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A Spatio-Temporal Autoregressive Model for Multi-Unit Residential Market Analysis

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  • Hua Sun

    ()

  • Yong Tu

    ()

  • Shi-Ming Yu

    ()

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    Abstract

    By splitting the spatial effects into building and neighborhood effects, this paper develops a two order spatio-temporal autoregressive model to deal with both the spatio-temporal autocorrelations and the heteroscedasticity problem arising from the nature of multi-unit residential real estate data. The empirical results based on 54,282 condominium transactions in Singapore between 1990 and 1999 show that in the multi-unit residential market, a two order spatio-temporal autoregressive model incorporates more spatial information into the model, thus outperforming the models originally developed in the market for single-family homes. This implies that the specification of a spatio-temporal model should consider the physical market structure as it affects the spatial process. It is found that the Bayesian estimation method can produce more robust coefficients by efficiently detecting and correcting heteroscedasticity, indicating that the Bayesian estimation method is more suitable for estimating a real estate hedonic model than the conventional OLS estimation. It is also found that there is a trade off between the heteroscedastic robustness and the incorporation of spatial information into the model estimation. The model is then used to construct building-specific price indices. The results show that the price indices for different condominiums and the buildings within a condominium do behave differently, especially when compared with the aggregate market indices. Copyright Springer Science + Business Media, Inc. 2005

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    Bibliographic Info

    Article provided by Springer in its journal The Journal of Real Estate Finance and Economics.

    Volume (Year): 31 (2005)
    Issue (Month): 2 (September)
    Pages: 155-187
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    Handle: RePEc:kap:jrefec:v:31:y:2005:i:2:p:155-187

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    Web page: http://www.springerlink.com/link.asp?id=102945

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    Related research

    Keywords: spatio-temporal autocorrelation; spatio-temporal model; heteroscedasticity; Gibbs Sampling; Bayesian; Singapore condominium market;

    References

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    1. Min Hwang & John M. Quigley, 2003. "Price Discovery in Time and Space: The Course of Condominium Prices in Singapore," Macroeconomics 0303011, EconWPA.
    2. Pace, R. Kelley & Barry, Ronald & Gilley, Otis W. & Sirmans, C. F., 2000. "A method for spatial-temporal forecasting with an application to real estate prices," International Journal of Forecasting, Elsevier, vol. 16(2), pages 229-246.
    3. Gillen, Kevin & Thibodeau, Thomas & Wachter, Susan, 2001. "Anisotropic Autocorrelation in House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 23(1), pages 5-30, July.
    4. R. Kelley Pace & James P. LeSage, 2004. "Spatial Statistics and Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 147-148, 09.
    5. Dubin, Robin A, 1988. "Estimation of Regression Coefficients in the Presence of Spatially Autocorrelated Error Terms," The Review of Economics and Statistics, MIT Press, vol. 70(3), pages 466-74, August.
    6. Alan E. Gelfand & Mark D. Ecker & John R. Knight & C. F. Sirmans, 2004. "The Dynamics of Location in Home Price," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 149-166, 09.
    7. McMillen, Daniel P., 1996. "One Hundred Fifty Years of Land Values in Chicago: A Nonparametric Approach," Journal of Urban Economics, Elsevier, vol. 40(1), pages 100-124, July.
    8. Case, Karl E & Shiller, Robert J, 1989. "The Efficiency of the Market for Single-Family Homes," American Economic Review, American Economic Association, vol. 79(1), pages 125-37, March.
    9. Basu, Sabyasachi & Thibodeau, Thomas G, 1998. "Analysis of Spatial Autocorrelation in House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 61-85, July.
    10. Can, Ayse & Megbolugbe, Isaac, 1997. "Spatial Dependence and House Price Index Construction," The Journal of Real Estate Finance and Economics, Springer, vol. 14(1-2), pages 203-22, Jan.-Marc.
    11. Deo Bardhan, Ashok & Datta, Rajarshi & Edelstein, Robert H. & Sau Kim, Lum, 2003. "A tale of two sectors: Upward mobility and the private housing market in Singapore," Journal of Housing Economics, Elsevier, vol. 12(2), pages 83-105, June.
    12. Pace, R Kelley, et al, 1998. "Spatiotemporal Autoregressive Models of Neighborhood Effects," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 15-33, July.
    13. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S19-40, Suppl. De.
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    Citations

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    Cited by:
    1. Tiziana Caliman & Enrico di Bella, 2011. "Spatial Autoregressive Models for House Price Dynamics in Italy," Economics Bulletin, AccessEcon, vol. 31(2), pages 1837-1855.
    2. Seow Ong & Poh Neo & Yong Tu, 2008. "Foreclosure Sales: The Effects of Price Expectations, Volatility and Equity Losses," The Journal of Real Estate Finance and Economics, Springer, vol. 36(3), pages 265-287, April.

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