Tuesday, September 16, 2014
Jennifer E. Sturiale, Georgetown University Law Center discusses Variety, Mergers, and Consumer Well-Being: Towards a Capability Approach to Merger Law.
ABSTRACT: Revisions incorporated into the Horizontal Merger Guidelines in 2010 claim that the DOJ and FTC consider anticompetitive effects to “variety” when evaluating mergers. The Guidelines do not, however, explain the methodology or tools that can and should be used to evaluate such effects. At the same time, there is an ongoing normative debate over antitrust’s consumer welfare standard, one strain of which is a disagreement over the meaning of the word “welfare.” This Article considers how variety effects could be evaluated — first, under normative welfare economics, and then under an alternative to welfare economics, the Capability Approach. The Capability Approach is a normative framework for evaluating individual well-being that stands in contrast to welfare economics. Rather than assess individual well-being in terms of an individual’s utility as determined from the individual’s subjective perspective, as welfare economics attempts to do, the Capability Approach evaluates individual well-being in terms of an individual’s capability to achieve the kind of life that the individual has reason to value. Ultimately, this is an assessment of what an individual is able to be and to do.
Philippe Chone, National Institute of Statistics and Economic Studies (INSEE) - Center for Research in Economics and Statistics (CREST) and Laurent Linnemer, National Institute of Statistics and Economic Studies (INSEE) - Laboratory of Industrial Economics; CESifo (Center for Economic Studies and Ifo Institute) address Nonlinear Pricing and Exclusion: I. Buyer Opportunism.
ABSTRACT: We study the exclusionary properties of nonlinear price-quantity schedules in an Aghion-Bolton style model with elastic demand and product differentiation. We distinguish three regimes depending on whether and how the price of the incumbent good is linked to the quantity purchased from the rival firm. We find that the supply of rival good is distorted downwards. Moreover, given the quantity supplied from the rival, the buyer may opportunistically purchase inefficiently many units from the incumbent to pocket quantity rebates. We show that the possibility for the buyer to dispose of unconsumed units attenuates the opportunism problem and limits the exclusionary effects of nonlinear pricing.
Arbitration and Competition Law: The Potential Role of Ireland in the Privatisation of Competition Law
Conor C. Talbot,
European University Institute - Department of Law (LAW); Trinity College (Dublin) - Department of Economics; European University Institute - Robert Schuman Centre for Advanced Studies (RSCAS)has written on Arbitration and Competition Law: The Potential Role of Ireland in the Privatisation of Competition Law.
ABSTRACT: This article examines the use of arbitration in competition law from Irish perspective, with a focus on the challenges faced by arbitrators operating in a jurisdiction where infringements of the competition rules can carry the weight of the criminal law and potentially lead to custodial sentences.
Monday, September 15, 2014
Trung H. Le, Banking Faculty - Banking Academy of Vietnam discusses Market concentration and competition in Vietnamese banking sector.
ABSTRACT: Vietnamese banking system has been playing a vital role in the development and economic growth since the economic renewal campaign namely “Doi Moi” in 1986. However, since the global financial crisis, financial and banking system has been under stress, exposing much weaknesses, severely affecting the whole economy. Additionally, the wave of financial liberalization raise questions about the competitiveness of Vietnamese commercial banks in the competition with the foreigners. The main purpose of this paper is to measure the market concentration using Hirschman-Herfindahl index (HHI) and test for the market competition in Vietnamese banking sector under Panzar – Rossse approach by an unbalanced panel data of 33 commercial banks for the period from 2004 to 2013. Vietnamese banking sector is found to be high-concentration although it is experiencing a decreasing trend. The test for market competition indicate a monopo! listic behavior of Vietnamese commercial banks. No surprising, the state-owned commercial banks and foreign banks are found to be superior in the competition with joint-stock commercial banks and domestic banks respectively. In addition, the foreign investment in banks seem to increase competitiveness of a commercial bank.
Is Subsidizing Companies in Difficulties an Optimal Policy? An Empirical Study on the Effectiveness of State Aid in the European Union
Nicole Nulsch, Halle Institute for Economic Research (IWH) asks Is Subsidizing Companies in Difficulties an Optimal Policy? An Empirical Study on the Effectiveness of State Aid in the European Union.
ABSTRACT: Even though state aid in order to rescue or restructure ailing companies is regularly granted by European governments, it is often controversially discussed. The aims for rescuing companies are manifold and vary from social, industrial and even political considerations. Well-known examples are Austrian Airlines (Austria) or MG Rover (Great Britain). Yet, this study aims to answer the question whether state aid is used effectively and whether the initial aim why aid has been paid has been reached, i.e. the survival of the company. By using data on rescued companies in the EU and applying a survival analysis, this paper investigates the survival rates of these companies up to 15 years after the aid has been paid. In addition, the results are compared to the survival rates of non-rescued companies which have also been in difficulties. The results suggest that despite the financial support, business failure is often only post-poned; best survival rates have firms with long-term restructuring, enterprises in Eastern Europe, smaller firms and mature companies. However, non-funded companies have an even higher ratio to go bankrupt.
Political antitrust has become more heated as the Treasury Department has sent a letter to the Chinese government regarding what it considers political antitrust enforcement. See here.
Of note, the article meantioned that
After July talks on the U.S.-China Strategic and Economic Dialogue, Treasury said China "recognized that the objective of competition policy is to promote consumer welfare and economic efficiency, rather than to promote individual competitors or industries, and that enforcement of its competition law should be fair, objective, transparent, and non-discriminatory."
A number of industry association reports (US Chamber of Commerce, USCBC, European Union Chamber of Commerce in China) have been critical of AML enforcement.
AML enforcement is very tricky. There is a combination of a relatively new law, three enforcement agencies (each with capacity constraints in terms of too few case handlers), a law that recognizes not merely consumer welfare and total welfare concerns but also industrial policy concerns, and a host of other issues. All the more reason for people to attend tomorrow's GCR Live 2nd Annual New York conference that will discuss "Antitrust Enforcement in China - what's next?" that includes a stellar group of panelists. I am moderating the panel.
a half-day CPD course organised by UCL's Centre for Law, Economics & Society
Thursday 29 October 2014 from 1 - 7.30pm
About this course:
Multi-sided platforms are businesses that act as intermediaries between several interdependent groups of customers. They are central many industries including payment systems, financial exchanges, advertising-supported media, much of online, and various kinds of marketplaces including shopping malls. Some of the largest IPOs in recent years have involved multisided platforms such as Facebook and, soon, Alibaba. They are also often at the center of debates concerning competition policy and sectoral regulation. Google and Uber are two that are making headlines in the European Union.
