Carl Shapiro, the government’s economics expert opposing the AT&T-Time Warner merger, seems skeptical of much of the antitrust populists’ Amazon rhetoric: “Simply saying that Amazon has grown like a weed, charges very low prices, and has driven many smaller retailers out of business is not sufficient. Where is the consumer harm?”

On its face, there was nothing about the Amazon/Whole Foods merger that should have raised any antitrust concerns. While one year is too soon to fully judge the competitive impacts of the Amazon-Whole Foods merger, nevertheless, it appears that much of the populist antitrust movement’s speculation that the merger would destroy competition and competitors and impoverish workers has failed to materialize.

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Viewed from the long history of the evolution of the grocery store, the Amazon-Whole Foods merger made sense as the start of the next stage of that historical process. The combination of increased wealth that is driving the demand for upscale grocery stores, and the corresponding increase in the value of people’s time that is driving the demand for one-stop shopping and various forms of pick-up and delivery, makes clear the potential benefits of this merger. Amazon was already beginning to make a mark in the sale and delivery of the non-perishables and dry goods that upscale groceries tend to have less of. Acquiring Whole Foods gives it a way to expand that into perishables in a very sensible way. We are only beginning to see the synergies that this combination will produce. Its long-term effect on the structure of the grocery business will be significant and highly beneficial for consumers.

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At the heart of the common ownership issue in the current antitrust debate is an empirical measure, the Modified Herfindahl-Hirschmann Index, researchers have used to correlate patterns of common ownership with measures of firm behavior and performance. In an accompanying post, Thom Lambert provides a great summary of just what the MHHI, and more specifically the MHHIΔ, is and how it can be calculated. I’m going to free-ride off Thom’s effort, so if you’re not very familiar with the measure, I suggest you start here and here.

There are multiple problems with the common ownership story and with the empirical evidence proponents of stricter antitrust enforcement point to in order to justify their calls to action. Thom and I address a number of those problems in our recent paper on “The Case for Doing Nothing About Institutional Investors’ Common Ownership of Small Stakes in Competing Firms.” However, one problem we don’t take on in that paper is the nature of the MHHIΔ itself. More specifically, what is one to make of it and how should it be interpreted, especially from a policy perspective?

The Policy Benchmark

The benchmark for discussion is the original Herfindahl-Hirschmann Index (HHI), which has been part of antitrust for decades. The HHI is calculated by summing the squared value of each firm’s market share. Depending on whether you use percents or percentages, the value of the sum may be multiplied by 10,000. For instance, for two firms that split the market evenly, the HHI could be calculated either as:

HHI = 502 + 502 = 5.000, or
HHI = (.502 + .502)*10,000 = 5,000

It’s a pretty simple exercise to see that one of the useful properties of HHI is that it is naturally bounded between 0 and 10,000. In the case of a pure monopoly that commands the entire market, the value of HHI is 10,000 (1002). As the number of firms increases and market shares approach very small fractions, the value of HHI asymptotically approaches 0. For a market with 10 firms firms that evenly share the market, for instance, HHI is 1,000; for 100 identical firms, HHI is 100; for 1,000 identical firms, HHI is 1. As a result, we know that when HHI is close to 10,000, the industry is highly concentrated in one firm; and when the HHI is close to zero, there is no meaningful concentration at all. Indeed, the Department of Justice’s Horizontal Merger Guidelines make use of this property of the HHI:

Based on their experience, the Agencies generally classify markets into three types:

  • Unconcentrated Markets: HHI below 1500
  • Moderately Concentrated Markets: HHI between 1500 and 2500
  • Highly Concentrated Markets: HHI above 2500

The Agencies employ the following general standards for the relevant markets they have defined:

  • Small Change in Concentration: Mergers involving an increase in the HHI of less than 100 points are unlikely to have adverse competitive effects and ordinarily require no further analysis.
  • Unconcentrated Markets: Mergers resulting in unconcentrated markets are unlikely to have adverse competitive effects and ordinarily require no further analysis.
  • Moderately Concentrated Markets: Mergers resulting in moderately concentrated markets that involve an increase in the HHI of more than 100 points potentially raise significant competitive concerns and often warrant scrutiny.
  • Highly Concentrated Markets: Mergers resulting in highly concentrated markets that involve an increase in the HHI of between 100 points and 200 points potentially raise significant competitive concerns and often warrant scrutiny. Mergers resulting in highly concentrated markets that involve an increase in the HHI of more than 200 points will be presumed to be likely to enhance market power. The presumption may be rebutted by persuasive evidence showing that the merger is unlikely to enhance market power.

Just by way of reference, an HHI of 2500 could reflect four firms sharing the market equally (i.e., 25% each), or it could be one firm with roughly 49% of the market and 51 identical small firms sharing the rest evenly.

Injecting MHHIΔ Into the Mix

MHHI is intended to account for both the product market concentration among firms captured by the HHI, and the common ownership concentration across firms in the market measured by the MHHIΔ. In short, MHHI = HHI + MHHIΔ.

As Thom explains in great detail, MHHIΔ attempts to measure the combined effects of the relative influence of shareholders that own positions across competing firms on management’s strategic decision-making and the combined market shares of the commonly-owned firms. MHHIΔ is the measure used in the various empirical studies allegedly demonstrating a causal relationship between common ownership (higher MHHIΔs) and the supposed anti-competitive behavior of choice.

Some common ownership critics, such as Einer Elhague, have taken those results and suggested modifying antitrust rules to incorporate the MHHIΔ in the HHI guidelines above. For instance, Elhague writes (p 1303):

Accordingly, the federal agencies can and should challenge any stock acquisitions that have produced, or are likely to produce, anti-competitive horizontal shareholdings. Given their own guidelines and the empirical results summarized in Part I, they should investigate any horizontal stock acquisitions that have created, or would create, a ΔMHHI of over 200 in a market with an MHHI over 2500, in order to determine whether those horizontal stock acquisitions raised prices or are likely to do so.

Elhague, like many others, couch their discussion of MHHI and MHHIΔ in the context of HHI values as though the additive nature of MHHI means such a context make sense. And if the examples are carefully chosen, the numbers even seem to make sense. For instance, even in our paper (page 30), we give a few examples to illustrate some of the endogeneity problems with MHHIΔ:

For example, suppose again that five institutional investors hold equal stakes (say, 3%) of each airline servicing a market and that the airlines have no other significant shareholders.  If there are two airlines servicing the market and their market shares are equivalent, HHI will be 5000, MHHI∆ will be 5000, and MHHI (HHI + MHHI∆) will be 10000.  If a third airline enters and grows so that the three airlines have equal market shares, HHI will drop to 3333, MHHI∆ will rise to 6667, and MHHI will remain constant at 10000.  If a fourth airline enters and the airlines split the market evenly, HHI will fall to 2500, MHHI∆ will rise further to 7500, and MHHI will again total 10000.

But do MHHI and MHHI∆ really fit so neatly into the HHI framework? Sadly–and worringly–no, not at all.

