Merger simulations in EU merger control: what have we learned?

It has been 25 years since a merger simulation was first included in a European Commission (Commission) merger decision. Since then, simulations – submitted by both the Commission and merging parties – have featured in numerous cases. Although their use has declined since the late 2010s, no comprehensive review has yet examined the evidence these simulations provide. This paper attempts to fill that gap, with the aim of rekindling the debate around the role of simulations in EU merger control. We begin with a qualitative assessment of where the Commission and the merging parties most frequently diverged in their simulation approaches, such as model selection, assumptions, and input data. We then conduct a quantitative analysis, using a dataset of nearly 1,000 post-merger price predictions derived from simulations cited in Commission decisions. We find that simulations using econometrically estimated demand parameters generally predict lower post-merger price increases, though not universally. Contrary to common belief, we also show that the merging parties’ simulations do not consistently predict smaller price increases than those of the Commission. When econometric demand models are used, estimates from both sides tend to converge. We argue that this consistency offers a promising foundation for restoring confidence in the value of simulations in EU merger control.