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Part V Advancing a Research Agenda for the Agencies and Academics, 19 Understanding and Assessing Data-Driven Efficiencies Claims

Maurice E. Stucke, Allen P. Grunes

From: Big Data and Competition Policy

Maurice Stucke, Allen Grunes

From: Oxford Competition Law (http://oxcat.ouplaw.com). (c) Oxford University Press, 2015. All Rights Reserved. Subscriber: null; date: 07 August 2020

Subject(s):
Barriers to entry — Market power — Rights — Internet — Technology — National merger control

(p. 302) 19  Understanding and Assessing Data-Driven Efficiencies Claims

19.01  We have mainly addressed the potential anticompetitive risks of data-driven mergers and data-opolies. Data-driven mergers, however, can yield significant pro-competitive efficiencies, such as improving products, services, and internal business processes. Nor is a dominant firm penalized for its growth or development, which is the consequence of a ‘superior product, business acumen, or historic accident’.1 As Big Data can be welfare enhancing, another signpost of progress is when competition officials account the myriad data-driven efficiencies.

19.02  No company, as of early 2016, has prevailed against a merger challenge by a US competition authority on an efficiency defence.2 Nonetheless the US and EU authorities do consider merger-specific efficiencies in deciding whether to challenge a merger. In closing statements, for example, the US Department of Justice (DOJ) highlighted the likely efficiencies from mergers in the highly concentrated telephone, satellite radio, and airline industries.3

19.03  As companies undertake data-driven business strategies, one might expect them to raise data-driven efficiencies. The four ‘V’s of data and data-driven network effects (p. 303) can be characterized as entry barriers or efficiencies. An enforcement agency may characterize the need to continually update a significant volume and variety of data as an entry barrier. The merging parties, on the other hand, may characterize their combining the volume and variety of their data, and increasing the velocity in processing the data, as a procompetitive efficiency, enabling them to deliver value to consumers, such as better quality products. We will evaluate several potential data-driven efficiencies, using the three criteria employed in the US and EU, namely whether the efficiencies benefit consumers, are merger-specific, and are verifiable.4

A.  Efficiencies Benefit Consumers

19.04  The merging parties must demonstrate that their claimed efficiencies would benefit customers.5 ‘The relevant benchmark in assessing efficiency claims is that consumers will not be worse off as a result of the merger.’6 Data-driven mergers may yield significant internal operational efficiencies. But the competition law ‘does not excuse mergers that lessen competition or create monopolies simply because the merged entity can improve its operations’.7 Customers must ultimately benefit for the efficiencies to count (at least in assessing the merger).

19.05  Nor can the data-driven efficiency be achieved by degrading non-price competition such as quality or privacy protection. Many online companies, like Facebook and Google, rely on advertising for nearly all their revenue. To track individuals, harvest their data, profile them, and target them with behavioural ads, they often do not elevate users’ privacy interests. (Indeed, as we saw, some tech companies in their statements to investors view privacy-protecting technologies as a threat to their business.) In acquiring a company with a subscription-based model that offers greater privacy, they may claim as a data-driven efficiency that prices of the acquired product will decline post-merger. The emerging consensus is that privacy protection is a parameter of non-price quality competition. Thus the competition agency would likely reject this trade-off, where the merging parties would lower the price (p. 304) at the expense of privacy protection. Cognizable efficiencies ‘do not arise from anticompetitive reductions in … service’ and ‘purported efficiency claims based on lower prices can be undermined if they rest on reductions in product quality or variety that customers value’.8

19.06  The European General Court in Ryanair rejected a similar trade-off. Ryanair, to put it charitably (for those who have never experienced their flights), is a no-frills airline. In seeking to acquire rival Aer Lingus, Ryanair cited as an efficiency the likely reductions in Aer Lingus’s costs. But Ryanair failed to demonstrate that ‘it could reduce Aer Lingus’s costs without offsetting reductions in that undertaking’s service quality’.9 Thus the European Commission ‘was entitled to call into question the verifiability of the efficiency claims in the light of the data provided by Ryanair on that point’.10