The Policy Problem

There seems to be a significant problem with simply imposing MHHIΔ into the HHI framework. Unlike HHI, from which we can infer something about the market based on the nominal value of the measure, MHHIΔ has no established intuitive or theoretical grounding. In fact, MHHIΔ has no intuitively meaningful mathematical boundaries from which to draw inferences about “how big is big?”, a fundamental problem for antitrust policy.

This is especially true within the range of cross-shareholding values we’re talking about in the common ownership debate. To illustrate just how big a problem this is, consider a constrained optimization of MHHI based on parameters that are not at all unreasonable relative to hypothetical examples cited in the literature:

  • Four competing firms in the market, each of which is constrained to having at least 5% market share, and their collective sum must equal 1 (or 100%).
  • Five institutional investors each of which can own no more than 5% of the outstanding shares of any individual airline, with no restrictions across airlines.
  • The remaining outstanding shares are assumed to be diffusely owned (i.e., no other large shareholder in any firm).

With only these modest restrictions on market share and common ownership, what’s the maximum potential value of MHHI? A mere 26,864,516,491, with an MHHI∆ of 26,864,513,774 and HHI of 2,717.

That’s right, over 26.8 billion. To reach such an astronomical number, what are the parameter values? The four firms split the market with 33, 31.7, 18.3, and 17% shares, respectively. Investor 1 owns 2.6% of the largest firm (by market share) while Investors 2-5 each own between 4.5 and 5% of the largest firm. Investors 1 and 2 own 5% of the smallest firm, while Investors 3 and 4 own 3.9% and Investor 5 owns a minuscule (0.0006%) share. Investor 2 is the only investor with any holdings (a tiny 0.0000004% each) in the two middling firms. These are not unreasonable numbers by any means, but the MHHI∆ surely is–especially from a policy perspective.

So if MHHI∆ can range from near zero to as much as 28.6 billion within reasonable ranges of market share and shareholdings, what should we make of Elhague’s proposal that mergers be scrutinized for increasing MHHI∆ by 200 points if the MHHI is 2,500 or more? We argue that such an arbitrary policy model is not only unfounded empirically, but is completely void of substantive reason or relevance.

The DOJ’s Horizontal Merger Guidelines above indicate that antitrust agencies adopted the HHI benchmarks for review “[b]ased on their experience”.  In the 1982 and 1984 Guidelines, the agencies adopted HHI standards 1,000 and 1,800, compared to the current 1,500 and 2,500 levels, in determining whether the industry is concentrated and a merger deserves additional scrutiny. These changes reflect decades of case reviews relating market structure to likely competitive behavior and consumer harm.

We simply do not know enough yet empirically about the relation between MHHI∆ and benchmarks of competitive behavior and consumer welfare to make any intelligent policies based on that metric–even if the underlying argument had any substantive theoretical basis, which we doubt. This is just one more reason we believe the best response to the common ownership problem is to do nothing, at least until we have a theoretically, and empirically, sound basis on which to make intelligent and informed policy decisions and frameworks.

Announcement

Truth on the Market is pleased to announce its next blog symposium:

Is Amazon’s Appetite Bottomless?

The Whole Foods Merger After One Year

August 28, 2018

One year ago tomorrow the Amazon/Whole Foods merger closed, following its approval by the FTC. The merger was something of a flashpoint in the growing populist antitrust movement, raising some interesting questions — and a host of objections from a number of scholars, advocates, journalists, antitrust experts, and others who voiced a range of possible problematic outcomes.

Under settled antitrust law — evolved over the last century-plus — the merger between Amazon and Whole Foods was largely uncontroversial. But the size and scope of Amazon’s operation and ambition has given some pause. And despite the apparent inapplicability of antitrust law to the array of populist concerns about large tech companies, advocates nonetheless contend that antitrust should be altered to deal with new threats posed by companies like Amazon.  

For something of a primer on the antitrust debate surrounding Amazon, listen to ICLE’s Geoffrey Manne and Open Markets’ Lina Khan on Season 2 Episode 1 of Briefly, a podcast produced by the University of Chicago Law Review.  

Beginning tomorrow, August 28, Truth on the Market and the International Center for Law & Economics will host a blog symposium discussing the impact of the merger.

One year on, we asked antitrust scholars and other experts to consider:

  • What has been the significance of the Amazon/Whole Foods merger?
  • How has the merger affected various markets and the participants within them (e.g., grocery stores, food delivery services, online retailers, workers, grocery suppliers, etc.)?
  • What, if anything, does the merger and its aftermath tell us about current antitrust doctrine and our understanding of platform markets?
  • Has a year of experience borne out any of the objections to the merger?
  • Have the market changes since the merger undermined or reinforced the populist antitrust arguments regarding this or other conduct?

As in the past (see examples of previous TOTM blog symposia here), we’ve lined up an outstanding and diverse group of scholars to discuss these issues.

Participants

The symposium posts will be collected here. We hope you’ll join us!

The Federal Trade Commission will soon hold hearings on Competition and Consumer Protection in the 21st Century.  The topics to be considered include:

  1. The state of antitrust and consumer protection law and enforcement, and their development, since the [1995] Pitofsky hearings;
  2. Competition and consumer protection issues in communication, information and media technology networks;
  3. The identification and measurement of market power and entry barriers, and the evaluation of collusive, exclusionary, or predatory conduct or conduct that violates the consumer protection statutes enforced by the FTC, in markets featuring “platform” businesses;
  4. The intersection between privacy, big data, and competition;
  5. The Commission’s remedial authority to deter unfair and deceptive conduct in privacy and data security matters;
  6. Evaluating the competitive effects of corporate acquisitions and mergers;
  7. Evidence and analysis of monopsony power, including but not limited to, in labor markets;
  8. The role of intellectual property and competition policy in promoting innovation;
  9. The consumer welfare implications associated with the use of algorithmic decision tools, artificial intelligence, and predictive analytics;
  10. The interpretation and harmonization of state and federal statutes and regulations that prohibit unfair and deceptive acts and practices; and
  11. The agency’s investigation, enforcement and remedial processes.

The Commission has solicited comments on each of these main topics and a number of subtopics.  Initial comments are due today, but comments will also be accepted at two other times.  First, before each scheduled hearing on a topic, the Commission will accept comments on that particular matter.  In addition, the Commission will accept comments at the end of all the hearings.

Over the weekend, Mike Sykuta and I submitted a comment on topic 6, “evaluating the competitive effects of corporate acquisitions and mergers.”  We addressed one of the subtopics the FTC will consider: “the analysis of acquisitions and holding of a non-controlling ownership interest in competing companies.”

Here’s our comment, with a link to our working paper on the topic of common ownership by institutional investors:

To Whom It May Concern:

We are grateful for the opportunity to respond to the U.S. Federal Trade Commission’s request for comment on its upcoming hearings on Competition and Consumer Protection in the 21st Century. We are professors of law (Lambert) and economics (Sykuta) at the University of Missouri. We wish to comment on Topic 6, “evaluating the competitive effects of corporate acquisitions and mergers” and specifically on Subtopic 6(c), “the analysis of acquisitions and holding of a non-controlling ownership interest in competing companies.”

