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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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File URL: http://hdl.handle.net/10.1007/s11146-005-1370-0
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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

Related research

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

References

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  1. 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.
  2. 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.
  3. Hwang, Min & Quigley, John M., 2002. "Price Discovery in Time and Space: The Course of Condominium Prices in Singapore," Department of Economics, Working Paper Series qt260185hr, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
  4. 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.
  5. R. Kelley Pace & Otis W. Gilley, 1998. "Generalizing the OLS and Grid Estimators," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 26(2), pages 331-347.
  6. 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.
  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. Kevin Gillen & Thomas Thibodeau & Susan Wachter, . "Anistropic Autocorrelation in House Prices," Zell/Lurie Center Working Papers 383, Wharton School Samuel Zell and Robert Lurie Real Estate Center, University of Pennsylvania.
  9. 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.
  10. 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.
  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. 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.
  13. Clapp, John M & Rodriguez, Mauricio, 1999. "Erratum: Spatiotemporal Autoregressive Models of Neighborhood Effects," The Journal of Real Estate Finance and Economics, Springer, vol. 19(1), pages 85, July.
  14. 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.
  15. 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.
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Citations

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Cited by:
  1. S. Wong & C. Yiu & K. Chau, 2013. "Trading Volume-Induced Spatial Autocorrelation in Real Estate Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(4), pages 596-608, May.
  2. Tiziana Caliman & Enrico di Bella, 2011. "Spatial Autoregressive Models for House Price Dynamics in Italy," Economics Bulletin, AccessEcon, vol. 31(2), pages 1837-1855.
  3. 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.
  4. Bartz, Kevin & Fuchs-Schündeln, Nicola, 2012. "The Role of Borders, Languages, and Currencies as Obstacles to Labor Market Integration," CEPR Discussion Papers 8987, C.E.P.R. Discussion Papers.
  5. Gelfand, Alan E. & Banerjee, Sudipto & Sirmans, C.F. & Tu, Yong & Eng Ong, Seow, 2007. "Multilevel modeling using spatial processes: Application to the Singapore housing market," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3567-3579, April.
  6. Yong Tu & Seow Ong & Ying Han, 2009. "Turnovers and Housing Price Dynamics: Evidence from Singapore Condominium Market," The Journal of Real Estate Finance and Economics, Springer, vol. 38(3), pages 254-274, April.
  7. Jean Dubé & Diègo Legros, 2013. "Dealing with spatial data pooled over time in statistical models," Letters in Spatial and Resource Sciences, Springer, vol. 6(1), pages 1-18, March.
  8. Deng, Yongheng & McMillen, Daniel P. & Sing, Tien Foo, 2012. "Private residential price indices in Singapore: A matching approach," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 485-494.

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