19.07  A tougher issue involves mergers in industries with data-driven network effects. The merger can tip the market in the parties’ favour and thus create a monopoly. On the other hand, the merger could benefit consumers (for example, more apps could be developed for the platform). Generally the stronger the presumption of harm, given the increase in concentration and other evidence of anticompetitive harm, the greater the showing by the merging parties that the projected ‘merger-specific’ cost savings are substantial enough to overcome the presumption of harm.11 If the data-driven merger may create a monopoly (or significantly help a dominant firm maintain its monopoly), efficiencies ‘almost never justify a merger to monopoly or near-monopoly’.12 If post-merger, the firm’s market power falls short of a near-monopoly, the verifiable merger-specific efficiencies must be extraordinary.13

19.08  Economic evidence—for example, an analysis of how the merger lowers costs and showing why they would likely be passed on to customers—often plays a key role. But customer views on efficiencies, particularly by knowledgeable customers, can also influence the competition authorities. Customer support of the merger (p. 305) and efficiencies reduces the likelihood of the agency challenging the merger, and increases the likelihood of the agency recognizing the merger-specific efficiency.

19.09  That was the case in the Microsoft/Yahoo! joint venture, which occurred, as we saw in Chapter 12, in a highly concentrated industry with high entry barriers and several data-driven network effects. But market participants supported the transaction, the European Commission and DOJ found, based in part on the data-driven efficiency, namely how Microsoft’s search algorithms, benefitting from the scale of data, could provide better quality search results.14 Almost all the advertisers responding to the Commission’s market investigation said that Microsoft ‘did not have enough traffic volume to be an attractive alternative to Google’.15 Moreover, because Microsoft and Yahoo! were at a significant disadvantage in scale of search queries (learning-by-doing network effect), they had less incentive to degrade the quality of their search results (in order to maximize advertising revenue).16

B.  Efficiencies Must Be Merger-Specific

19.10  The merging parties must also prove that their efficiencies are merger-specific—‘meaning they represent a type of cost saving that could not be achieved without the merger’.17 The merging parties must demonstrate that ‘there are no less anti-competitive, realistic and attainable alternatives of a non-concentrative nature (e.g. a licensing agreement, or a cooperative joint venture) or of a concentrative nature (p. 306) (e.g. a concentrative joint venture, or a differently structured merger) than the notified merger which preserve the claimed efficiencies’.18

19.11  When the DOJ challenged Bazaarvoice’s acquisition of PowerReviews, Bazaarvoice argued that the increase in the four ‘V’s of data was an efficiency. Bazaarvoice claimed that post-merger it ‘now has access to a large amount of data and will be able to provide more value to its clients with additional and more powerful data analytics products, expand its social commerce marketing solutions focused on the retail channel for brands, and offer additional advertising and opportunities to engage with a wider audience for brands’.19 Bazaarvoice said the acquisition, by expanding its number of clients, including retailers and brands, would increase the variety and volume of data it would obtain, which would improve its data analytics products and tools.20

19.12  Bazaarvoice, however, failed to show that the efficiencies were merger-specific. Bazaarvoice, the court noted, ‘acknowledged that it could have shared data with PowerReviews absent the merger and, in the future, Bazaarvoice “fully expect[s]‌” to share data sets with other online software providers to expand analytic power’.21

19.13  It would seem then that the possibility of sharing data through licensing agreements would kill most data-driven efficiency claims. But the competition agencies ‘do not insist upon a less restrictive alternative that is merely theoretical’.22 Instead they only consider ‘alternatives that are reasonably practical in the business situation faced by the merging parties having regard to established business practices in the industry concerned’.23

19.14  Thus to substantiate their data-driven efficiency, the merging parties must articulate why a licensing arrangement is not reasonably practical. This might be the case where the velocity of data is key, and the data’s value would diminish by the time it is collected and shared. Or licensing the data might raise statutory or privacy issues. Or despite the best efforts of the drafters of the licensing agreement to align the contracting parties’ incentives, a significant risk remains that one or both of the contracting parties would engage in strategic behaviour. Such was the case in the TomTom/Tele Atlas merger.