Recent empirical research purports to demonstrate that institutional investors’ “common ownership” of small stakes in competing firms causes those firms to compete less aggressively, injuring consumers. A number of prominent antitrust scholars have cited this research as grounds for limiting the degree to which institutional investors may hold stakes in multiple firms that compete in any concentrated market. In our recent working paper, The Case for Doing Nothing About Institutional Investors’ Common Ownership of Small Stakes in Competing Firms, which we submit along with these comments, we contend that the purported competitive problem is overblown and that the proposed solutions would reduce overall social welfare.

With respect to the purported problem, our paper shows that the theory of anticompetitive harm from institutional investors’ common ownership is implausible and that the empirical studies supporting the theory are methodologically unsound. The theory fails to account for the fact that intra-industry diversified institutional investors are also inter-industry diversified, and it rests upon unrealistic assumptions about managerial decision-making. The empirical studies purporting to demonstrate anticompetitive harm from common ownership are deficient because they inaccurately assess institutional investors’ economic interests and employ an endogenous measure that precludes causal inferences.

Even if institutional investors’ common ownership of competing firms did soften market competition somewhat, the proposed policy solutions would themselves create welfare losses that would overwhelm any social benefits they secured. The proposed policy solutions would create tremendous new decision costs for business planners and adjudicators and would raise error costs by eliminating welfare-enhancing investment options and/or exacerbating corporate agency costs.

In light of these problems with the purported problem and shortcomings of the proposed solutions, the optimal regulatory approach—at least, on the current empirical record—is to do nothing about institutional investors’ common ownership of small stakes in competing firms.

Thank you for considering these comments and our attached paper. We would be happy to answer any questions you may have.

Sincerely,

Thomas A. Lambert, Wall Family Chair in Corporate Law and Governance, University of Missouri Law School;
Michael E. Sykuta, Associate Professor, Division of Applied Social Sciences, University of Missouri; Director, Contracting and Organizations Research Institute (CORI)

Kudos to the Commission for holding this important set of hearings.

One of the hottest topics in antitrust these days is institutional investors’ common ownership of the stock of competing firms. Large investment companies like BlackRock, Vanguard, State Street, and Fidelity offer index and actively managed mutual funds that are invested in thousands of companies. In many concentrated industries, these institutional investors are “intra-industry diversified,” meaning that they hold stakes in all the significant competitors within the industry.

Recent empirical studies (e.g., here and here) purport to show that this intra-industry diversification has led to a softening of competition in concentrated markets. The theory is that firm managers seek to maximize the profits of their largest and most powerful shareholders, all of which hold stakes in all the major firms in the market and therefore prefer maximization of industry, not firm-specific, profits. (For example, an investor that owns stock in all the airlines servicing a route would not want those airlines to engage in aggressive price competition to win business from each other. Additional sales to one airline would come at the expense of another, and prices—and thus profit margins—would be lower.)

The empirical studies on common ownership, which have received a great deal of attention in the academic literature and popular press and have inspired antitrust scholars to propose a number of policy solutions, have employed a complicated measurement known as “MHHI delta” (MHHI∆). MHHI∆ is a component of the “modified Herfindahl–Hirschman Index” (MHHI), which, as the name suggests, is an adaptation of the Herfindahl–Hirschman Index (HHI).

HHI, which ranges from near zero to 10,000 and is calculated by summing the squares of the market shares of the firms competing in a market, assesses the degree to which a market is concentrated and thus susceptible to collusion or oligopolistic coordination. MHHI endeavors to account for both market concentration (HHI) and the reduced competition incentives occasioned by common ownership of the firms within a market. MHHI∆ is the part of MHHI that accounts for common ownership incentives, so MHHI = HHI + MHHI∆.  (Notably, neither MHHI nor MHHI∆ is bounded by the 10,000 upper limit applicable to HHI.  At the end of this post, I offer an example of a market in which MHHI and MHHI∆ both exceed 10,000.)

In the leading common ownership study, which looked at the airline industry, the authors first calculated the MHHI∆ on each domestic airline route from 2001 to 2014. They then examined, for each route, how changes in the MHHI∆ over time correlated with changes in airfares on that route. To control for route-specific factors that might influence both fares and the MHHI∆, the authors ran a number of regressions. They concluded that common ownership of air carriers resulted in a 3%–7% increase in fares.

As should be apparent, it is difficult to understand the common ownership issue—the extent to which there is a competitive problem and the propriety of proposed solutions—without understanding MHHI∆. Unfortunately, the formula for the metric is extraordinarily complex. Posner et al. express it as follows:

Where:

  • βij is the fraction of shares in firm j controlled by investor I,
  • the shares are both cash flow and control shares (so control rights are assumed to be proportionate to the investor’s share of firm profits), and
  • sj is the market share of firm j.

The complexity of this formula is, for less technically oriented antitrusters (like me!), a barrier to entry into the common ownership debate.  In the paragraphs that follow, I attempt to lower that entry barrier by describing the overall process for determining MHHI∆, cataloguing the specific steps required to calculate the measure, and offering a concrete example.

Overview of the Process for Calculating MHHI∆

Determining the MHHI∆ for a market involves three primary tasks. The first is to assess, for each coupling of competing firms in the market (e.g., Southwest Airlines and United Airlines), the degree to which the investors in one of the competitors would prefer that it not attempt to win business from the other by lowering prices, etc. This assessment must be completed twice for each coupling. With the Southwest and United coupling, for example, one must assess both the degree to which United’s investors would prefer that the company not win business from Southwest and the degree to which Southwest’s investors would prefer that the company not win business from United. There will be different answers to those two questions if, for example, United has a significant shareholder who owns no Southwest stock (and thus wants United to win business from Southwest), but Southwest does not have a correspondingly significant shareholder who owns no United stock (and would thus want Southwest to win business from United).

Assessing the incentive of one firm, Firm J (to correspond to the formula above), to pull its competitive punches against another, Firm K, requires calculating a fraction that compares the interest of the first firm’s owners in “coupling” profits (the combined profits of J and K) to their interest in “own-firm” profits (J profits only). The numerator of that fraction is based on data from the coupling—i.e., the firm whose incentive to soften competition one is assessing (J) and the firm with which it is competing (K). The fraction’s denominator is based on data for the single firm whose competition-reduction incentive one is assessing (J). Specifically:

  • The numerator assesses the degree to which the firms in the coupling are commonly owned, such that their owners would not benefit from price-reducing, head-to-head competition and would instead prefer that the firms compete less vigorously so as to maximize coupling profits. To determine the numerator, then, one must examine all the investors who are invested in both firms; for each, multiply their ownership percentages in the two firms; and then sum those products for all investors with common ownership. (If an investor were invested in only one firm in the coupling, its ownership percentage would be multiplied by zero and would thus drop out; after all, an investor in only one of the firms has no interest in maximization of coupling versus own-firm profits.)
  • The denominator assesses the degree to which the investor base (weighted by control) of the firm whose competition-reduction incentive is under consideration (J) would prefer that it maximize its own profits, not the profits of the coupling. Determining the denominator requires summing the squares of the ownership percentages of investors in that firm. Squaring means that very small investors essentially drop out and that the denominator grows substantially with large ownership percentages by particular investors. Large ownership percentages suggest the presence of shareholders that are more likely able to influence management, whether those shareholders also own shares in the second company or not.

