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Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal

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  • Steven Peterson
  • Albert Flanagan

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.

Suggested Citation

  • Steven Peterson & Albert Flanagan, 2009. "Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal," Journal of Real Estate Research, Taylor & Francis Journals, vol. 31(2), pages 147-164, January.
    • Handle: RePEc:taf:rjerxx:v:31:y:2009:i:2:p:147-164
    DOI: 10.1080/10835547.2009.12091245
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    Cited by:

    1. Marc Francke & Alex van de Minne, 2024. "Combining machine learning and econometrics: Application to commercial real estate prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 52(5), pages 1308-1339, September.
    2. Silviu-IonuÈ› BÄ‚BÈšAN, 2024. "AUTOMATED EVALUATION MODELS in real estate market: A comparative analysis between linear regression and XGBoost," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(26), pages 1-3.
    3. Reza Amindarbari & Perver Baran & Ross K. Meentemeyer, 2023. "Spatially disaggregated simulation of interactions between home prices and land-use change," Environment and Planning B, , vol. 50(7), pages 1879-1897, September.
    4. Jose A. Rodriguez-Serrano, 2025. "Prototype-based learning for real estate valuation: a machine learning model that explains prices," Annals of Operations Research, Springer, vol. 344(1), pages 287-311, January.

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