This course will cover the unique business models followed by multi-sided businesses; the economics of multi-sided platforms and the industries they anchor; the applications of competition policy to multi-sided platforms; a survey of key competition policy and regulator matters involving these platforms; and tools and techniques for competition policy analysis.
The course will include presentations from several executives of platform startups including Will Page, Chief Economist at Spotify, and Alain Falys, Founder and CEO, of Yoyo.
The course will consist of three segments:
- The Business and Economics of Multi-sided Platforms.
- Market Definition, Market Power, and Merger Analysis for Multi-sided Platforms
- Abuse of Dominance and Coordinated Practices for Multi-sided Platforms
The course will draw extensively on examples of multi-sided platform cases involving online businesses and payments.
About the teacher Professor David S. Evans has taught antitrust law and economics at the University of Chicago Law School (2006-present) where he is a Lecturer; University College London Faculty of Laws (2004-present) where he is Executive Director of the Jevons Institute for Competition Law and Economics and Visiting Professor; and Fordham Law School (1985-1995) where he was a Professor. He has BA, MA, and PhD degrees, all in economics, from the University of Chicago. He has written extensively on industrial organization including more than 150 articles and 8 books. His 2006 book, Invisible Engines, co-authored with Andrei Hagiu and Richard Schmalensee, was the Winner of the Business, Management & Accounting category in the 2006 Professional/Scholarly Publishing Annual Awards Competition presented by the Association of American Publishers, Inc. Many of his publications concern antitrust law and economics. Dr. Evans was one of the early contributors to the economics of multi-sided platforms. His work on that topic includes Catalyst Code published by Harvard Business School Press in 2007. His recent published work in multi-sided platforms involves platform governance, online attention markets, ignition strategies, and vertical restraints.He has served as an expert economist in a number of high profile antitrust and regulatory matters in the United States, European Union, and China. Dr. Evans is the Chairman of Global Economics Group, where he provides expert help on litigation and regulation matters, and Founder of Market Platform Dynamics, where he provides business and strategic advice.
Gaurab Aryal, University of Chicago and Maria F. Gabrielli, CONCIET and Universidad Nacional de Cuyo ask Is Collusion Proof Auction Expensive? Estimates from Highway Procurements.
ABSTRACT: Collusion in auctions affects both revenue and efficiency and are prevalent. Yet, sellers do not use collusion-proof auctions as often as they should. Why is that? We find that one reason for this could be the cost of implementing efficient collusion-proof auctions. We use California highway procurements data, to estimate the cost of implementing collusion-proof auction. Our estimates show that cost must increase by at least 10.8% to ensure efficient outcome. The cost can sometimes be as high as 48.8% (depending on the size of bidding-ring in the data).
Cedric Clastres (Universite Pierre-Mendes-France- Grenoble II - Universite Joseph Fourier - Grenoble I) and Haikel Khalfallah (Universite Pierre-Mendes-France- Grenoble II - Universite Joseph Fourier - Grenoble I) offer An analytical approach for elasticity of demand activation with demand response mechanisms.
ABSTRACT: The aim of this work is to demonstrate analytically under what conditions activating elasticity of demand of consumers could be beneficial for the social welfare. It has added to the literature on analyzing the use of price signals in eliciting demand response by an analytical approach. We develop so an analytical Nash model to quantify the effect of implementing demand response, via price signals, on social welfare and energy exchanges. A prior results show that the trade-off between producing locally and exporting energy depends on the opportunity cost of the energy and the global efficiency of the generation technology. Results are moreover impacted by the degree of integration between the countries. The novelty of this research is the demonstration of the existence of an optimal region of price signal for which demand response leads to increase the social welfare. This optimality region is negatively correlated to th! e degree of competitiveness of the generation technologies and to the market size of the system. We particularly notice that the value of un-served energy or energy reduction the producers could lose from such demand response program would limit the effectiveness of its implementation. This constraint is strengthened when energy exchanges between countries are limited. Finally, we demonstrate that when we only consider the impact in term of consumers' surplus, more aggressive DR could be adopted. The intensity of DR program is however negatively correlated to the degree of the elasticity of demand.
Friday, September 12, 2014
Tomoya Nakamura, Osaka University describes One-Leader and Multiple-Follower Stackelberg Games with Private Information.
ABSTRACT: This study analyzes one-leader and multiple-follower Stackelberg games with private information regarding demand uncertainty. In the equilibrium of the Stackelberg games, a leader's private information becomes public information among followers. This study demonstrates that the strategic relationship between the leader and each follower is determined by the weight on public information regarding a follower's estimation of demand uncertainty. If the weight is sufficiently low (high), then the relationship is a strategic substitute (complement), and the leader has a first-mover (dis)advantage, respectively. In the case of strategic complementarity, the leader can exit from a market. The threshold is determined by the intensity of Cournot competition among the followers.
The Spring/Summer 2014 issue of Competition Policy International presents a lively discussion regarding effective institutional designs for competition regimes. More than 100 jurisdictions around the globe now have competition laws. But despite this proliferation, there’s no consensus on the optimal structure for an authority. While differences across countries probably dictate that there is no one “best” design for a national competition authority, we can still hope for some general principles for those countries figuring out how to come up with the best design for their circumstances.
Christian Koenig, University of Bonn and Franziska Schramm, ZEI describe Exemptions for large-scale energy consumers under state aid scrutiny (Germany).
ABSTRACT: Over the last decade, successive German governments have introduced regimes favourable to the production and sale of energy from renewable sources. There is considerable uncertainty as to the legality of these regimes under EU state aid law.
Bronwyn H. Hall, University of California at Berkeley; University of Maastricht - Maastricht Economic Research Institute on Innovation and Technology (MERIT); National Bureau of Economic Research (NBER); Institute for Fiscal Studies (IFS); Christian Helmers, London School of Economics & Political Science (LSE) - Centre for Economic Performance (CEP); Georg Von Graevenitz, University of East Anglia in London; Center for Competition Policy; and Chiara Rosazza Bondibene, University of London - Centre for Economics & Finance undertake A Study of Patent Thickets.
ABSTRACT: This report analyses whether entry of UK enterprises into patenting in a technology area is affected by patent thickets in the technology area. The aim is to contribute to our understanding of the role of patent thickets as a barrier to entry into new technologies for UK enterprises, in particular small and medium sized enterprises (SMEs). The report consists of several parts: 1) A review of the literature on patent thickets, including the limited empirical evidence regarding effects of patent thickets on R&D investments and competition; 2) Discussion of the factors contributing to thicket formation and growth; 3) An empirical evaluation of the extent to which patent thickets appear to be barriers to entry in some technology areas.