19.15  Tele Atlas, as we saw in Chapter 6, supplied navigable digital map data to portable navigation device makers, including TomTom. The merging parties characterized (p. 307) the four ‘V’s of data as a procompetitive efficiency, enabling them to produce ‘better maps—faster’.24 Specifically, they argued how their vertical merger would yield significant efficiencies ‘due to the integration of TomTom’s … data to improve Tele Atlas’s map databases’.25 TomTom gathered ‘a very significant amount of feedback data from its large customer base through Map Share’.26 Apparently users of TomTom’s navigation devices would report to TomTom any errors in the maps. One can envision post-merger a positive feedback loop similar to Waze’s community-sourced mapping data: users report errors in the maps to TomTom, which now owns the navigable digital map database and can quickly fix the mistakes, thereby improving its maps’ quality, which attracts more users to TomTom’s devices, whose feedback further improves the maps’ quality and reduces TomTom’s costs.

19.16  TomTom/Tele Atlas’s data-driven efficiency, the European Commission found, conceivably fell within the efficiencies that the Merger Guidelines recognized.27 Moreover, the Commission agreed that ‘end-customers would certainly benefit from the more frequent and comprehensive map database updates made possible by the merger’.28

19.17  The efficiency was also merger-specific. Some market participants disagreed: Tele Atlas could contract with TomTom to secure the ‘feedback data.’29 The Commission was sceptical. There were no examples of such contracts in the marketplace.30 Moreover, a licensing agreement, the Commission found, could not practically yield the same efficiencies due to the parties’ concern over strategic behaviour:

Although part of the efficiencies put forward by the parties could potentially be achieved through contract, both parties are unlikely to pursue investments of the same order of magnitude as the integrated company. Such investments are risky for the non-integrated company since they are very specific to the particular relationship and hence subject to a so-called hold-up problem. Such a situation arises when a party refrains from cooperating with another due to the concern that it would become captive of its partner, for instance, because of specific investments that are only valuable if used with this partner and therefore loses all bargaining power. In addition, the difficulty in specifying all the required investments upfront and the uncertainty about the future environment in which the parties will operate makes it impossible to provide full protection to a non-integrated company through a long-term contract.31

(p. 308) 19.18  Although TomTom and Tele Atlas persuaded the Commission that their data-driven efficiencies were merger-specific and likely to benefit customers, they struck out on the third condition: they failed to verify them. The Commission found the claimed efficiencies ‘difficult to quantify’ and the parties’ estimates ‘not particularly convincing’.32

C.  Efficiencies Must Be Verifiable

19.19  As the TomTom/Tele Atlas merger shows, the efficiencies must be verifiable—‘namely reasoned, quantified and supported by internal studies and documents if necessary’.33 The ‘more precise and convincing the efficiency claims are, the better the Commission can evaluate the claims’.34 The agencies and courts are more likely to credit an efficiency documented as part of the internal valuation of the merger (rather than calculated after the fact to persuade the competition authority), including:

internal documents that were used by the management to decide on the merger, statements from the management to the owners and financial markets about the expected efficiencies, historical examples of efficiencies and consumer benefit, and pre-merger external experts’ studies on the type and size of efficiency gains, and on the extent to which consumers are likely to benefit.35

19.20  Bazaarvoice, for example, asserted that its acquisition brought ‘together the very best technologies and capabilities from both companies with the goal of developing “a next-generation platform” for its customers’.36 This efficiency, while potentially merger-specific, was never verified with evidence.37

D.  Balancing Efficiency and Privacy

19.21  Data-driven efficiencies, at times, will not raise privacy concerns. Although our focus has been on personal data, Big Data encompasses technical data of the companies’ internal production and distribution systems.38 Companies will increasingly seek to create a smart manufacturing and distribution infrastructure, ‘that lets operators make real-time use of “big data” flows from fully-instrumented plants in order to improve productivity, optimize supply chains, and improve energy, water, (p. 309) and materials use’.39 Big Data can be employed to monitor and optimize inventory levels, monitor machines for wear and tear of components, and reduce costs in the supply chain. These data-driven efficiencies involving internal manufacturing and distribution ordinarily will not raise privacy concerns.