Having assessed, for each firm in a coupling, the incentive to soften competition with the other, one must proceed to the second primary task: weighing the significance of those firms’ incentives not to compete with each other in light of the coupling’s shares of the market. (The idea here is that if two small firms reduced competition with one another, the effect on overall market competition would be less significant than if two large firms held their competitive fire.) To determine the significance to the market of the two coupling members’ incentives to reduce competition with each other, one must multiply each of the two fractions determined above (in Task 1) times the product of the market shares of the two firms in the coupling. This will generate two “cross-MHHI deltas,” one for each of the two firms in the coupling (e.g., one cross-MHHI∆ for Southwest/United and another for United/Southwest).

The third and final task is to aggregate the effect of common ownership-induced competition-softening throughout the market as a whole by summing the softened competition metrics (i.e., two cross-MHHI deltas for each coupling of competitors within the market). If decimals were used to account for the firms’ market shares (e.g., if a 25% market share was denoted 0.25), the sum should be multiplied by 10,000.

Following is a detailed list of instructions for assessing the MHHI∆ for a market (assuming proportionate control—i.e., that investors’ control rights correspond to their shares of firm profits).

A Nine-Step Guide to Calculating the MHHI∆ for a Market

  1. List the firms participating in the market and the market share of each.
  2. List each investor’s ownership percentage of each firm in the market.
  3. List the potential pairings of firms whose incentives to compete with each other must be assessed. There will be two such pairings for each coupling of competitors in the market (e.g., Southwest/United and United/Southwest) because one must assess the incentive of each firm in the coupling to compete with the other, and that incentive may differ for the two firms (e.g., United may have less incentive to compete with Southwest than Southwest with United). This implies that the number of possible pairings will always be n(n-1), where n is the number of firms in the market.
  4. For each investor, perform the following for each pairing of firms: Multiply the investor’s percentage ownership of the two firms in each pairing (e.g., Institutional Investor 1’s percentage ownership in United * Institutional Investor 1’s percentage ownership in Southwest for the United/Southwest pairing).
  5. For each pairing, sum the amounts from item four across all investors that are invested in both firms. (This will be the numerator in the fraction used in Step 7 to determine the pairing’s cross-MHHI∆.)
  6. For the first firm in each pairing (the one whose incentive to compete with the other is under consideration), sum the squares of the ownership percentages of that firm held by each investor. (This will be the denominator of the fraction used in Step 7 to determine the pairing’s cross-MHHI∆.)
  7. Figure the cross-MHHI∆ for each pairing of firms by doing the following: Multiply the market shares of the two firms, and then multiply the resulting product times a fraction consisting of the relevant numerator (from Step 5) divided by the relevant denominator (from Step 6).
  8. Add together the cross-MHHI∆s for each pairing of firms in the market.
  9. Multiply that amount times 10,000.

I will now illustrate this nine-step process by working through a concrete example.

An Example

Suppose four airlines—American, Delta, Southwest, and United—service a particular market. American and Delta each have 30% of the market; Southwest and United each have a market share of 20%.

Five funds are invested in the market, and each holds stock in all four airlines. Fund 1 owns 1% of each airline’s stock. Fund 2 owns 2% of American and 1% of each of the others. Fund 3 owns 2% of Delta and 1% of each of the others. Fund 4 owns 2% of Southwest and 1% of each of the others. And Fund 4 owns 2% of United and 1% of each of the others. None of the airlines has any other significant stockholder.

Step 1: List firms and market shares.

  1. American – 30% market share
  2. Delta – 30% market share
  3. Southwest – 20% market share
  4. United – 20% market share

Step 2: List investors’ ownership percentages.

Step 3: Catalogue potential competitive pairings.

  1. American-Delta (AD)
  2. American-Southwest (AS)
  3. American-United (AU)
  4. Delta-American (DA)
  5. Delta-Southwest (DS)
  6. Delta-United (DU)
  7. Southwest-American (SA)
  8. Southwest-Delta (SD)
  9. Southwest-United (SU)
  10. United-American (UA)
  11. United-Delta (UD)
  12. United-Southwest (US)

Steps 4 and 5: Figure numerator for determining cross-MHHI∆s.

Step 6: Figure denominator for determining cross-MHHI∆s.

Steps 7 and 8: Determine cross-MHHI∆s for each potential pairing, and then sum all.

  1. AD: .09(.0007/.0008) = .07875
  2. AS: .06(.0007/.0008) = .0525
  3. AU: .06(.0007/.0008) = .0525
  4. DA: .09(.0007/.0008) = .07875
  5. DS: .06(.0007/.0008) = .0525
  6. DU: .06(.0007/.0008) = .0525
  7. SA: .06(.0007/.0008) = .0525
  8. SD: .06(.0007/.0008) = .0525
  9. SU: .04(.0007/.0008) = .035
  10. UA: .06(.0007/.0008) = .0525
  11. UD: .06(.0007/.0008) = .0525
  12. US: .04(.0007/.0008) = .035
    SUM = .6475

Step 9: Multiply by 10,000.

MHHI∆ = 6475.

(NOTE: HHI in this market would total (30)(30) + (30)(30) + (20)(20) + (20)(20) = 2600. MHHI would total 9075.)

***

I mentioned earlier that neither MHHI nor MHHI∆ is subject to an upper limit of 10,000. For example, if there are four firms in a market, five institutional investors that each own 5% of the first three firms and 1% of the fourth, and no other investors holding significant stakes in any of the firms, MHHI∆ will be 15,500 and MHHI 18,000.  (Hat tip to Steve Salop, who helped create the MHHI metric, for reminding me to point out that MHHI and MHHI∆ are not limited to 10,000.)

Last week, I objected to Senator Warner relying on the flawed AOL/Time Warner merger conditions as a template for tech regulatory policy, but there is a much deeper problem contained in his proposals.  Although he does not explicitly say “big is bad” when discussing competition issues, the thrust of much of what he recommends would serve to erode the power of larger firms in favor of smaller firms without offering a justification for why this would result in a superior state of affairs. And he makes these recommendations without respect to whether those firms actually engage in conduct that is harmful to consumers.

In the Data Portability section, Warner says that “As platforms grow in size and scope, network effects and lock-in effects increase; consumers face diminished incentives to contract with new providers, particularly if they have to once again provide a full set of data to access desired functions.“ Thus, he recommends a data portability mandate, which would theoretically serve to benefit startups by providing them with the data that large firms possess. The necessary implication here is that it is a per se good that small firms be benefited and large firms diminished, as the proposal is not grounded in any evaluation of the competitive behavior of the firms to which such a mandate would apply.