Thursday, September 11, 2014
Peter Oliver, Institut d'Etudes Europeennes and Thomas Bombois, Belgian Constitutional Court address Competition and Fundamental Rights 2013 Survey.
ABSTRACT: This survey covers the case law from the Luxembourg and Strasbourg courts on fundamental rights and competition law, together with fundamental rights cases which do not directly concern competition law but are likely to have an impact on it. Arguably, the most novel developments relate to requests for access to documents submitted with a leniency application (Donau Chemie, Energie Baden-Württemberg and Netherlands v Commission) and the proper remedy for unreasonable delay, in particular Gascogne. Other issues have emerged as well including the standard and extent of judicial control of Commission decisions applying Articles 101 and 102 TFEU, and the General Court's unlimited jurisdiction under Article 261 TFEU in relation to fines.
Christopher Gedge, James W. Roberts and Andrew Sweeting theorize A Model of Dynamic Limit Pricing with an Application to the Airline Industry.
ABSTRACT: The one-shot nature of most theoretical models of strategic investment, especially those based on asymmetric information, limits our ability to test whether they can fit the data. We develop a dynamic version of the classic Milgrom and Roberts (1982) model of limit pricing, where a monopolist incumbent has incentives to repeatedly signal information about its costs to a potential entrant by setting prices below monopoly levels. The model has a unique Markov Perfect Bayesian Equilibrium under a standard form of refinement, and equilibrium strategies can be computed easily, making it well suited for empirical work. We provide reduced-form evidence that our model can explain why incumbent airlines cut prices when Southwest becomes a potential entrant into airport-pair route markets, and we also calibrate our model to show that it can generate the large price declines that are observed in the data.
Rune Stenbacka, Hanken School of Economics and Mihkel Tombak, University of Toronto explore Optimal Co-Payment Policy In Health Care: Competition, Ownership Structure And Quality Provision.
ABSTRACT: We analytically characterize the effects of ownership and competition in the health care industry on quality provision, market coverage and optimal co-payment policy. A private monopoly selects a lower quality than a public supplier, and the socially optimal co-payment rate with a private monopoly exceeds that with a public monopoly. We establish that the optimal co-payment policy is invariant to the introduction of private competition. Thus, market coverage is invariant to the introduction of competition, whereas all consumers with a higher willingness to pay for quality are better off with competition.
Do "Reverse Payment" Settlements of Brand-Generic Patent Disputes in the Pharmaceutical Industry Constitute an Anticompetitive Pay for Delay?
Keith M. Drake, Martha A. Starr and Thomas McGuire have an emperical paper on Do "Reverse Payment" Settlements of Brand-Generic Patent Disputes in the Pharmaceutical Industry Constitute an Anticompetitive Pay for Delay?
ABSTRACT: Brand and generic drug manufacturers frequently settle patent litigation on terms that include a payment to the generic manufacturer along with a specified date at which the generic would enter the market. The Federal Trade Commission contends that these agreements extend the brand’s market exclusivity and amount to anticompetitive divisions of the market. The parties involved defend the settlements as normal business agreements that reduce business risk associated with litigation. The anticompetitive hypothesis implies brand stock prices should rise with announcement of the settlement. We classify 68 brand-generic settlements from 1993 to the present into those with and without an indication of a “reverse payment” from the brand to the generic, and conduct an event study of the announcement of the patent settlements on the stock price of the brand. For settlements with an indication of a reverse payment, brand stock prices rise on average 6% at the announcement. A “control group” of brand-generic settlements without indication of a reverse payment had no significant effect on the brands’ stock prices. Our results support the hypothesis that settlements with a reverse payment increase the expected profits of the brand manufacturer and are anticompetitive.
Wednesday, September 10, 2014
Mario Mariniello, Brugel and Marco Antonielli, Brugel offer Antitrust risk in EU manufacturing: A sector-level ranking.
ABSTRACT: Based on a dataset of manufacturing sectors from five major European economies (France, Germany, Italy, Spain and the United Kingdom) between 2000 and 2011, we identify a number of key sector-level features that, according to established economic research, have a positive impact on the likelihood of collusion. Each feature is proxied by an â??Antitrust Risk Indicatorâ?? (ARI). We rank the sectors according to their ARI scores. At 2-digit level, sectors that appears more exposed to collusion risk are those that tend to score high in most of the ARIs: Tobacco, Pharmaceuticals, Beverages, Chemicals. The 4-digit analysis suggests higher anticompetitive risk in Tobacco products, Spirits, Sugar, Railway Locomotives and Aircraft (high concentration and fixed costs), Coating of Metals and Printing (low import penetration), Tobacco products, Meat products, Footwear and Clothing (high market stability), Plastic products and Spin! ning/Weaving of textiles (high symmetry of market leaders). We then rank sectors according to the distribution of antitrust intervention by the European Commission between 2000 and 2013, in terms of merger control and anti-cartel enforcement. Tobacco, Paper and paper products, Pharmaceuticals and Food products are the sectors for which a notified merger has a greater likelihood of being deemed problematic by the Commission. There has been a greater incidence of anti-cartel action in Chemicals, Tobacco, Beverages, Electric equipment and Rubber and plastic. Antitrust investigations are based on the identification of narrow product markets. The characteristics of these markets are not necessarily well represented by average measures at sector level. Nevertheless, a simple comparison exercise shows that the European Commissionâ??s interventions have been largely consistent with sector rankings based on market concentration Introduction The object of this paper is twofold: to p! rovide a broad descriptive analysis of the risk of collusive behaviour throughout Europe in the manufacturing sector; and to identify those manufacturing sectors in which the European Commission has been more active in the past in its capacity of antitrust authority. This paper is close in spirit to industry and market studies, although our target is wider and encompasses the whole manufacturing sector in Europe, as explained further below. Our methodology resembles Ilzkovitz et al (2008), in which the authors couple a variety of product market indicators to measures of antitrust enforcement to determine whether an economic sector is characterised by weak competition. In the manufacturing sector they identify Basic metals and Motor vehicles as the sectors in which competition issues are more likely to arise. Symeonidis (2003) asks in which United Kingdom manufacturing industries collusion is more likely, finding no clear link with industry concentration (industries where collusion had a higher incidence were Basic metals, Building materials an! d Electrical engineering). Yet Symeonidis's (2003) analysis is based on observed collusive agreements that were considered lawful during the period of observation1. Our aim instead is to investigate potential infringements of competition law that could be pursued by an antitrust authority. During our observation period, collusion is illegal and therefore participating to a cartel is risky: the inability to coordinate in an explicit and transparent manner between market players and the threat of antitrust intervention make collusion instable. We are looking after market characteristics that help counter-balancing those effects and make collusion more likely in this context. The exercise that we propose in this paper, ranking