In an illiquid market like the real estate market, market values are not readily available. Transactions are scarce and do not always reflect market value. As a consequence, appraisal values play an important role to inform agents in decision making, financial reporting and for property taxes.

For example, appraisal values are used for property investment decisions and for providing mortgage loans. In a recent report De Nederlandsche Bank raises concerns about the quality and independency of appraisal values (Van der Molen and Nijskens, 2019).

The authors show that one third of all appraisal values exactly match the transaction price, and in almost 60% the appraisal value is higher than the transaction price. Automated valuation models (AVMs) are less prone to potential client influence. However, in order to be accepted by a broad audience, AVMs need to be transparent, robust, explainable and they need to provide reliable predictions. In this research the authors address these issues. They compare traditional hedonic price models to more advanced machine learning algorithms and analyse the accuracy of out-of-sample predictions and variable importance. The research is based on almost all residential transaction prices in the Netherlands in 2017.

Marc Francke, Ortec Finance en University of Amsterdam
Jeroen Beimer, Bouwinvest


Do you have questions about this article or an idea for another interesting analysis? Please contact Marc Francke using the details below.

Download your copy

By submitting my contact information, I confirm that I have read the Ortec Finance Privacy statement, which explains how Ortec Finance collects, processes and shares my personal data. I consent to my data being processed with Ortec Finance's Privacy Policy. Ortec Finance can optimize my experience with the Ortec Finance brand.

We respect your privacy

Related Insights

Cookies help us improve your website experience.
By using our website, you agree to our use of cookies.