19.22  But often Big Data involve consumers. Here too efficiencies can arise. As the Federal Trade Commission (FTC) identified in announcing a 2014 workshop on Big Data, ‘[t]‌remendous benefits flow from the insights of big data, such as advances in medicine, education, and transportation, improved product offerings, more efficient manufacturing processes, and more effectively tailored advertisements.’40

19.23  The FTC identified how financial institutions, online and brick-and-mortar retailers, lead generators, and service providers can use Big Data, not all of which are positive:

  • •  ‘To reward loyal customers with better customer service or shorter wait times.’

  • •  ‘To offer different prices or discounts to different consumers. For example, a financial institution may offer a consumer a discounted mortgage rate if that consumer has a checking, savings, credit card, and retirement account with a competitor.’

  • •  ‘To tailor advertising for financial products. For example, high-income consumers may receive offers for “gold level” credit cards and low-income consumers may receive offers for subprime credit cards.’

  • •  ‘To assess credit risks of particular populations. For example, some commentators have highlighted the use of unregulated “aggregate scoring models” that assess credit risks, not based on the credit characteristics of individual consumers, but on the aggregate credit characteristics of groups of consumers who shop at certain stores.’41

19.24  While the uses of Big Data can ‘create efficiencies, lower costs, and improve the ability of certain populations to find and access credit and other services’, the FTC noted, at the same time, ‘these practices may have an unfair impact on other populations, limiting their access to higher quality products, services, or content’.42

19.25  So if the relevant benchmark in assessing efficiency claims is that consumers will not be worse off as a result of the merger, how will the agency tackle merger-specific (p. 310) efficiencies that potentially benefits some customers (with ‘gold-level’ credit cards with perks) while harming others (with longer wait times, worse service, and onerous terms)? One likely outcome of Big Data is helping companies better price discriminate, where they charge different prices to different customers based on their estimate of how much the customer is willing to pay.43 Competition authorities will need to understand these trade-offs of Big Data by not only verifying how some customers may be better off post-merger, but independently inquiring whether others would be worse off.

19.26  Besides price discrimination and behavioural exploitation, there is also at times a trade-off between efficiency (targeting customers with more relevant ads) and privacy (tracking people and compiling profiles on them). As Peter Swire noted,

The topic of efficiencies shows an additional way that privacy harms can be logically included in antitrust analysis. To the extent proponents of the merger seek to justify the merger on efficiency grounds, such as personalization, then privacy harms to consumers should be considered as an offset to the claimed efficiencies. To give a simple numerical example, suppose that a merger analysis showed efficiencies of $10 million. If there are privacy harms estimated at $8 million, then the efficiencies that count should be no more than $2 million.44

19.27  One problem, however, is that privacy harms are often difficult to quantify. In assessing data-driven efficiencies, the EU and US competition agencies ‘will not simply compare the magnitude of the cognizable efficiencies with the magnitude of the likely harm to competition absent the efficiencies’.45 This suggests that if the merger lessens any important parameter of competition, then it should not matter whether the harm is quantifiable. The efficiencies must prevent any significant harm to consumers, including non-quantifiable privacy harms.

E.  Challenges Ahead

19.28  Data-driven efficiencies claims, as the Microsoft/Yahoo!, TomTom/Tele Atlas, and Bazaarvoice/PowerReviews cases reflect, have received so far a mixed reception. The parties at times will use the scale of data as an efficiency, and the competition authorities must understand both the data-driven merger’s competitive benefits and risks. At times, the merger may provide sufficient scale for smaller rivals to effectively compete. Thus, the competition agencies will want to know when data-driven (p. 311) mergers are likelier to lead to market dominance or enhance consumers’ welfare with better quality or innovative products and services.

19.29  As the competition authorities recognize, ‘[e]‌fficiencies are difficult to verify and quantify, in part because much of the information relating to efficiencies is uniquely in the possession of the merging firms.’46 This is especially the case if the companies are much further along in assessing and calculating data-driven efficiencies. If the competition agency is unfamiliar with data-driven business strategies generally, it will not necessarily know whether the data-driven efficiencies are projected reasonably and in good faith. The burden of demonstrating efficiencies is on the companies, not the government. This is where it should be. The companies will almost always have better information (especially if efficiencies are real and not an afterthought) as well as strong incentives to make out a case if there is one to be made.

