.
    10. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    11. Norman Miller & Liang Peng, 2006. "Exploring Metropolitan Housing Price Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 33(1), pages 5-18, August.
    12. Riddel, Mary, 1999. "Fundamentals, Feedback Trading, and Housing Market Speculation: Evidence from California," Journal of Housing Economics, Elsevier, vol. 8(4), pages 272-284, December.
    13. William Miles, 2011. "Long-Range Dependence in U.S. Home Price Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 329-347, April.

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