economic sectors according to their predisposition to collusion, has an intrinsic limitation. The antitrust definition of a market (our theoretical subject of study â?? referred to in this paper as 'antitrust market') is conventionally based on tests, s! uch as the SSNIP test2, that identify the boundaries of a market by me asuring the degree of competition that different products exert on each other. If two products are very good substitutes â?? such that a significant proportion of demand and/or of supply would shift to one product if the price of the other is changed - then the products are considered to belong to the same market. This often leads to markets the boundaries of which are much narrower than those captured by product classification at sector level. However, macroscopic analysis such as the one proposed in this paper, is necessarily based on sector data: that is, data that aggregate information from multiple markets that are grouped together for statistical purposes. In fact, we are only able to capture an imperfect link between antitrust markets and the observable average performance of the sectors they belong to. Previous research has been confronted with the same challenge (see, for example, Griffith et al, 2010, on the effect of the EU Single Market Programme on mark-ups and! productivity). To partially mitigate that problem, we focus on market characteristics that we presume could be shared by the majority of products within the same statistical sector. This would be the case if, for example, antitrust product markets within a certain sector share regulatory features (eg similar barriers to entry), production features (eg similar levels of economies of scale) or demand characteristics (eg a customer base which is largely the same). To rank sectors according to their predisposition to collusion we follow the common wisdom in economic literature concerning the role of marketâ??s structural features (see, for an exhaustive overview: Ivaldi et al, 2003, or Motta, 2004). The general intuition is that the more concentrated, stable and transparent markets are, the easier is for players to coordinate on a collusive price and stick to it without yielding to the temptation of undercutting the rivals and break the cartel agreement. On the basis of the a! vailable data (see Section 2 below), we are able to measure proxies an d account for the following factors: (1) market concentration; (2) likelihood of entry; (3) stability of demand and supply; (4) market symmetry3. The treatment and measurement of each factor is described in the next Section. In the second part of our analysis we look at antitrust intervention by the European Commission. We look specifically at merger investigations and cartel infringement decisions. Both types of competition policy interventions give insights about the treatment of collusion likelihood by a competition authority. Regarding merger control, a merger has a higher chance to be considered 'problematic' from a competition policy perspective if it occurs in an already malfunctioning market where concentration levels are high, likelihood of entry is low, and supply and demand are relatively inelastic. A crucial determinant of a merger decision is, moreover, whether a merger has 'coordinated effects' ie whether the merger will make future collusion more likely. Final! ly we propose and discuss a simple comparison exercise: the European Commissionâ??s antitrust action is matched with the ranking of manufacturing sectors according to their collusion risk. Gual and Mas (2011) have an approach broadly similar to ours. They focus on Commission antitrust investigations only (ie they do not look at merger decisions), between 1999 and 2004 and check whether the probability of dropping the investigation is lower when industry characteristics suggest a lower likelihood of antitrust infringement. They find positive and weakly significant links consistent with theoretical prediction. For example, higher industry concentration rates are positively correlated with the probability of antitrust sanctioning. It is important to stress that this exercise suffers from the fundamental limitation described above: that sector data does not necessarily convey information for antitrust product markets. Therefore, while the exercise can provide for an interestin! g consistency check between antitrust action and status of competition at sector level and deliver suggestions for follow-up inquiries, it should not in itself be used in a normative fashion to judge the quality of antitrust intervention. An ad-hoc case-by-case ex-post analysis should instead be performed for that purpose (see Neven and Zenger, 2008, for a good overview of the literature). The paper is organised as follows. We first provide an illustration of the Antitrust Risk Indicators. We then describe our data sample in Section 2. Section 3 reports the sectorsâ?? rankings and discusses the results. Section 4 concludes. 1. The Antitrust Risk Indicators Below we report and explain the construction of the Antitrust Risk Indicators (ARIs) used to rank sectorsâ?? predisposition to collusion. A good summary of the underlying economic theory can be found in Motta (2004). Note that the indicators are computed at European wide level (ie they are cross-country averages) and on a 10 years-wide time period (with two exceptions described below). We ! are in fact interested in capturing the probability of potential cartels with boundaries that are wider than national, to identify true 'European' issues4. Moreover the time period of observation has to be sufficiently long as anti-competitive behaviours are usually put in place for years (for example: the average duration of an international cartel is between 6 and 14 years â?? See Mariniello, 2013). We note that market structures are generally stable over time; in other words, to give an example: the average market performance within the tobacco sector during the period 2000 and 2011 is a good proxy of the performance of the tobacco sector at any point of time during that period. Again, this is the case if, despite changes prompted by regulatory intervention, sectors tend to preserve their key structural features over time, at least in relative terms if compared with other sectors of the economy. The literature reports consistent findings5. (1) Market concentration A hig! her degree of market concentration is associated with higher likelihoo d of collusion. It is easier to coordinate and reach a collusive agreement within a smaller group of players. Also, if concentration is high, deviation from a collusive equilibrium is less profitable: the remaining slice of the market a player would grab by undercutting rivals is smaller if compared to a market where many players are active. This means that cartels are generally more stable when markets are more concentrated. We use three measures to proxy the average level of market concentration within a sector: the average price-cost margin for the period 2000 â?? 2011, the industry concentration ratio for 2010 and the Herfindal-Hirschman Index (HHI) for 2010. Price-cost margins have been widely used in the literature to proxy the degree of market concentration (See Griffith et al, 2010), as the companiesâ?? ability to extract rents and increase the gap between marginal costs and prices is decreasing in the level of competition in the market. They are, however, imperfec! t indicators: margins may be high, for example, because companies are more efficient or because they benefit from economies of scale, but calculating exact firm-level marginal cost is an extremely difficult exercise affected by other limitations (see Altomonte et al, 2010, for an example of such an exercise). We resort to use sector-wide production value and average variable costs as proxy of marginal costs; that is: we use the sum of the costs of labour, capital and all intermediate inputs as in Griffith et al (2010)6. In order to accommodate for the limitations of price-cost margins measures, we complement that indicator with industry concentration ratios and HHI indexes, calculated respectively as the simple sum of companiesâ?? market shares and the sum of the square of companiesâ?? market shares. These are also widely used measures of