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Apartment Rent Prediction Using Spatial Modeling

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Author Info

  • James Valente

    ()
    (SSR Realty Advisers, Inc.)

  • ShanShan Wu

    (Department of Statistics, University of Connecticut)

  • Alan Gelfand

    (Institute for Statistics and Decision Sciences, Duke University)

  • C.F. Sirmans

    (Director, Center for Real Estate and Urban Economic Studies, University of Connecticut)

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    Abstract

    This paper provides a new model to explain local variation in apartment rents by introducing the notion of a spatial process. This model differs from those in the literature by explicitly specifying spatial association between pairs of locations as a function of distance between them. Data on apartment rents for the eight markets are used to illustrate the spatial model. Results indicate signi?cant prediction improvement over traditional hedonic rent models that only include indicator variables to capture spatial effects.

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    File URL: http://aux.zicklin.baruch.cuny.edu/jrer/papers/pdf/past/vol27n01/05.105_136.pdf
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    Bibliographic Info

    Article provided by American Real Estate Society in its journal journal of Real Estate Research.

    Volume (Year): 27 (2005)
    Issue (Month): 1 ()
    Pages: 105-136

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    Handle: RePEc:jre:issued:v:27:n:1:2005:p:105-136

    Contact details of provider:
    Postal: American Real Estate Society Clemson University School of Business & Behavioral Science Department of Finance 401 Sirrine Hall Clemson, SC 29634-1323
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    Web page: http://www.aresnet.org/

    Order Information:
    Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323
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    Web: http://aux.zicklin.baruch.cuny.edu/jrer/about/get.htm

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    Cited by:
    1. Marcus Allen & Ronald Rutherford & Thomas Thomson, 2009. "Residential Asking Rents and Time on the Market," The Journal of Real Estate Finance and Economics, Springer, vol. 38(4), pages 351-365, May.
    2. Olivier Parent & Rainer Hofe, 2013. "Understanding the impact of trails on residential property values in the presence of spatial dependence," The Annals of Regional Science, Springer, vol. 51(2), pages 355-375, October.
    3. Bing Zhu & Roland Füss & Nico Rottke, 2011. "The Predictive Power of Anisotropic Spatial Correlation Modeling in Housing Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 42(4), pages 542-565, May.
    4. Morito Tsutsumi & Hajime Seya, 2009. "Hedonic approaches based on spatial econometrics and spatial statistics: application to evaluation of project benefits," Journal of Geographical Systems, Springer, vol. 11(4), pages 357-380, December.
    5. Beth Wilson & James Frew, 2007. "Apartment Rents and Locations in Portland, Oregon: 1992 – 2002," Journal of Real Estate Research, American Real Estate Society, vol. 29(2), pages 201-218.

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