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Algorithm-Driven Hedonic Real Estate Pricing – An Explainable AI Approach

Author

Listed:
  • Tarasov Stanislav

    (Faculty of Economic Sciences, University of Warsaw, Długa 44/50, 00-241 Warsaw, Poland)

  • Dessoulavy-Śliwiński Bartłomiej

    (Department of Management and Information Technology, Faculty of Economic Sciences, University of Warsaw, Długa 44/50, 00-241 Warsaw, Poland)

Abstract

Data-driven machine learning algorithms triggered a fundamental change in hedonic real estate pricing. However, their adaptive nonparametric structure makes inference and out-ofsample prediction challenging. This study introduces an explainable approach to interpreting machine learning predictions, which has not been done before in the local market context. Specifically, Random Forest and Extreme Gradient Boosting models are developed for residential real estate price prediction in Warsaw in 2021 on 10,827 property transactions. Model-agnostic Explainable Artificial Intelligence (XAI) methods are then used to investigate the black box decision making. The results show the practicability of applying XAI frameworks in the real estate market context to decode the rationale behind data-driven algorithms. Information about the relationships between input variables is extracted in greater detail. Accurate, reliable and transparent real estate valuation support tools can offer substantial advantages to participants in the real estate market, including banks, insurers, pension and sovereign wealth funds, as well public authorities and private individuals.

Suggested Citation

  • Tarasov Stanislav & Dessoulavy-Śliwiński Bartłomiej, 2025. "Algorithm-Driven Hedonic Real Estate Pricing – An Explainable AI Approach," Real Estate Management and Valuation, Sciendo, vol. 33(1), pages 22-34.
    • Handle: RePEc:vrs:remava:v:33:y:2025:i:1:p:22-34:n:1003
    DOI: 10.2478/remav-2025-0003
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    References listed on IDEAS

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    More about this item

    Keywords

    residential real estate; machine learning; explainable artificial intelligence; mass appraisal; automated valuation models;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • R39 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other

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