concentration (see Ilzkovitz et al, 2007), even if they are possibly even more subject to the fundamental limitation that affect macro-! analysis as described above: market shares at sector level are not nec essarily a good proxy of market shares at market level. In our case, moreover, market shares are available only for the biggest 4 companies in the sector and only for year 2010. We construct the indicators accordingly: C4 is the sum of the market shares of the four biggest companies in the sector in 2010; HHI4 is the sum of the square of the market shares of the four biggest companies in the sector in 2010. (2) Entry Entry has a disruptive effect on collusive behaviour. The mere threat of entry makes collusion less sustainable: when effective entry is likely, incumbent players may find it difficult to maintain high prices in the market without risking sudden loss of customers. Moreover, a high firmsâ?? turnover implies that coordination is less likely: instability in the identity and in the number of counterparts make collusive agreements more difficult to reach. Sectors where entry is more likely should therefore ceteris paribus be associated with lower probability of coll! usion. Our dataset does not contain information that can directly help measuring the likelihood of entry; likewise, it does not contain information on the pattern of actual entries by new companies that occurred in the period of observation. The data report just the change in number of companies and do not disentangle entry from exit. Low growth rates may therefore mean low entry rates or high entry rates accompanied by equally high exit rates. The change in the number of companies cannot therefore be used to proxy entry. We nevertheless can exploit the information available in our dataset to measure proxies that provides indications on the degree of a sectorâ??s openness to outside competitive pressure. To do so, we build 2 indicators: (a) firmsâ?? size and (b) import penetration. Firmsâ?? size is computed as the average size of companies within the sector during the period of observation (2000-2011). Relatively bigger sizes imply the existence of economies of scale, po! ssibly due to higher fixed costs and barriers to entry. Bigger average size should therefore imply lower likelihood of entry7. Import penetration is the yearly average of sector imports divided by sector production. This indicator is again computed over the period 2000-2011. A high ratio of imports over total production suggests that the sector tends to have relatively lower barriers to entry to foreign competitors. Moreover, it is reasonable to assume that reaching a collusive agreement with exporters is comparatively more difficult: exporters, for example, tend to be exposed to different costs shocks. Therefore it would be more difficult for local producers to explain price changes by exporters and detect potential deviation from collusive outcomes that may not be justified by change in production costs. (3) Market stability Stable markets are more predisposed to collusion. Collusive agreements crucially rely on playersâ?? ability to capture other playersâ?? deviation from the agreed price. When markets are subject to frequent and unpredic! table demand or supply shocks, attributing a change in price to a deviation is more difficult, therefore collusion is less stable. We compute two indicators to capture marketsâ?? stability: (a) variance in market size and (b) variance in import penetration. Variance in market size is computed as the variance of the yearly growth rate of production values in nominal terms. Variance in import penetration is the variance of the yearly growth rate of the ratio of imports over total production. The two variables are calculated over the full period of observation 2000-2011. High variance levels are presumed to indicate lower market predictability and lower likelihood of collusion. (4) Market symmetry The last dimension of analysis is market symmetry. Symmetric markets where players hold similar market shares tend to be more predisposed to collusion. Symmetry aligns playersâ?? incentive to stick to a cartel agreement. Conversely, if a company is much smaller than the others, it ! may have a relatively higher incentive to deviate, undercut its rivals and enjoy all marketâ??s profits. To test for symmetry we compute an Asymmetry Indicator based on Giniâ??s coefficient8. In our case we employ it on the distribution of the production shares of the top four companies in each sector for year 2010. If the asymmetry indicator is 0, that indicates that the four observed companies have identical production shares ie the market is perfectly symmetric. When the indicator instead approaches 100 that meansthat there exists a huge gap between the market share held by the biggest company and the one held by the smaller ones9. 2. The Dataset Our dataset contains a number of widely-used data for European manufacturing sectors from 2000 to 2011 for 5 European countries: France, Germany, Italy, Spain and UK. The 5 economies together represent 71 percent of the EU GDP10, in 2011, while the manufacturing sector in the five countries observed represents on average 12.5 percent of a countryâ??s GDP11. The primary sources for data are Natio! nal Accounts, Structural Business Statistics and International Trade databases. The aggregate statistics were compiled by Euromonitor12. The market features variables contained in our database are: total production, value added, gross operating surplus, market size, imports, exports, production and number of firms by employment size, production value and production shares of up to five top companies (all monetary data is recorded in euro)13. Using Eurostat NACE 2-digit classification14, the manufacturing sector can be split in 22 categories: Food products, Tobacco, Textiles, Wearing apparel, Leather products, Wood and wood products, Paper and paper products, Reproduction of recorded media, Chemicals, Pharmaceuticals, Rubber and Plastics, Other non-metallic mineral products, Basic metals, Fabricated metal products, Computers and electronics, Electrical equipment, Machinery and equipment, Motor vehicles, Other transport equipment, Furniture, Other manufacturing15. The 4-digit! disaggregation results in 92 sub-categories. The below table provides an overview of the database with few key descriptive statistics relative to 2010 for 2-digit sectors aggregated across the five economies. As it can be noted the total manufacturing production for our database amounted to â?¬3.5 trillion, with the Food, Motor vehicles and Fabricated metal sectors topping the list in terms of production and value added. As for the demand-side, the five economies consumed â?¬3.9 trillion with the Food and Motor vehicles sectors again on the top 3 by market size, and Computers and electronics coming third. The latter sector is ranked first also in terms of imports. Noticeably, imports and exports are originally defined at country level and therefore these aggregates include intra-group trade. The smallest sectors are Tobacco, Electrical equipment and Wood16 by either production or value added. The highest numbers of companies are in the Fabricated metal and Food sectors, with more than 180 thousands firms. 