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Neuronal Network Artificial Model for Real Estate Appraisal: Logic, controversies, and utility for the Romanian context

Author

Listed:
  • Helga Flavia Tothăzan

    (“Babes-Bolyai†University of Cluj-Napoca)

  • Adela Deaconu

    (“Babes-Bolyai†University of Cluj-Napoca)

Abstract

The requirement for statistical techniques in the appraisal process is far-reaching for every country. Market price accuracy for properties is mean in economics filed, mass appraisal, and for all users of appraisals reports. Studies were developing for econometric models that can be applied in real estate issues. Literature dominates for the USA and UK and stands a need to be tested for emerging (developing) markets. The paper aims to give some hints of the logic, the problems, benefits, and a guide of the ANN (Artificial neuronal network) technique. In the study, much practical information for ANN's representing an encouragement and a tool for other emerging countries to append the technique. We conclude that ANN is critical to be applied in property valuation for emerging countries in the global environment.

Suggested Citation

  • 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.
    • Handle: RePEc:ovi:oviste:v:xx:y:2020:i:2:p:1093-1100
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    References listed on IDEAS

    as
    1. Allan Din & Martin Hoesli & Andre Bender, 2001. "Environmental Variables and Real Estate Prices," Urban Studies, Urban Studies Journal Limited, vol. 38(11), pages 1989-2000, October.
    2. 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.
    3. W.J. McCluskey & M. McCord & P.T. Davis & M. Haran & D. McIlhatton, 2013. "Prediction accuracy in mass appraisal: a comparison of modern approaches," Journal of Property Research, Taylor & Francis Journals, vol. 30(4), pages 239-265, December.
    4. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Artificial Neural Network model; market value; appraisal; emerging countries; accuracy;
    All these keywords.

    JEL classification:

    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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