Warner also proposes an “interoperability” requirement on “dominant platforms” (which I criticized previously) in situations where, “data portability alone will not produce procompetitive outcomes.” Again, the necessary implication is that it is a per se good that established platforms share their services with start ups without respect to any competitive analysis of how those firms are behaving. The goal is preemptively to “blunt their ability to leverage their dominance over one market or feature into complementary or adjacent markets or products.”

Perhaps most perniciously, Warner recommends treating large platforms as essential facilities in some circumstances. To this end he states that:

Legislation could define thresholds – for instance, user base size, market share, or level of dependence of wider ecosystems – beyond which certain core functions/platforms/apps would constitute ‘essential facilities’, requiring a platform to provide third party access on fair, reasonable and non-discriminatory (FRAND) terms and preventing platforms from engaging in self-dealing or preferential conduct.

But, as  i’ve previously noted with respect to imposing “essential facilities” requirements on tech platforms,

[T]he essential facilities doctrine is widely criticized, by pretty much everyone. In their respected treatise, Antitrust Law, Herbert Hovenkamp and Philip Areeda have said that “the essential facility doctrine is both harmful and unnecessary and should be abandoned”; Michael Boudin has noted that the doctrine is full of “embarrassing weaknesses”; and Gregory Werden has opined that “Courts should reject the doctrine.”

Indeed, as I also noted, “the Supreme Court declined to recognize the essential facilities doctrine as a distinct rule in Trinko, where it instead characterized the exclusionary conduct in Aspen Skiing as ‘at or near the outer boundary’ of Sherman Act § 2 liability.”

In short, it’s very difficult to know when access to a firm’s internal functions might be critical to the facilitation of a market. It simply cannot be true that a firm becomes bound under onerous essential facilities requirements (or classification as a public utility) simply because other firms find it more convenient to use its services than to develop their own.

The truth of what is actually happening in these cases, however, is that third-party firms are choosing to anchor their business to the processes of another firm which generates an “asset specificity” problem that they then seek the government to remedy:

A content provider that makes itself dependent upon another company for distribution (or vice versa, of course) takes a significant risk. Although it may benefit from greater access to users, it places itself at the mercy of the other — or at least faces great difficulty (and great cost) adapting to unanticipated, crucial changes in distribution over which it has no control.

This is naturally a calculated risk that a firm may choose to make, but it is a risk. To pry open Google or Facebook for the benefit of competitors that choose to play to Google and Facebook’s user base, rather than opening markets of their own, punishes the large players for being successful while also rewarding behavior that shies away from innovation. Further, such a policy would punish the large platforms whenever they innovate with their services in any way that might frustrate third-party “integrators” (see, e.g., Foundem’s claims that Google’s algorithm updates meant to improve search quality for users harmed Foundem’s search rankings).  

Rather than encouraging innovation, blessing this form of asset specificity would have the perverse result of entrenching the status quo.

In all of these recommendations from Senator Warner, there is no claim that any of the targeted firms will have behaved anticompetitively, but merely that they are above a certain size. This is to say that, in some cases, big is bad.

Senator Warner’s policies would harm competition and innovation

As Geoffrey Manne and Gus Hurwitz have recently noted these views run completely counter to the last half-century or more of economic and legal learning that has occurred in antitrust law. From its murky, politically-motivated origins through the early 60’s when the Structure-Conduct-Performance (“SCP”) interpretive framework was ascendant, antitrust law was more or less guided by the gut feeling of regulators that big business necessarily harmed the competitive process.

Thus, at its height with SCP, “big is bad” antitrust relied on presumptions that large firms over a certain arbitrary threshold were harmful and should be subjected to more searching judicial scrutiny when merging or conducting business.

A paradigmatic example of this approach can be found in Von’s Grocery where the Supreme Court prevented the merger of two relatively small grocery chains. Combined, the two chains would have constitutes a mere 9 percent of the market, yet the Supreme Court, relying on the SCP aversion to concentration in itself, prevented the merger despite any procompetitive justifications that would have allowed the combined entity to compete more effectively in a market that was coming to be dominated by large supermarkets.

As Manne and Hurwitz observe: “this decision meant breaking up a merger that did not harm consumers, on the one hand, while preventing firms from remaining competitive in an evolving market by achieving efficient scale, on the other.” And this gets to the central defect of Senator Warner’s proposals. He ties his decisions to interfere in the operations of large tech firms to their size without respect to any demonstrable harm to consumers.

To approach antitrust this way — that is, to roll the clock back to a period before there was a well-defined and administrable standard for antitrust — is to open the door for regulation by political whim. But the value of the contemporary consumer welfare test is that it provides knowable guidance that limits both the undemocratic conduct of politically motivated enforcers as well as the opportunities for private firms to engage in regulatory capture. As Manne and Hurwitz observe:

Perhaps the greatest virtue of the consumer welfare standard is not that it is the best antitrust standard (although it is) — it’s simply that it is a standard. The story of antitrust law for most of the 20th century was one of standard-less enforcement for political ends. It was a tool by which any entrenched industry could harness the force of the state to maintain power or stifle competition.

While it is unlikely that Senator Warner intends to entrench politically powerful incumbents, or enable regulation by whim, those are the likely effects of his proposals.

Antitrust law has a rich set of tools for dealing with competitive harm. Introducing legislation to define arbitrary thresholds for limiting the potential power of firms will ultimately undermine the power of those tools and erode the welfare of consumers.

 

The Economist takes on “sin taxes” in a recent article, “‘Sin’ taxes—eg, on tobacco—are less efficient than they look.” The article has several lessons for policy makers eyeing taxes on e-cigarettes and other vapor products.

Historically, taxes had the key purpose of raising revenues. The “best” taxes would be on goods with few substitutes (i.e., inelastic demand) and on goods deemed to be luxuries. In Wealth of Nations Adam Smith notes:

Sugar, rum, and tobacco are commodities which are nowhere necessaries of life, which are become objects of almost universal consumption, and which are therefore extremely proper subjects of taxation.

The Economist notes in 1764, a fiscal crisis driven by wars in North America led Britain’s parliament began enforcing tariffs on sugar and molasses imported from outside the empire. In the U.S., from 1868 until 1913, 90 percent of all federal revenue came from taxes on liquor, beer, wine and tobacco.

Over time, the rationale for these taxes has shifted toward “sin taxes” designed to nudge consumers away from harmful or distasteful consumption. The Temperance movement in the U.S. argued for higher taxes to discourage alcohol consumption. Since the Surgeon General’s warning on the dangers of smoking, tobacco tax increases have been justified as a way to get smokers to quit. More recently, a perceived obesity epidemic has led several American cities as well as Thailand, Britain, Ireland, South Africa to impose taxes on sugar-sweetened beverages to reduce sugar consumption.

Because demand curves slope down, “sin taxes” do change behavior by reducing the quantity demanded. However, for many products subject to such taxes, demand is not especially responsive. For example, as shown in the figure below, a one percent increase in the price of tobacco is associated with a one-half of one percent decrease in sales.

