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Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal

Author

Listed:
  • Steven Peterson

    (Virginia Commonwealth University)

  • Albert B. Flanagan

    (Williams Appraisers, Inc.)

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 B. Flanagan, 2009. "Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal," Journal of Real Estate Research, American Real Estate Society, vol. 31(2), pages 147-164.
    • Handle: RePEc:jre:issued:v:31:n:2:2009:p:147-164
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    References listed on IDEAS

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    Cited by:

    1. Mehmet Emin Tabar & Aziz Sisman & Yasemin Sisman, 2023. "A Real Estate Appraisal Model with Artificial Neural Networks and Fuzzy Logic: A Local Case Study of Samsun City," International Real Estate Review, Global Social Science Institute, vol. 26(4), pages 565-581.
    2. 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.
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    5. 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.
    6. Mahdieh Yazdani & Maziar Raissi, 2023. "Real Estate Property Valuation using Self-Supervised Vision Transformers," Papers 2302.00117, arXiv.org.
    7. Helga Flavia Tothăzan & Adela Deaconu, 2020. "Neuronal Network Artificial Model for Real Estate Appraisal: Logic, controversies, and utility for the Romanian context," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 1093-1100, December.
    8. Cankun Wei & Meichen Fu & Li Wang & Hanbing Yang & Feng Tang & Yuqing Xiong, 2022. "The Research Development of Hedonic Price Model-Based Real Estate Appraisal in the Era of Big Data," Land, MDPI, vol. 11(3), pages 1-30, February.
    9. Toorajipour, Reza & Sohrabpour, Vahid & Nazarpour, Ali & Oghazi, Pejvak & Fischl, Maria, 2021. "Artificial intelligence in supply chain management: A systematic literature review," Journal of Business Research, Elsevier, vol. 122(C), pages 502-517.
    10. Kuan-Lun Pan & Hsiao Jung Teng & Shih-Yuan Lin & Yu En Cheng, 2021. "An Empirical Method for Decomposing the Contributions of Land and Building Values to Housing Value," International Real Estate Review, Global Social Science Institute, vol. 24(3), pages 385-403.
    11. Vladimir Vargas-Calder'on & Jorge E. Camargo, 2020. "Towards robust and speculation-reduction real estate pricing models based on a data-driven strategy," Papers 2012.09115, arXiv.org.
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    13. Mahdieh Yazdani, 2021. "Machine Learning, Deep Learning, and Hedonic Methods for Real Estate Price Prediction," Papers 2110.07151, arXiv.org.
    14. William Cheung & Lewen Guo & Yuichiro Kawaguchi, 2021. "Automated valuation model for residential rental markets: evidence from Japan," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-34, December.
    15. Jasmina Ćetković & Slobodan Lakić & Marijana Lazarevska & Miloš Žarković & Saša Vujošević & Jelena Cvijović & Mladen Gogić, 2018. "Assessment of the Real Estate Market Value in the European Market by Artificial Neural Networks Application," Complexity, Hindawi, vol. 2018, pages 1-10, January.
    16. 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.
    17. Kristoffer B. Birkeland & Allan D. D'Silva & Roland Füss & Are Oust, 2021. "The Predictability of House Prices: "Human Against Machine"," International Real Estate Review, Global Social Science Institute, vol. 24(2), pages 139-183.
    18. Áron Horváth & Blanka Imre & Zoltán Sápi, 2016. "The International Practice of Statistical Property Valuation Methods and the Possibilities of Introducing Automated Valuation Models in Hungary," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(4), pages 45-64.
    19. Tien Foo Sing & Jesse Jingye Yang & Shi Ming Yu, 2022. "Boosted Tree Ensembles for Artificial Intelligence Based Automated Valuation Models (AI-AVM)," The Journal of Real Estate Finance and Economics, Springer, vol. 65(4), pages 649-674, November.
    20. Kirill Solovev & Nicolas Prollochs, 2021. "Integrating Floor Plans into Hedonic Models for Rent Price Appraisal," Papers 2102.08162, arXiv.org.
    21. Jose Torres-Pruñonosa & Pablo García-Estévez & Josep Maria Raya & Camilo Prado-Román, 2022. "How on Earth Did Spanish Banking Sell the Housing Stock?," SAGE Open, , vol. 12(1), pages 21582440221, March.
    22. Moreno-Izquierdo, Luis & Egorova, Galina & Peretó-Rovira, Alexandre & Más-Ferrando , Adrián, 2018. "Exploring the use of artificial intelligence in price maximisation in the tourism sector: its application in the case of Airbnb in the Valencian Community," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 42, pages 113-128.
    23. Jose Torres-Pruñonosa & Pablo García-Estévez & Camilo Prado-Román, 2021. "Artificial Neural Network, Quantile and Semi-Log Regression Modelling of Mass Appraisal in Housing," Mathematics, MDPI, vol. 9(7), pages 1-16, April.

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