19.30  The Chicago School decried how earlier merger policy inhibited efficiencies. The recent economics literature on firm behaviour, while less developed than that on consumer behaviour, suggests that many large mergers do not yield significant efficiencies.47 Thus even when the efficiencies are verifiable, the merger may turn out (p. 312) to be a bust. Competition agencies cannot presume, as some previously did, that the ‘vast majority of mergers pose no harm to consumers, and many produce efficiencies that benefit consumers in the form of lower prices, higher quality goods or services, or investments in innovation’.48 The agency must develop, through more post-merger reviews, a better understanding of when data-driven efficiencies will likely be realized. Moreover, at times the merging parties will discount any potential anticompetitive concerns by arguing that data is like sunshine, being both non-rivalrous and non-excludable. Other times, the parties will argue that their data-driven efficiencies are merger-specific, as the acquired firm’s data is not otherwise publicly available. Thus the agencies must understand what data can be obtained outside the merger, the costs and time to amass the data, and viable alternatives for these categories of data.

19.31  What we can conclude is that data-driven efficiencies, which are recognized in the industry, cited by customers in support of the merger, and verified by the agencies, will more likely influence the agencies. It will be easier for the agency to understand how the data-driven efficiency benefits customers if they directly hear from the customers how the efficiency would significantly enhance the merging parties’ competitive performance (such as Microsoft having access to a larger set of search queries would likely yield more relevant search results, particularly with rare, ‘tail’ queries), and how they would likely benefit in this more competitive environment. The customer effectively validates the efficiency and explains why it is merger- specific. In discussing how the efficiency would be passed on to them (rather than pocketed by the merging parties), the customer also undercuts a presumption of anticompetitive harm.

Footnotes:

1  United States v Grinnell Corp, 384 US 563, 570–1, 86 S Ct 1698, 1703–4 (1966).

2  FTC v Sysco Corp, Case No 1:15-CV-00256 (APM), 2015 WL 3958568, p *56 (US Dist Ct (D DC), 23 June 2015) (‘The court is not aware of any case, and Defendants have cited none, where the merging parties have successfully rebutted the government’s prima facie case on the strength of the efficiencies.’).

3  US Department of Justice (DOJ), ‘Statement by Assistant Attorney General Thomas O. Barnett Regarding the Closing of the Investigation of AT&T’s Acquisition of Bellsouth: Investigation Concludes That Combination Would Not Reduce Competition’, Press Release, 11 October 2006, http://www.justice.gov/archive/atr/public/press_releases/2006/218904.pdf; DOJ, ‘Statement of the Department of Justice Antitrust Division on Its Decision to Close Its Investigation of XM Satellite Radio Holdings Inc’s Merger with Sirius Satellite Radio Inc: Evidence Does Not Establish That Combination of Satellite Radio Providers Would Substantially Reduce Competition’, Press Release, 24 March 2008, http://www.justice.gov/archive/opa/pr/2008/March/08_at_226.html; DOJ, ‘Statement of the Department of Justice’s Antitrust Division on Its Decision to Close Its Investigation of the Merger of Delta Air Lines Inc and Northwest Airlines Corporation’, 29 October 2008, http://www.justice.gov/archive/opa/pr/2008/October/08-at-963.html.

4  DOJ and Federal Trade Commission (FTC), Horizontal Merger Guidelines, 19 August 2010, s 10 (‘US Horizontal Merger Guidelines’), http://www.ftc.gov/sites/default/files/attachments/merger-review/100819hmg.pdf; European Commission, Guidelines on the Assessment of Horizontal Mergers under the Council Regulation on the Control of Concentrations Between Undertakings [2004] OJ C 31/03, para 78 (‘EC Horizontal Merger Guidelines’), http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:52004XC0205%2802%29.

5  Sysco, above note 2, p *57; Case T-342/07 Ryanair Holdings plc v Commission [2010] ECR II-03457, para 387.

6  EC Horizontal Merger Guidelines, above note 4, para 79.

7  Saint Alphonsus Med Ctr-Nampa Inc v St Luke’s Health Sys, Ltd, 778 F3d 775, 792 (US Ct of Apps (9th Cir), 2015); see also US Horizontal Merger Guidelines, above note 4, s 10 (‘… Agencies are mindful that the antitrust laws give competition, not internal operational efficiency, primacy in protecting customers’).