Economist-Sin-Taxes

 

Substitutability is another consideration for tax policy. An increase in the tax on spirits will result in an increase in beer and wine purchases. A high toll on a road will divert traffic to untolled streets that may not be designed for increased traffic volumes. A spike in tobacco taxes in one state will result in a spike in sales in bordering states as well as increase illegal interstate sales or smuggling. The Economist reports:

After Berkeley introduced its tax, sales of sugary drinks rose by 6.9% in neighbouring cities. Denmark, which instituted a tax on fat-laden foods in 2011, ran into similar problems. The government got rid of the tax a year later when it discovered that many shoppers were buying butter in neighbouring Germany and Sweden.

Advocates of “sin” taxes on tobacco, alcohol, and sugar argue their use impose negative externalities on the public, since governments have to spend more to take care of sick people. With approximately one-third of the U.S. population covered by some form of government funded health insurance, such as Medicare or Medicaid, what were once private costs of healthcare have been transformed into a public cost.

According to Centers for Disease Control and Prevention in U.S., smoking-related illness in the U.S. costs more than $300 billion each year, including; (1) nearly $170 billion for direct medical care for adults and (2) more than $156 billion in lost productivity, including $5.6 billion in lost productivity due to secondhand smoke exposure.

On the other hand, The Economist points out:

Smoking, in contrast, probably saves taxpayers money. Lifelong smoking will bring forward a person’s death by about ten years, which means that smokers tend to die just as they would start drawing from state pensions. In a study published in 2002 Kip Viscusi, an economist at Vanderbilt University who has served as an expert witness on behalf of tobacco companies, estimated that even if tobacco were untaxed, Americans could still expect to save the government an average of 32 cents for every pack of cigarettes they smoke.

The CDC’s cost estimates raise important questions regarding who bears the burden of smoking related illness. For example, much of the direct cost is borne by private insurance, which charge steeper premiums for customers who smoke. In addition, the CDC estimates reflect costs imposed by people who have smoked for decades—many of whom have now quit. A proper accounting of the costs vis-à-vis tax policy should evaluate the discounted costs imposed by today’s smokers.

State and local governments in the U.S. collect more than $18 billion a year in tobacco taxes. While some jurisdictions earmark a portion of tobacco taxes for prevention and cessation efforts, in practice most tobacco taxes are treated by policymakers as general revenues to be spent in whatever way the legislative body determines. Thus, in practice, there is no clear nexus between taxes levied on tobacco and government’s use of the tax revenues on smoking related costs.

Most of the harm from smoking is caused by the inhalation of toxicants released through the combustion of tobacco. Public Health England and the American Cancer Society have concluded non-combustible tobacco products, such as e-cigarettes, “heat-not-burn” products, smokeless tobacco, are considerably less harmful than combustible products.

Many experts believe that the best option for smokers who are unable or unwilling to quit smoking is to switch to a less harmful alternative activity that has similar attributes, such as using non-combustible nicotine delivery products. Policies that encourage smokers to switch from more harmful combustible tobacco products to less harmful non-combustible products would be considered a form of “harm reduction.”

Nine U.S. states now have taxes on vapor products. In addition, several local jurisdictions have enacted taxes. Their methods and levels of taxation vary widely. Policy makers considering a tax on vapor products should account for the following factors.

  • The current market for e-cigarettes as well as heat-not-burn products in the range of 0-10 percent of the cigarette market. Given the relatively small size of the e-cigarette and heated tobacco product market, it is unlikely any level of taxation of e-cigarettes and heated tobacco products would generate significant tax revenues to the taxing jurisdiction. Moreover much of the current research likely represents early adopters and higher income consumer groups. As such, the current empirical data based on total market size and price/tax levels are likely to be far from indicative of the “actual” market for these products.
  • The demand for e-cigarettes is much more responsive to a change in price than the demand for combustible cigarettes. My review of the published research to date finds the median estimated own-price elasticity is -1.096, meaning something close to a 1-to-1 relationship: a tax resulting in a one percent increase in e-cigarette prices would be associated with one percent decline in e-cigarette sales. Many of those lost sales would be shifted to purchases of combustible cigarettes.
  • Research on the price responsiveness of vapor products is relatively new and sparse. There are fewer than a dozen published articles, and the first article was published in 2014. As a result, the literature reports a wide range of estimated elasticities that calls into question the reliability of published estimates, as shown in the figure below. As a relatively unformed area of research, the policy debate would benefit from additional research that involves larger samples with better statistical power, reflects the dynamic nature of this new product category, and accounts for the wide variety of vapor products.

 

With respect to taxation and pricing, policymakers would benefit from reliable information regarding the size of the vapor product market and the degree to which vapor products are substitutes for combustible tobacco products. It may turn out that a tax on vapor products may be, as The Economist notes, less efficient than they look.

Senator Mark Warner has proposed 20 policy prescriptions for bringing “big tech” to heel. The proposals — which run the gamut from policing foreign advertising on social networks to regulating feared competitive harms — provide much interesting material for Congress to consider.

On the positive side, Senator Warner introduces the idea that online platforms may be able to function as least-cost avoiders with respect to certain tortious behavior of their users. He advocates for platforms to implement technology that would help control the spread of content that courts have found violated certain rights of third-parties.

Yet, on other accounts — specifically the imposition of an “interoperability” mandate on platforms — his proposals risk doing more harm than good.

The interoperability mandate was included by Senator Warner in order to “blunt [tech platforms’] ability to leverage their dominance over one market or feature into complementary or adjacent markets or products.” According to Senator Warner, such a measure would enable startups to offset the advantages that arise from network effects on large tech platforms by building their services more easily on the backs of successful incumbents.

Whatever you think of the moats created by network effects, the example of “successful” previous regulation on this issue that Senator Warner relies upon is perplexing:

A prominent template for [imposing interoperability requirements] was in the AOL/Time Warner merger, where the FCC identified instant messaging as the ‘killer app’ – the app so popular and dominant that it would drive consumers to continue to pay for AOL service despite the existence of more innovative and efficient email and internet connectivity services. To address this, the FCC required AOL to make its instant messaging service (AIM, which also included a social graph) interoperable with at least one rival immediately and with two other rivals within 6 months.

But the AOL/Time Warner merger and the FCC’s conditions provide an example that demonstrates the exact opposite of what Senator Warner suggests. The much-feared 2001 megamerger prompted, as the Senator notes, fears that the new company would be able to leverage its dominance in the nascent instant messaging market to extend its influence into adjacent product markets.

Except, by 2003, despite it being unclear that AOL had developed interoperable systems, two large competitors had arisen that did not run interoperable IM networks (Yahoo! and Microsoft). In that same period, AOL’s previously 100% IM market share had declined by about half. By 2009, after eight years of heavy losses, Time Warner shed AOL, and by last year AIM was completely dead.

Not only was it not clear that AOL was able to make AIM interoperable, AIM was never able to catch up once better, rival services launched. What the conditions did do, however, was prevent AOL from launching competitive video chat services as it flailed about in the wake of the deal, thus forcing it to miss out on a market opportunity available to unencumbered competitors like Microsoft and Yahoo!

