The Impact of Competition Policy: What are the Known Unknowns?

Abstract

Evaluations of competition policy are increasingly common and typically establish that consumer bene.ts from detected cases easily outweigh the costs of competition authorities (CA). However, such assessments are often driven by data availability and only capture a small part of the total impact because they sidestep the di¢ cult issue of how to evaluate deterrence. Similarly, they ignore the fact that policy does not root out all anti-competitive cases. This paper suggests a broader framework for evaluation which encompasses these unobserved impacts. Calibration is difficult precisely because we cannot rely on empirical observations on cases which have been observed to make deductions about cases which have not (because they are deterred or undetected). It thereby confronts the classic sample selection problem which is endemic in all studies based on data from CA decisions. Drawing on insights from economic theory, it argues that selection bias is likely to be substantial because the unobserved cases could well be those which are most harmful. If so, the deterrence of anti-competitive mergers may have a much greater positive impact, but the effects of non-detected cartels may be more serious than is usually supposed. Evaluations of competition policy are increasingly common and typically establish that consumer bene…ts from detected cases easily outweigh the costs of competition authorities (CA). However, such assessments are often driven by data availability and only capture a small part of the total impact because they sidestep the di¢ cult issue of how to evaluate deterrence. Similarly, they ignore the fact that policy does not root out all anti-competitive cases. This paper suggests a broader framework for evaluation which encompasses these unobserved impacts. Calibration is di¢ cult precisely because we cannot rely on empirical observations on cases which have been observed to make deductions about cases which have not (because they are deterred or undetected). It thereby confronts the classic sample selection problem which is endemic in all studies based on data from CA decisions. Drawing on insights from economic theory, it argues that selection bias is likely to be substantial because the unobserved cases could well be those which are most harmful. If so, the deterrence of anti-competitive mergers may have a much greater positive impact, but the e¤ects of non-detected cartels may be more serious than is usually supposed.

Simulating Collusion: Challenging Conventional Estimation Methods

“…Becker et al (2018) combine a game-theoretic model with Monte Carlo (MC) simulations to measure the deterrent effect of cartel law enforcement. Davies and Ormosi (2013) and Davies et al (2018) use simulations to estimate a quantification of harm deterred by antitrust policies, taking into account potential sample selection bias. Based on Harrington and Chang (2009), Katsoulacos et al (2016) develop a framework for evaluating the effects of policy instruments on welfare, simulating different intervention variables and allowing for repeat offenders.…”

Competition Law Enforcement and Household Inequality in the United Kingdom

“…36 The deterrent effects of competition law have been examined extensively in the literature. 37 Taking account of factors such as selection bias (that undetected cartels are likely to be more harmful as are more anticompetitive mergers that are notified), Davies and Ormosi (2013) estimate that the direct effects of competition law enforcement could be multiplied by a factor of up to 30 for cartels and 17 for mergers. 38 Looking at the total impact of competition enforcement (including deterrent effects), Dierx et al (2017) estimate that EU competition law enforcement could have contributed up to 0.4 percent of GDP after 5 years and 0.8 percent over the long term.…”

“…Davies and Ormosi (2013) suggest a range of multiplying factors of between 6 and 17 for mergers and 17 and 30 for cartel decisions.39 This is supported to some extent by the findings in Competition and Markets Authority (2018c) that awareness of competition law is higher in medium/large businesses and that 53% of firms surveyed were aware that dominant firms are under a special responsibility not to allow their conduct to impair competition beyond the rules applicable to other companies.Downloaded from https://academic.oup.com/jcle/article/18/4/905/6604438 by ETH Zürich user on 19 January 2023…”

“…Davies and Ormosi (2013) observe the estimates used by competition authorities are typically derived using very conservative assumptions to avoid accusations of self-justification. Similarly, Dierx et al(2017) note that the values of these different parameters depend on the characteristics of the case and are a rather conservative reflection of the relevant literature.Downloaded from https://academic.oup.com/jcle/article/18/4/905/6604438 by ETH Zürich user on 19 January 2023…”

A Step Ahead: Competition Policy for Shared Prosperity and Inclusive Growth

“…The reason is that the observed sample of cartels detected may not be representative of the full population of cartels. Davies and Ormosi (2013) consider that this sample selection bias is likely to be substantial because the unobserved cases could well be those that are the most harmful. In particular, undetected cartels are likely to be more harmful than the detected ones, because the latter are less sustainable or more prone to whistle-blowers.…”