8  US Horizontal Merger Guidelines, above note 4, s 10.

9  Ryanair Holdings, above note 5, para 414.

10  Ibid.

11  Sysco, above note 2, p *57; US Horizontal Merger Guidelines, above note 4, s 10 (‘The greater the potential adverse competitive effect of a merger, the greater must be the cognizable efficiencies, and the more they must be passed through to customers, for the Agencies to conclude that the merger will not have an anticompetitive effect in the relevant market.’).

12  US Horizontal Merger Guidelines, above note 4, s 10; see also EC Horizontal Merger Guidelines, above note 4, para 84 (‘It is highly unlikely that a merger leading to a market position approaching that of a monopoly, or leading to a similar level of market power, can be declared compatible with the common market on the ground that efficiency gains would be sufficient to counteract its potential anti-competitive effects.’).

13  Saint Alphonsus, above note 7 (because competition law ‘seeks to avert monopolies, proof of “extraordinary efficiencies” is required to offset the anticompetitive concerns in highly concentrated markets’); see also Ryanair Holdings, above note 5, para 391.

14  DOJ, Office of Public Affairs, ‘Statement of the Department of Justice Antitrust Division on Its Decision to Close Its Investigation of the Internet Search and Paid Search Advertising Agreement Between Microsoft Corporation and Yahoo! Inc: Investigation Shows That Agreement Not Likely to Reduce Competition’, 18 February 2010, http://www.justice.gov/opa/pr/statement-department-justice-antitrust-division-its-decision-close-its-investigation-internet (market participants ‘believe[d]‌ that combining the parties’ technology would be likely to increase competition by creating a more viable competitive alternative to Google, the firm that now dominates these markets. Most customers view Google as posing the most significant competitive constraint on both Microsoft and Yahoo!, and the competitive focus of both Microsoft and Yahoo! is predominately on Google and not on each other.’).

15  Microsoft/Yahoo! Search Business (Case Comp/M.7217), Commission Decision C(2014) 7239 final, 18 February 2010, para 153, http://ec.europa.eu/competition/mergers/cases/decisions/M5727_20100218_20310_261202_EN.pdf.

16  Maurice E Stucke and Ariel Ezrachi, ‘When Competition Fails to Optimize Quality: A Look at Search Engines’, 18 Yale J L & Tech (2016): p 70; Microsoft/Yahoo! Search, above note 15, para 219.

17  Sysco, above note 2, p *57 (internal citation omitted); EC Horizontal Merger Guidelines, above note 4, para 85 (‘Efficiencies are relevant to the competitive assessment when they are a direct consequence of the notified merger and cannot be achieved to a similar extent by less anticompetitive alternatives.’); Ryanair Holdings, above note 5, paras 387 and 427; US Horizontal Merger Guidelines, above note 4, s 10 (crediting ‘only those efficiencies likely to be accomplished with the proposed merger and unlikely to be accomplished in the absence of either the proposed merger or another means having comparable anticompetitive effects’).

18  EC Horizontal Merger Guidelines, above note 4, para 85.

19  United States v Bazaarvoice, Case No 3:13-cv-00133-WHO, 2014 WL 203966 (US Dist Ct (ND Cal), 8 January 2014), para 310.

20  Ibid, para 315.

21  Ibid.

22  US Horizontal Merger Guidelines, above note 4, s 10.

23  EC Horizontal Merger Guidelines, above note 4, para 85.

24  TomTom/Tele Atlas (Case Comp/M.4854), Commission Decision C(2008) 1859 [2008] OJ C 237/53.

25  Ibid.

26  Ibid.

27  Ibid.

28  Ibid, p 54.

29  Ibid, p 54 n 190.

30  Ibid.

31  Ibid, p 54 (internal footnote omitted).

32  Ibid.

33  Ryanair Holdings, above note 5, para 389; see also Sysco, above note 2, p *57.

34  EC Horizontal Merger Guidelines, above note 4, para 86.

35  Ibid, para 88.

36  Bazaarvoice, above note 19, para 315.

37  Ibid.

39  The White House, ‘President Obama to Announce New Efforts to Support Manufacturing Innovation, Encourage Insourcing’, Press Release, 9 March 2012, https://www.whitehouse.gov/the-press-office/2012/03/09/president-obama-announce-new-efforts-support-manufacturing-innovation-en.

