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Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal

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Author Info

  • Steven Peterson

    ()
    (Virginia Commonwealth University)

  • Albert B. Flanagan

    ()
    (Williams Appraisers, Inc.)

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    Abstract

    Using a large sample of 46,467 residential properties spanning 1999-2005, we demonstrate using matched pairs that, relative to linear hedonic pricing models, artificial neural networks (ANN) generate significantly lower dollar pricing errors, have greater pricing precision out-of-sample, and extrapolate better from more volatile pricing environments. While a single layer ANN is functionally equivalent to OLS, multiple layered ANNs are capable of modeling complex nonlinearities. Moreover, because parameter estimation in ANN does not depend on the rank of the regressor matrix, ANN is better suited to hedonic models that typically utilize large numbers of dummy variables.

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    File URL: http://aux.zicklin.baruch.cuny.edu/jrer/papers/pdf/past/vol31n02/03.147_164.pdf
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    Bibliographic Info

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

    Volume (Year): 31 (2009)
    Issue (Month): 2 ()
    Pages: 147-164

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    Handle: RePEc:jre:issued:v:31:n:2:2009:p:147-164

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    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/

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    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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    References

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    1. Shiller, R.J. & Weiss, A.N., 1999. "Evaluating Real Estate Valuation Systems," Papers 983r, Yale - Economic Growth Center.
    2. Grether, D. M. & Mieszkowski, Peter, 1974. "Determinants of real estate values," Journal of Urban Economics, Elsevier, vol. 1(2), pages 127-145, April.
    3. Carlo Bagnoli & Halbert C. Smith, 1998. "The Theory of Fuzzy Logic and its Application to Real Estate Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 16(2), pages 169-200.
    4. 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.
    5. A. Quang Do & G. Grudnitski, 1993. "A Neural Network Analysis of the Effect of Age on Housing Values," Journal of Real Estate Research, American Real Estate Society, vol. 8(2), pages 253-264.
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    Cited by:
    1. Beatriz Larraz, 2011. "An Expert System for Online Residential Properties Valuation," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 69-82, April.
    2. Manuel Landajo & Celia Bilbao & Amelia Bilbao, 2012. "Nonparametric neural network modeling of hedonic prices in the housing market," Empirical Economics, Springer, vol. 42(3), pages 987-1009, June.
    3. Narula, Subhash C. & Wellington, John F. & Lewis, Stephen A., 2012. "Valuating residential real estate using parametric programming," European Journal of Operational Research, Elsevier, vol. 217(1), pages 120-128.

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