And all of this of course ignores the practical impossibility entailed in interfering in highly integrated technology platforms.

The AOL/Time Warner merger conditions are no template for successful tech regulation. Congress would be ill-advised to rely upon such templates for crafting policy around tech and innovation.

What to make of Wednesday’s decision by the European Commission alleging that Google has engaged in anticompetitive behavior? In this post, I contrast the European Commission’s (EC) approach to competition policy with US antitrust, briefly explore the history of smartphones and then discuss the ruling.

Asked about the EC’s decision the day it was announced, FTC Chairman Joseph Simons noted that, while the market is concentrated, Apple and Google “compete pretty heavily against each other” with their mobile operating systems, in stark contrast to the way the EC defined the market. Simons also stressed that for the FTC what matters is not the structure of the market per se but whether or not there is harm to the consumer. This again contrasts with the European Commission’s approach, which does not require harm to consumers. As Simons put it:

Once they [the European Commission] find that a company is dominant… that imposes upon the company kind of like a fairness obligation irrespective of what the effect is on the consumer. Our regulatory… our antitrust regime requires that there be a harm to consumer welfare — so the consumer has to be injured — so the two tests are a little bit different.

Indeed, and as the history below shows, the popularity of Apple’s iOS and Google’s Android operating systems arose because they were superior products — not because of anticompetitive conduct on the part of either Apple or Google. On the face of it, the conduct of both Apple and Google has led to consumer benefits, not harms. So, from the perspective of U.S. antitrust authorities, there is no reason to take action.

Moreover, there is a danger that by taking action as the EU has done, competition and innovation will be undermined — which would be a perverse outcome indeed. These concerns were reflected in a statement by Senator Mike Lee (R-UT):

Today’s decision by the European Commission to fine Google over $5 billion and require significant changes to its business model to satisfy EC bureaucrats has the potential to undermine competition and innovation in the United States,” Sen. Lee said. “Moreover, the decision further demonstrates the different approaches to competition policy between U.S. and EC antitrust enforcers. As discussed at the hearing held last December before the Senate’s Subcommittee on Antitrust, Competition Policy & Consumer Rights, U.S. antitrust agencies analyze business practices based on the consumer welfare standard. This analytical framework seeks to protect consumers rather than competitors. A competitive marketplace requires strong antitrust enforcement. However, appropriate competition policy should serve the interests of consumers and not be used as a vehicle by competitors to punish their successful rivals.

Ironically, the fundamental basis for the Commission’s decision is an analytical framework developed by economists at Harvard in the 1950s, which presumes that the structure of a market determines the conduct of the participants, which in turn presumptively affects outcomes for consumers. This “structure-conduct-performance” paradigm has been challenged both theoretically and empirically (and by “challenged,” I mean “demolished”).

Maintaining, as EC Commissioner Vestager has, that “What would serve competition is to have more players,” is to adopt a presumption regarding competition rooted in the structure of the market, without sufficient attention to the facts on the ground. As French economist Jean Tirole noted in his Nobel Prize lecture:

Economists accordingly have advocated a case-by-case or “rule of reason” approach to antitrust, away from rigid “per se” rules (which mechanically either allow or prohibit certain behaviors, ranging from price-fixing agreements to resale price maintenance). The economists’ pragmatic message however comes with a double social responsibility. First, economists must offer a rigorous analysis of how markets work, taking into account both the specificities of particular industries and what regulators do and do not know….

Second, economists must participate in the policy debate…. But of course, the responsibility here goes both ways. Policymakers and the media must also be willing to listen to economists.

In good Tirolean fashion, we begin with an analysis of how the market for smartphones developed. What quickly emerges is that the structure of the market is a function of intense competition, not its absence. And, by extension, mandating a different structure will likely impede competition, or, at the very least, will not likely contribute to it.

A brief history of smartphone competition

In 2006, Nokia’s N70 became the first smartphone to sell more than a million units. It was a beautiful device, with a simple touch screen interface and real push buttons for numbers. The following year, Apple released its first iPhone. It sold 7 million units — about the same as Nokia’s N95 and slightly less than LG’s Shine. Not bad, but paltry compared to the sales of Nokia’s 1200 series phones, which had combined sales of over 250 million that year — about twice the total of all smartphone sales in 2007.

By 2017, smartphones had come to dominate the market, with total sales of over 1.5 billion. At the same time, the structure of the market has changed dramatically. In the first quarter of 2018, Apple’s iPhone X and iPhone 8 were the two best-selling smartphones in the world. In total, Apple shipped just over 52 million phones, accounting for 14.5% of the global market. Samsung, which has a wider range of devices, sold even more: 78 million phones, or 21.7% of the market. At third and fourth place were Huawei (11%) and Xiaomi (7.5%). Nokia and LG didn’t even make it into the top 10, with market shares of only 3% and 1% respectively.

Several factors have driven this highly dynamic market. Dramatic improvements in cellular data networks have played a role. But arguably of greater importance has been the development of software that offers consumers an intuitive and rewarding experience.

Apple’s iOS and Google’s Android operating systems have proven to be enormously popular among both users and app developers. This has generated synergies — or what economists call network externalities — as more apps have been developed, so more people are attracted to the ecosystem and vice versa, leading to a virtuous circle that benefits both users and app developers.

By contrast, Nokia’s early smartphones, including the N70 and N95, ran Symbian, the operating system developed for Psion’s handheld devices, which had a clunkier user interface and was more difficult to code — so it was less attractive to both users and developers. In addition, Symbian lacked an effective means of solving the problem of fragmentation of the operating system across different devices, which made it difficult for developers to create apps that ran across the ecosystem — something both Apple (through its closed system) and Google (through agreements with carriers) were able to address. Meanwhile, Java’s MIDP used in LG’s Shine, and its successor J2ME imposed restrictions on developers (such as prohibiting access to files, hardware, and network connections) that seem to have made it less attractive than Android.

The relative superiority of their operating systems enabled Apple and the manufacturers of Android-based phones to steal a march on the early leaders in the smartphone revolution.

The fact that Google allows smartphone manufacturers to install Android for free, distributes Google Play and other apps in a free bundle, and pays such manufacturers for preferential treatment for Google Search, has also kept the cost of Android-based smartphones down. As a result, Android phones are the cheapest on the market, providing a powerful experience for as little as $50. It is reasonable to conclude from this that innovation, driven by fierce competition, has led to devices, operating systems, and apps that provide enormous benefits to consumers.

The Commission decision would harm device manufacturers, app developers and consumers

The EC’s decision seems to disregard the history of smartphone innovation and competition and their ongoing consequences. As Dirk Auer explains, the Open Handset Alliance (OHA) was created specifically to offer an effective alternative to Apple’s iPhone — and it worked. Indeed, it worked so spectacularly that Android is installed on about 80% of all new phones. This success was the result of several factors that the Commission now seeks to undermine:

First, in order to maintain order within the Android universe, and thereby ensure that apps developed for Android would function on the vast majority of Android devices, Google and the OHA sought to limit the extent to which Android “forks” could be created. (Apple didn’t face this problem because its source code is proprietary, so cannot be modified by third-party developers.) One way Google does this is by imposing restrictions on the licensing of its proprietary apps, such as the Google Play store (a repository of apps, similar to Apple’s App Store).

