MERGER REVIEWS AND POST-MERGER EVALUATION WITH DEA

Abstract

Merger reviews is a core business for competition authorities (CA). In this paper I employ linear programming methods to evaluate potential efficiency gains following a merger, against the background of market-side effects (e.g. price increases), which are usually relevant in a CA’s merger assessment. Furthermore, I use an additive model to show that there are circumstances where a merger cannot induce technical efficiency gains, thus limiting the scope for potential welfare gains. I argue that when there is no potential for technical efficiency gains, the CA should consider an outright ban of the proposed merger, because there will be little room for positive effects on market competition and respectively, on consumer welfare.