3. Results 3.1 Sector ranking â?! ? Antitrust Risk Indicators Table 2 and Table 3 above report the ranking of all sectors according to each of the ARI indicators (table 2 reports ranking based on 2-digit aggregation data, table 3 on 4-digit). In terms of market concentration, there is a general consistency between the three indicators, price-cost margins, C4 and HHI4, particularly in pointing to the most concentrated sectors: Tobacco, Beverages and Pharmaceuticals. Reproduction of recorded media and Chemicals, Motor vehicles and Electrical equipment score high respectively in terms of price cost margins and HHI(4) and C4. Divergences between indicators are possibly due to differences in cost structures (this should be the case for Motor vehicles and Other transport equipment for example)17 or differences in the size of antitrust markets. For example, Reproduction of recorded media scores very low for HHI(4) and C4. That is possibly due to the fact that products in these sectors tend to be more heterogeneous! and therefore less substitutable to each other. Therefore, even if se veral players are active in the sector (hence market shares at sector level are low), each player can still enjoy a certain degree of market power (hence price-cost margins are high), because the products sold may not have immediate close substitutes, or be perceived as such by customers. The opposite holds for Electrical equipment and Basic metals: if price-margins are relatively low despite high market shares, that may be due to a higher degree of substitutability between products. Table 3 provides a more disaggregated insight by ranking 2-digit sectors according to the highest score reached by any of their 4-digit sub-sectors. No great difference is noted with the NACE-2 results. Tobacco, Pharmaceuticals and Beverages (Spirits and Beer) still rank high. Interestingly, Food climbs up the concentration ranking thanks to the low level of competition detected in the Sugar market. Other transport equipment (Locomotives and Aircrafts) scores high in terms of market share concen! tration. Concerning entry, we note that, consistently with intuition, the firm size indicator is highly correlated with concentration. Tobacco, Motor Vehicles, Pharmaceutical, Chemicals, Beverages, Electric equipment, Basic metals are in the upper half of the ranking. This is not surprising given the relevance of research and development or high fixed entry costs and economy of scale featuring most of the products manufactured in these sectors. The NACE-4 analysis confirms Sugar (Food category) as a potentially problematic market, together with Tobacco, Aircraft and Spacecraft (Motor Vehicles), Plastic (Chemicals). The other entry indicator we use, â??import penetrationâ??, scores low for sectors were production tends to have a more narrow geographic scope (Reproduction of recorded media and in particular at 4-digit level, Printing) or has a stronger local dimension (Tobacco, Fabricated/Coated Metals, Other Non-metalic/Cement, Beverages/Soft drinks), while import penetrat! ion is high where multinational companies tend to be more present: Com puter and electronics, Pharmaceuticals, Chemicals, Motor vehicles. In terms of market stability, Tobacco, Food, Beverages and Pharmaceutical are amongst the sectors where demand varied the least during the period of observation (beside Wearing apparel, a result driven by the stability of the Clothing sector, as the 4-digit analysis shows). Import penetration is stable the most in Rubber and plastics, Wearing apparel, Electrical equipment, Wood and wood products. The lack of overtime variability may be due to the relevance of products where demand is notoriously less elastic (Meat products, Clothing, Tobacco, Beer and Footwear, Clothing, Pulp, paper and paper board, Plastic products, respectively for market size and import penetration variance at 4-digit level). Finally, the least â??asymmetricâ?? sectors according to our Gini-indicator seem to be Rubber and plastic, Textile, Electrical equipment and Tobacco. 3.2 Sector ranking â?? European Commission Merger and Anti-Carte! l Decisions Table 4 above reports the ranking of manufacturing sectors on the basis of European Commissionâ??s merger and cartel investigations during the period 2000 - 2013.18 The database was assembled downloading the decisionsâ?? record from the Commissionâ??s website and allocating them to sectors according to the reported economic classification. If more than one sector was reported, all indicated sectors were compiled as affected by the decision. For merger investigations we collected three types of information: the number of mergers that were unconditionally cleared in â??first phaseâ?? ie after a preliminary inquiry usually requiring 1 month of investigation; the number of mergers that were cleared in first phase but did instead require the parties to commit to certain conditions; the number of mergers for which a deeper investigation (â??second phaseâ??, usually lasting approximately 4 months) was deemed necessary. We define as â??potentially problematicâ?! ? a merger that was deemed as such at the end of the first phase inves tigation by the European Commission either imposing conditions or requiring further scrutiny in second phase.19 The ratio between potentially problematic mergers and the total number of scrutinised cases is the likelihood indicator used to rank sectors. Sectors display a high heterogeneity in terms of incidence of merger control. The sector where merger scrutiny took place most often is Chemicals with an overall count of 259 decisions, while only 6 mergers were scrutinised in the Tobacco and the Leather sectors during the period of observation. Since most of mergers are cleared without conditions, the likelihood that a merger is deemed potentially problematic by the European Commission is on average low (approximately 11 percent for the manufacturing sector as a whole). The index however varies substantially across sectors. Sectors where the index scores higher are Paper and paper products (25.4 percent), Pharmaceuticals (25 percent), Chemicals (15.1 percent), Other manufact! uring (14.6 percent). At the other end, the risk of a finding of problematic merger by the European Commission is lower in Motor vehicles (1.9 percent), Wearing apparel (5.6 percent), Electric equipment (6.5 percent). Tobacco (50 percent) and Furniture and Leather (0 percent) are clearly outliers (these results are due to idiosyncratic factors and the small number of observations). As for hard-core cartels, the Commission took decisions concerning 16 of the 22 sectors during the period of analysis. Chemicals account for the majority of rulings, 27 out of 65. Sectors with no uncovered cartels are Leather, Wood, Recorded media, Other transport equipment, Furniture and Other Manufacturing. To rank the sectors, we weighed the number of cartels to the size of the market as a share of total production in manufacturing. In the resulting ranking the sectors where the incidence of anti-cartel action was stronger in the period of observation are Chemicals, Beverages, Electrical equip! ment and Other non-metallic mineral products. Tobacco scores high as w ell, but again this might as well be due to the very small size of the sector compared to the other sectors, since just one cartel in Tobacco was sanctioned by the EC during the period of observation. It is interesting to note that the likelihood that a merger is deemed problematic and the weighed incidence of anti-cartel enforcement are highly and significantly correlated: 51.5 percent (5 percent significance level). This provides comfort that economic sectorsâ?? features affecting the probability of collusion play a role in determining the outcome of merger decisions. 3.3 Sector ranking - comparative exercise We now proceed with an illustrative comparative exercise. Figure 1 below attributes colours to sectors according to their performance with respect to the different computed indicators. The idea is to give a graphical glimpse of the consistency between Antitrust Risk Indicators and the action of the European Commission. As explained above, this exercise is useful to c! heck whether antitrust intervention is more frequent where it is expected to according to from a macro-economic perspective. It is important to keep in mind, though, that this exercise cannot provide indications as regards the quality of antitrust intervention, given the fact that sector data are not disaggregated enough to capture the boundaries of product markets as defined in the course of antitrust investigations. The coloured squares in figure 1 reflect the ranking of the sectors ordered according to their anticompetitive risk or the intensity of antitrust action: red corresponds to the seven sectors at the top, green to the seven sectors at the bottom, and yellow to the eight sectors in the middle. Red sectors in terms of â??problematic merger riskâ?? are, as described above: Tobacco, Pharmaceuticals, Chemical, Food and Paper; in terms of risk of cartel conviction, red sectors are: Tobacco, Beverages, Other non-metallic, Chemicals, Electric equipment, Rubber and pla! stic, Wearing apparel. Figure 1 suggests a significant degree of consi stency between European Commissionâ??s action both in terms of merger control and anti-cartel enforcement and ARIs related to market concentration and firmâ??s average size (simple correlation analysis point to significant correlation coefficients between 45 percent and 75 percent). A much lower degree of consistency is observed as regards the other ARIs and correlation results are all not statistically significant. The variance of market size (a negative proxy of market stability) is however broadly consistent with merger decisions for what concerns negative decisions ie: sectors such as Tobacco, Food products, Pharmaceuticals, Paper and paper products are ranked top both in terms of lack of market variance and of probability of negative merger decision. Cartels discovery seems also overall consistent in the top ranking for what concern import penetration (Tobacco, Other non-metallic mineral products and Beverages), variance of market size (Wearing apparel, Tobacco and Be! verages), variance of import penetration and market symmetry (Rubber and plastic, Wearing apparel, Electrical equipment and Other non-metallic mineral products). 