As competition policy and antitrust rules around the world move away from structural considerations towards assessments that are more driven by competitive effects, it is important to understand the role that economic analysis plays in assessing the competitive impact of a specific transaction. When properly designed and executed, empirical analyses can help policymakers define the relevant market and quantify the competitive effects of a proposed merger or an allegedly anticompetitive business practice or conduct.

In this article, the authors discuss the basis of several standard routines of empirical analysis in competition policy economics. They describe the tests used in market definition analysis, including the hypothetical monopolist test (or SSNIP test—‘small but significant non-transitory increase in price’) to inform the determination of the relevant market, and the cross-price elasticity of demand methodology, to determine whether two products are likely to be in the same relevant market. They also explain how event studies, natural market experiments, surveys, and pricing studies are used to assess market definition and cite advantages of and examples for each approach. The remainder of the article explores quantitative methods that are used in competitive effects analysis. These techniques, such as price concentration studies, bidding analyses, simulation models, and estimation of damages often involve an explicit model of a counterfactual market situation, or a projection of future market prices and output. Competitive effects analysis can help determine if a prevailing state of competition is likely to deteriorate as a result of a merger or if prices are likely to rise or fall if two or more firms merge.

The authors note that an appropriately chosen empirical technique needs to fit the theoretical considerations of a particular case and make full use of the available data. The quantitative techniques defined in this article can help evaluate whether the conclusions of an empirical analysis are likely to be sensitive to small changes in underlying assumptions, which is an important consideration when analyzing and interpreting economic evidence.