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.
We are grateful to the three anonymous referees and the editor of the journal
for suggestions and comments that helped to improve the paper. We thank
seminar participants at the Technische Universit¨at Berlin, Fiona Stoddard,
and Verity Watson for helpful comments. The usual disclaimer applies.
- housing market
- machine learning