4. Conclusions In this paper we have analysed features of European manufacturing sectors. We ranked sectors according to their performance based on indicators that economic wisdom suggests positively affect the likelihood of collusive behaviour by market players. At 2-digit level, sectors that appear more exposed to collusion risk are Tobacco, Pharmaceuticals, Beverages, Chemicals. The 4-digit analysis suggests higher anticompetitive risk in Tobacco products, Spirits, Sugar, Railway Locomotives and Aircrafts (high concentration and fixed costs), Coating of Metals and Printing (low import penetration), Tobacco products, Meat products, Footwear and Clothing (high market stability), Plastic products and Spinning/Weaving of textiles (high symmetry of market leaders). We also have ranked sectors according to the distrib! ution of Europeanâ??s Commissionâ??s antitrust intervention between 2000 and 2013 in terms of merger control and anti-cartel enforcement. Tobacco, Paper and paper products, Pharmaceuticals, Food products, are the sectors in which a notified merger has a greater likelihood of being deemed problematic by the Commission. The incidence of anti-cartel action has been higher in Chemicals, Tobacco, Beverages, Electric equipment and Rubber and plastic. We then checked the consistency of the European Commissionâ??s action with the prediction of economic theory based on sector data, bearing in mind that sector data cannot provide for indications on the quality of antitrust intervention given the fact that antitrust investigations are based on very narrow product market definitions. The comparison exercise suggests that, by and large, both merger control and anti-cartel action have been focusing on sectors displaying a higher level of market concentrations and economic rents or economy of scale. This paper has a descriptive nature and should be taken ! as a starting point for a deeper reflection on the choice of appropriate instruments to foster competition in European manufacturing sectors and the definition of intervention priorities. Without appropriate regulatory intervention, ex-ante monitoring by the antitrust authority is warranted. The action of the European Commission is sometimes considered to be too much 'case-driven'. Cartels are discovered through whistle-blowers, abuse of dominance or anti-competitive agreementsâ?? investigations are prompted by complaints. Because of such an approach, the restoration of normal competitive conditions that antitrust intervention is supposed to bring comes often with a significant delay with respect to the starting of the infringement. Uncovered cartelsâ?? duration, for example, fluctuates between 6 to 14 years (see Mariniello, 2013) from their commencement. During that time, cartels affect the economy through a higher burden on customers and ultimately on consumers. It woul! d thus be more efficient to anticipate the breaking down of cartels by investing resources in uncovering cartels to monitor markets in which infringements are more likely. The European Commission already has the tools to perform such a job through so-called 'sector inquiries'; an appropriate use of those tools in the identified sectors could yield significant social benefit. *** 1 Symeonidis (2003) uses agreements between competitors that were formally registered in compliance with UK Restrictive Trade Practice Act of 1956 as indication of an industryâ??s propensity to collusion; those agreements were at the time considered lawful. 2 See Amelio and Donath, 2009. 3 There are other factors which may be relevant to explain the likelihood of collusion in a certain market: for example, the existence of cross-ownership links between players or the frequency of their multi-market contacts. However, to our knowledge those factors are not available at sector level and are therefore excluded from our analysis. 4 We presume that the average marketsâ?? ! performance across the 5 countries reported in our dataset is a good approximation of the average performance of a cross-border market within the European Union. For the sake of illustration, consider the following example: we assume that averaging out the concentration ratio within the tobacco sector in UK, France, Germany, Italy and Spain yields a good approximation of the average concentration ratio of a market within the tobacco sector that has an international dimension (that is: it is not confined to just one European country and therefore falls in the competence of the European Commission). The validity of this presumption crucially depends on the degree of commonality that sectors have across countries in Europe. If the tobacco sector is very open to competition in UK while little competition in the same sector occurs in Italy, then the cross-country average may bear little indication as to the level of competition of a hypothetical tobacco market affecting Italy an! d UK. Instead, if cross-country variability is limited, this would sug gest that sectors have intrinsic characteristics that, despite idiosyncratic country characteristics (such as domestic regulatory policy) are conducive to similar market structures. For example: a production process typically implemented in a certain sector may give raise to sector-specific economies of scale, resulting in more concentrated markets. Strong and highly significant pairwise correlations between EU-wide and national indicators in our dataset support such presumption. Confirmations are also found in the empirical literature. Hollis (2003) for example finds that concentration ratios in 82 sectors are very similar across five European economies (Belgium, France, Germany, Italy and the UK), the US and Japan. 5 Veugelers (2004) analyses 67 manufacturing sectors in the EU15, finding that concentration ratios tend to be quite stable over time. Persistency checks ran on our database point to strong and highly significant cross-year correlations for price-cost margins, i! mport penetration and firm size. 6 We implement Griffithâ??s methodology except that we do not subtract for the capital costs because of data availability. 7 Alternative measures could be used to proxy entry (such as â??businessâ?? churn rateâ?? ie the sum of firmsâ?? birth and date rate) using Eurostat and OECD datasets. However, we believe that using average firm size as an indication of barriers to entry is a better option. First, because the data on firm size are reported at a higher level of disaggregation (up to 4-digit in our dataset, while businessâ?? churn rate is limited to 2-digit in the Eurostat/OECD dataset). Second, because the number of companies that enter or exit a sector is less informative about the disruptive power that those firms can exert on potential collusive agreements. A high number of small firms entering small markets within a sector affect positively the sectorâ??s businessâ?? churn rate, but this is unlikely to represent a threat to co! llusive agreements between bigger companies in wider markets. An exten ded discussion on alternative indicators to measure entry likelihood is reported in the Appendix. 8 The Gini index expresses inequality among values of a frequency distribution and ranges from 0 (complete equality) to 100 (extreme inequality). 