The data-driven investigation of potential antitrust violations has found more and more applications in recent years, including through the use of machine learning. However, the availability of labelled data to train algorithms proves to be an obstacle. In a new working paper, Valentin Förster, Jürgen Fleiß, Dominik Kowald and Vicky Robertson explore the use of unsupervised machine learning to detect Resale Price Maintenance (RPM) in price data. Their paper is available here.
