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A Hierarchical Bayesian Approach for Residential Property Valuation:Application to Hong Kong Housing Market

Author

Listed:
  • Sam K. Hui

    (Stern School of Business of New York University)

  • Alvin Cheung

    (Massachusetts Institute of Technology)

  • Jimmy Pang

    (Stanford University)

Abstract

We have developed a statistical method for the valuation of residential properties using a hierarchical Bayesian approach, which takes into consideration the unique structure of the Hong Kong property market. Our model is calibrated on a dataset that covers all residential real estate transactions in ten major Hong Kong residential complexes from February 2008 to February 2009. Although parsimonious, our model outperforms other valuation methods that are based on average price-per-square- feet or expert assessments. By providing our model-based valuations online without charge, we hope to improve transparency in the Hong Kong housing market, thus enabling consumers to make better investment decisions.

Suggested Citation

  • Sam K. Hui & Alvin Cheung & Jimmy Pang, 2010. "A Hierarchical Bayesian Approach for Residential Property Valuation:Application to Hong Kong Housing Market," International Real Estate Review, Global Social Science Institute, vol. 13(1), pages 1-29.
    • Handle: RePEc:ire:issued:v:13:n:01:2010:p:1-29
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    References listed on IDEAS

    as
    1. 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 125-137, March.
    2. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    3. Tsong-Yue Lai & Kerry Vandell & Ko Wang & Gerd Welke, 2008. "Estimating Property Values by Replication: An Alternative to the Traditional Grid and Regression Methods," Journal of Real Estate Research, American Real Estate Society, vol. 30(4), pages 441-460.
    4. Eric Clapham & Peter Englund & John M. Quigley & Christian L. Redfearn, 2006. "Revisiting the Past and Settling the Score: Index Revision for House Price Derivatives," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 34(2), pages 275-302, June.
    5. Helen X.H. Bao & Alan T.K. Wan, 2004. "On the Use of Spline Smoothing in Estimating Hedonic Housing Price Models: Empirical Evidence Using Hong Kong Data," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(3), pages 487-507, September.
    6. Cropper, Maureen L & Deck, Leland B & McConnell, Kenneth E, 1988. "On the Choice of Functional Form for Hedonic Price Functions," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 668-675, November.
    7. George H. Lentz & Ko Wang, 1998. "Residential Appraisal and the Lending Process: A Survey of Issues," Journal of Real Estate Research, American Real Estate Society, vol. 15(1), pages 11-40.
    8. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
    9. Tsong‐Yue Lai & Ko Wang, 1996. "Comparing the Accuracy of the Minimum‐Variance Grid Method to Multiple Regression in Appraised Value Estimates," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 24(4), pages 531-549, December.
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    Cited by:

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    3. Ying-Hui Chiang & Yuan Ku & Feng Liu & Chin-Oh Chang, 2019. "House Price Dispersion in Taipei Residential Communities," International Real Estate Review, Global Social Science Institute, vol. 22(1), pages 109-129.
    4. Tommy Wu & Michael Cheng & Ken Wong, 2017. "Bayesian analysis of Hong Kong's housing price dynamics," Pacific Economic Review, Wiley Blackwell, vol. 22(3), pages 312-331, August.
    5. Volkan Sevinç, 2022. "Determining the Flat Sales Prices by Flat Characteristics Using Bayesian Network Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 549-577, February.
    6. Yunxi Bai & Jusheng Song & Shanshan Wu & Wei Wang & Jacqueline T. Y. Lo & S. M. Lo, 2020. "Comparing the Impacts of Location Attributes on Residents’ Preferences and Residential Values in Compact Cities: A Case Study of Hong Kong," Sustainability, MDPI, vol. 12(12), pages 1-23, June.
    7. Daikun Wang & Victor Jing Li, 2019. "Mass Appraisal Models of Real Estate in the 21st Century: A Systematic Literature Review," Sustainability, MDPI, vol. 11(24), pages 1-14, December.
    8. Daikun Wang & Victor Jing Li & Huayi Yu, 2020. "Mass Appraisal Modeling of Real Estate in Urban Centers by Geographically and Temporally Weighted Regression: A Case Study of Beijing’s Core Area," Land, MDPI, vol. 9(5), pages 1-18, May.

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    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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