We study the determinants of common European merger policy over its first 25 years, from 1990 to 2014. Using a novel dataset at the level of the relevant antitrust markets and containing all relevant merger cases notified to the European Commission, we evaluate how consistently arguments related to structural market parameters – dominance, rising concentration, barriers to entry, and foreclosure – were applied over time and across different geographic market definitions. On average, linear probability models overestimate the effects of structural indicators. Using non-parametric machine learning techniques, we find that dominance is positively correlated with competitive concerns, especially in markets with a substantial increase in post-merger concentration and in complex mergers. Yet, its importance decreased following the 2004 merger policy reform. Competitive concerns are also correlated with rising concentration, especially if entry barriers and foreclosure are of concern. The impact of these structural indicators in explaining competitive concerns is independent of the geographic market definition and does not change over time.