40  FTC, ‘Big Data: A Tool for Inclusion or Exclusion?’, Conference Description, updated 2 November 2010, http://www.ftc.gov/news-events/events-calendar/2014/09/big-data-tool- inclusion-or-exclusion.

41  Ibid.

42  Ibid.

43  For how Big Data can help companies approach perfect price discrimination and the welfare effects, see Ariel Ezrachi and Maurice E Stucke, Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy (Cambridge, MA: Harvard University Press, forthcoming 2016).

44  Peter P Swire, Professor, Moritz College of Law of the Ohio State University & Senior Fellow, Center for American Progress, Submitted Testimony to the Federal Trade Commission Behavioral Advertising Town Hall 3, 18 October 2007, p 7.

45  US Horizontal Merger Guidelines, above note 4, s 10.

46  US Horizontal Merger Guidelines, above note 4, s 10.

47  Kenneth M Davidson, Reality Ignored: How Milton Friedman and Chicago Economics Undermined American Institutions and Endangered the Global Economy (Seattle: CreateSpace Independent Publishing Platform, 2011), p 64; Ulrike Malmendier et al, Winning by Losing: Evidence on the Long-Run Effects of Mergers, NBER Working Paper 18024, April 2012, http://www.nber.org/papers/w18024 (collecting data on all US mergers with concurrent bids of at least two public potential acquirers from 1985 to 2009, comparing winners’ and losers’ performance prior and several years after the merger contest, and finding that post-merger, losing bidders significantly outperform winning bidders); George Alexandridis et al, ‘How Have M&As Changed? Evidence from the Sixth Merger Wave’, 18 Eur J Fin (2012): p 663; Klaus Gugler et al, ‘Market Optimism and Merger Waves’, 33 Mgmt Decision Econ (2012): pp 159, 171–2; Clayton M Christensen et al, ‘The Big Idea: The New M&A Playbook’, Harv Bus Rev (March 2011): pp 49, 49 (reporting that ‘study after study puts the failure rate of mergers and acquisitions somewhere between 70 percent and 90 percent’); Spencer Weber Waller, ‘Corporate Governance and Competition Policy’, 18 Geo Mason L Rev (2011): pp 833, 873–9 (examining evidence from corporate finance that suggests that entire categories of mergers are ‘more likely to destroy, rather than enhance, shareholder value’); Vicki Bogan and David Just, ‘What Drives Merger Decision Making Behavior? Don’t Seek, Don’t Find, and Don’t Change Your Mind’, 72 J Econ Behav & Org (2009): pp 930, 930–1 (collecting some of the academic research showing that many mergers add no value or reduce shareholder value for the acquiring firm); Sara B Moeller et al, Do Shareholders of Acquiring Firms Gain from Acquisitions?, NBER Working Paper No 9523, February 2003, http://www.nber.org/papers/w9523 (in examining whether shareholders of acquiring firms gain when firms announce acquisitions of public firms, private firms, and subsidiaries, the study examined over 12,000 purchases between 1980 to 2001 for more than $1 million by public firms and found roughly that ‘shareholders from small firms earn $8 billion from the acquisitions they made from 1980 to 2001, whereas the shareholders from large firms lose $226 billion’); James A Fanto, ‘Braking the Merger Momentum: Reforming Corporate Law Governing Mega-Mergers’, 49 Buff L Rev (2001): pp 249, 280 (‘The systematic empirical evidence on past mergers and the available data on the mega-mergers, however, now supports the conclusion that a large majority of these transactions destroy shareholder value.’); Walter Adams and James W Brock, ‘Antitrust and Efficiency: A Comment’, 62 NYU L Rev (1987): pp 1116, 1117 n 8 (referencing earlier studies).

48  FTC and DOJ, Commentary on the Horizontal Merger Guidelines, March 2006, p v, http://www.justice.gov/sites/default/files/atr/legacy/2006/04/27/215247.pdf.