Device manufacturers that don’t conform to these restrictions may still build devices with their forked version of Android — but without those Google apps. Indeed, Amazon chooses to develop a non-conforming version of Android and built its own app repository for its Fire devices (though it is still possible to add the Google Play Store). That strategy seems to be working for Amazon in the tablet market; in 2017 it rose past Samsung to become the second biggest manufacturer of tablets worldwide, after Apple.

Second, in order to be able to offer Android for free to smartphone manufacturers, Google sought to develop unique revenue streams (because, although the software is offered for free, it turns out that software developers generally don’t work for free). The main way Google did this was by requiring manufacturers that choose to install Google Play also to install its browser (Chrome) and search tools, which generate revenue from advertising. At the same time, Google kept its platform open by permitting preloads of rivals’ apps and creating a marketplace where rivals can also reach scale. Mozilla’s Firefox browser, for example, has been downloaded over 100 million times on Android.

The importance of these factors to the success of Android is acknowledged by the EC. But instead of treating them as legitimate business practices that enabled the development of high-quality, low-cost smartphones and a universe of apps that benefits billions of people, the Commission simply asserts that they are harmful, anticompetitive practices.

For example, the Commission asserts that

In order to be able to pre-install on their devices Google’s proprietary apps, including the Play Store and Google Search, manufacturers had to commit not to develop or sell even a single device running on an Android fork. The Commission found that this conduct was abusive as of 2011, which is the date Google became dominant in the market for app stores for the Android mobile operating system.

This is simply absurd, to say nothing of ahistorical. As noted, the restrictions on Android forks plays an important role in maintaining the coherency of the Android ecosystem. If device manufacturers were able to freely install Google apps (and other apps via the Play Store) on devices running problematic Android forks that were unable to run the apps properly, consumers — and app developers — would be frustrated, Google’s brand would suffer, and the value of the ecosystem would be diminished. Extending this restriction to all devices produced by a specific manufacturer, regardless of whether they come with Google apps preinstalled, reinforces the importance of the prohibition to maintaining the coherency of the ecosystem.

It is ridiculous to say that something (efforts to rein in Android forking) that made perfect sense until 2011 and that was central to the eventual success of Android suddenly becomes “abusive” precisely because of that success — particularly when the pre-2011 efforts were often viewed as insufficient and unsuccessful (a January 2012 Guardian Technology Blog post, “How Google has lost control of Android,” sums it up nicely).

Meanwhile, if Google is unable to tie pre-installation of its search and browser apps to the installation of its app store, then it will have less financial incentive to continue to maintain the Android ecosystem. Or, more likely, it will have to find other ways to generate revenue from the sale of devices in the EU — such as charging device manufacturers for Android or Google Play. The result is that consumers will be harmed, either because the ecosystem will be degraded, or because smartphones will become more expensive.

The troubling absence of Apple from the Commission’s decision

In addition, the EC’s decision is troublesome in other ways. First, for its definition of the market. The ruling asserts that “Through its control over Android, Google is dominant in the worldwide market (excluding China) for licensable smart mobile operating systems, with a market share of more than 95%.” But “licensable smart mobile operating systems” is a very narrow definition, as it necessarily precludes operating systems that are not licensable — such as Apple’s iOS and RIM’s Blackberry OS. Since Apple has nearly 25% of the market share of smartphones in Europe, the European Commission has — through its definition of the market — presumed away the primary source of effective competition. As Pinar Akman has noted:

How can Apple compete with Google in the market as defined by the Commission when Apple allows only itself to use its operating system only on devices that Apple itself manufactures?

The EU then invents a series of claims regarding the lack of competition with Apple:

  • end user purchasing decisions are influenced by a variety of factors (such as hardware features or device brand), which are independent from the mobile operating system;

It is not obvious that this is evidence of a lack of competition. A better explanation is that the EU’s narrow definition of the market is defective. In fact, one could easily draw the opposite conclusion of that drawn by the Commission: the fact that purchasing decisions are driven by various factors suggests that there is substantial competition, with phone manufacturers seeking to design phones that offer a range of features, on a number of dimensions, to best capture diverse consumer preferences. They are able to do this in large part precisely because consumers are able to rely upon a generally similar operating system and continued access to the apps that they have downloaded. As Tim Cook likes to remind his investors, Apple is quite successful at targeting “Android switchers” to switch to iOS.

 

  • Apple devices are typically priced higher than Android devices and may therefore not be accessible to a large part of the Android device user base;

 

And yet, in the first quarter of 2018, Apple phones accounted for five of the top ten selling smartphones worldwide. Meanwhile, several competing phones, including the fifth and sixth best-sellers, Samsung’s Galaxy S9 and S9+, sell for similar prices to the most expensive iPhones. And a refurbished iPhone 6 can be had for less than $150.

 

  • Android device users face switching costs when switching to Apple devices, such as losing their apps, data and contacts, and having to learn how to use a new operating system;

 

This is, of course, true for any system switch. And yet the growing market share of Apple phones suggests that some users are willing to part with those sunk costs. Moreover, the increasing predominance of cloud-based and cross-platform apps, as well as Apple’s own “Move to iOS” Android app (which facilitates the transfer of users’ data from Android to iOS), means that the costs of switching border on trivial. As mentioned above, Tim Cook certainly believes in “Android switchers.”

 

  • even if end users were to switch from Android to Apple devices, this would have limited impact on Google’s core business. That’s because Google Search is set as the default search engine on Apple devices and Apple users are therefore likely to continue using Google Search for their queries.

 

This is perhaps the most bizarre objection of them all. The fact that Apple chooses to install Google search as the default demonstrates that consumers prefer that system over others. Indeed, this highlights a fundamental problem with the Commission’s own rationale, As Akman notes:

It is interesting that the case appears to concern a dominant undertaking leveraging its dominance from a market in which it is dominant (Google Play Store) into another market in which it is also dominant (internet search). As far as this author is aware, most (if not all?) cases of tying in the EU to date concerned tying where the dominant undertaking leveraged its dominance in one market to distort or eliminate competition in an otherwise competitive market.

Conclusion

As the foregoing demonstrates, the EC’s decision is based on a fundamental misunderstanding of the nature and evolution of the market for smartphones and associated applications. The statement by Commissioner Vestager quoted above — that “What would serve competition is to have more players” — belies this misunderstanding and highlights the erroneous assumptions underpinning the Commission’s analysis, which is wedded to a theory of market competition that was long ago thrown out by economists.

And, thankfully, it appears that the FTC Chairman is aware of at least some of the flaws in the EC’s conclusions.

Google will undoubtedly appeal the Commission’s decision. For the sakes of the millions of European consumers who rely on Android-based phones and the millions of software developers who provide Android apps, let’s hope that they succeed.