9 Formally, we compute the Gini index as follows: Index = 1- (7*x4 + 5*x3 + 3*x2 + x1)/4; where x1 is the production share of the top company normalized to the production share of the four companies (or concentration ratio). 10 Source: Eurostat. 11 Source: The World Bank. 12 Euromonitor International (link) is a research and data company that collects and aggregate data at sector level from official sources as well as through market research. The data obtained through market research in our dataset consists of production value and production shares for the year 2010 of up to five top companies for all manufacturing sectors in the 5 target economies for our analysis. 13 Total production is the total revenue of all locally-registered com! panies, excluding taxes and subsidies on products like VAT; valued added equals total production minus intermediate consumption; the gross operating surplus equals value added minus labour costs and taxes less subsidies on production and therefore includes the remuneration of equity and the depreciation of capital; market size consists of the value of all goods and services sold, either from local or foreign producers and recorded at purchaser prices; imports consist of the value of goods delivered at the frontier and consumed in the country; exports consist of the value of goods shipped out of the country, excluding re-exports; the number of firms is made up by all locally-registered companies, including 0 employees enterprises and single-employed; production values and shares of top companies refer to the revenues made by companies from industry-specific products. 14 http://epp.eurostat.ec.europa.eu/portal/page/portal/nace_rev2/introduction 15 Two 2-digit sectors â?? Cok! e and refined petroleum products, and Repair and installation of machi nery and equipment â?? are left out of our analysis. 16 The great difference between market size and production for the Tobacco sector is given by secondary production, i.e. production of Tobacco products made by companies falling in other categories. 17 Profit margins are calculated with respect to estimation of marginal costs that includes intermediate goods and services. As explained above, this is a standard methodology in the literature, although alternative measures could rely on labour costs only â?? depending on what is considered a better approximation of total marginal costs. The methodology used in this paper therefore tends to bias downwards profit margins of sectors that rely heavily on intermediate goods and services, such as motor vehicles or other transport equipment. 18 Data were retrieved from the website of the European Commissionâ??s Directorate-General of Competition through the case search tool: link. 19 We opted for this definition in order to guara! ntee the maximum degree of statistical compatibility between merger decisions, since the ones used for the indicators are taken all at the end of a first phase investigation. Alternative definitions could also be possible. For example it could be possible to further segment mergers that were investigated in â??second phaseâ?? in mergers cleared with conditions, mergers cleared with no conditions and blocked mergers. A problematic merger could then be defined as a merger for which conditions were imposed at the end of either first or second phase investigation or a blocked merger. However, this would have implied mixing decisions taken after different administrative processes and with different depth of scrutiny. It should be said in any case that the ranking of sectors is not affected by the choice between the two different definitions. 20 According to the Eurostat definition, â??the enterprise is the smallest combination of legal units that is an organisational unit pro! ducing goods or services, which benefits from a certain degree of auto nomy in decision-making, especially for the allocation of its current resourcesâ??. Births and deaths account for the creation or dissolution of entreprise units, thus excluding mergers, break-ups or restructuring of a set of enterprises. REFERENCES Altomonte, C., Nicolini, M., Rungi, A., and Ogliari, L. 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Evidence from the UK', The Journal of Industrial Economics No. 51(1): 45-74 Veugelers, R., Davies, S., De! Voldere, I., Egger, P., Pfaffermayr, M., Reynaerts, J., Rommens, K., Rondi, L., Vannoni, D., Benfratello, L., and Sleuwaegen, L. (2002) 'Determinants of industrial concentration, market integration and efficiency in the European Union', chapter 3 in Dierx, A; Ilzkovitz, F. and K. Sekkat (eds) European Integration and the functioning of product markets, European Economy, Special Report Number 2, EC, DG ECFIN: 103-212 Appendix 1 Alternative ways to measure likelihood of entry In this paper we have used firm size as an indication of entry costs. Firms in sectors with higher barriers to entry are expected on average to be bigger in size. Another way to proxy likelihood of entry consists in measuring the actual number of enterprise births and deaths using the Business Demography datasets of Eurostat and the OECD20. A summary indicator for firms' turnover is the business churn, obtained as the sum of the birth rate and the death rate over the number of active enterprises! in a given year. The higher is the churn rate, the easier is for firm s to enter or exit a sector. Table A below reports the indicator used in this paper, firm size, and business churn in two separate columns at two-digits NACE 2. As it can be noted, the sectoral disaggregation of the two indicators differs. In particular, the Eurostat Business Demography/OECD dataset provides data at a more aggregated level than the level of analysis used in this paper. This makes the comparison between the two indicators difficult as sectors included in the same group in the Business Demography dataset may have very heterogeneous firms' size. For example, the Tobacco sector has the highest average firm size but Tobacco is aggregated with Food and Beverages in Eurostat and OECD datasets, which have average firm size about 10 times smaller. A rough comparison yields mixed results. Sectors with the highest business churn (ie Textiles, Wearing apparel, and Leather products) have very low firm sizes â?? consistently with the approach adopted in our analysis. ! However, sectors with higher firm sizes (eg Motor vehicles and Transport Equipment) also display relatively high churn rates. A possible explanation for this divergence is that high entry and exit rates may be due to high flows of small companies in narrow markets within a sector. If a high number of small companies enter or exit small markets in a sector, this significantly increases the sector's reported average churn rate. However, the disruptive effect on collusion brought about by these companies can be very limited, given their small size. For that reason, we believe that using firm size is a better measure to indicate the exposure of the sector to external competition for the purposes of the analysis reported in this paper. Another way to measure barriers to entry is to use sector capital and R&D intensity as in Gual and Mas (2011) and Symeonidis (2003). A high capital intensity, as measured by investment in tangible goods over value added, might imply! that firms need to make expensive investments in order to operate at an efficient scale. Similarly, a high R&D intensity, as measures by R&D spending over value added, may point to high costs incurred to differentiate or improve their products. Thus, capital and R&D costs may represent fixed or sunk costs that reduce likelihood of entry. The two indicators are also displayed in Table A. Again testing the similarity between these alternative measures and firm size is difficult due to the different level of aggregation of the sectors. Nevertheless, a rough comparison suggests a higher degree of consistency compared to what observed in the case of business churn rate. Excluding Tobacco, the correlations between capital intensity and firm size and between R&D intensity and firm size are respectively as high as 44 percent and 72 percent. Taking the sum of the capital and the R&D intensity the correlation with firm size reaches 89 percent.