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Automated Valuation Services: A case study for Aberdeen in Scotland

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  • Rainer Schulz
  • Martin Wersing

Abstract

Automated valuation services (AVSs) offered by listings platforms predict market values based on property characteristics supplied by users. We investigate the implementation of such a service for the City of Aberdeen. We fit different market value models with machine learning methods and assess them in a rolling windows procedure that mimics an AVS setting. We also investigate the ease and robustness with which the models can be implemented. We discuss how prediction uncertainty can be measured and reported to users. If implemented in the future, such a service has the potential to improve the transparency of the local housing market.

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  • Rainer Schulz & Martin Wersing, 2021. "Automated Valuation Services: A case study for Aberdeen in Scotland," Journal of Property Research, Taylor & Francis Journals, vol. 38(2), pages 154-172, April.
    • Handle: RePEc:taf:jpropr:v:38:y:2021:i:2:p:154-172
    DOI: 10.1080/09599916.2020.1861066
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    Cited by:

    1. Jungsun Kim & Jaewoong Won & Hyeongsoon Kim & Joonghyeok Heo, 2021. "Machine-Learning-Based Prediction of Land Prices in Seoul, South Korea," Sustainability, MDPI, vol. 13(23), pages 1-14, November.

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