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Comparing Rough Set Theory with Multiple Regression Analysis as Automated Valuation Methodologies

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  • Maurizio d’Amato

    ()
    (1st Faculty of Engineering, Technical University of Bari, Politecnico di Bari, Italy)

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    Abstract

    This paper focuses on the problem of applying rough set theory to mass appraisal. This methodology was first introduced by a Polish mathematician, and has been applied recently as an automated valuation methodology by the author. The method allows the appraiser to estimate a property without defining econometric modeling, although it does not give any quantitative estimation of marginal prices. In a previous paper by the author, data were organized into classes prior to the valuation process, allowing for the if-then, or right “rule” for each property class to be defined. In that work, the relationship between property and class of valued was said to be dichotomic.

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    Bibliographic Info

    Article provided by Asian Real Estate Society in its journal International Real Estate Review.

    Volume (Year): 10 (2007)
    Issue (Month): 2 ()
    Pages: 42-65

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    Handle: RePEc:ire:issued:v:010:n:02:2007:p:42-65

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    Postal: Asia Real Estate Society, 51 Monroe Street, Plaza E-6, Rockville, MD 20850, USA
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    Postal: Asian Real Estate Society, 51 Monroe Street, Plaza E-6, Rockville, MD 20850, USA
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    Related research

    Keywords: mass appraisal; property valuation; rough set theory; valued tolerance relation;

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    1. Han-Bin Kang & Alan K. Reichert, 1991. "An Empirical Analysis of Hedonic Regression and Grid-Adjustment Techniques in Real Estate Appraisal," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(1), pages 70-91.
    2. Hoesli, Martin & Giaccotto, Carmelo & Favarger, Philippe, 1997. "Three New Real Estate Price Indices for Geneva, Switzerland," The Journal of Real Estate Finance and Economics, Springer, vol. 15(1), pages 93-109, July.
    3. Gerald R. Brown & George A. Matysiak & Mark Shepherd, 1998. "Valuation uncertainty and the Mallinson Report," Journal of Property Research, Taylor & Francis Journals, vol. 15(1), pages 1-13, January.
    4. Pawlak, Zdzislaw, 1997. "Rough set approach to knowledge-based decision support," European Journal of Operational Research, Elsevier, vol. 99(1), pages 48-57, May.
    5. 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.
    6. 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.
    7. Mok, Henry M K & Chan, Patrick P K & Cho, Yiu-sun, 1995. "A Hedonic Price Model for Private Properties in Hong Kong," The Journal of Real Estate Finance and Economics, Springer, vol. 10(1), pages 37-48, January.
    8. 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..
    9. Martin Hoesli & Bernard Thion & Craig Watkins, 1997. "A hedonic investigation of the rental value of apartments in central Bordeaux," Journal of Property Research, Taylor & Francis Journals, vol. 14(1), pages 15-26, January.
    10. 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.
    11. Elaine M. Worzala & Margarita Lenk & Ana Silva, 1995. "An Exploration of Neural Networks and Its Application to Real Estate Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 10(2), pages 185-202.
    12. Peter F. Colwell & Roger E. Cannaday & Chunchi Wu, 1983. "The Analytical Foundations of Adjustment Grid Methods," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 11(1), pages 11-29.
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