In the Federal Trade Commission’s recent hearings on competition policy in the 21st century, Georgetown professor Steven Salop urged greater scrutiny of vertical mergers. He argued that regulators should be skeptical of the claim that vertical integration tends to produce efficiencies that can enhance consumer welfare. In his presentation to the FTC, Professor Salop provided what he viewed as exceptions to this long-held theory.
Also, vertical merger efficiencies are not inevitable. I mean, vertical integration is common, but so is vertical non-integration. There is an awful lot of companies that are not vertically integrated. And we have lots of examples in which vertical integration has failed. Pepsi’s acquisition of KFC and Pizza Hut; you know, of course Coca-Cola has not merged with McDonald’s . . . .
Aside from the logical fallacy of cherry picking examples (he also includes Betamax/VHS and the split up of Alcoa and Arconic, as well as “integration and disintegration” “in cable”), Professor Salop misses the fact that PepsiCo’s 20 year venture into restaurants had very little to do with vertical integration.
Popular folklore says PepsiCo got into fast food because it was looking for a way to lock up sales of its fountain sodas. Soda is considered one of the highest margin products sold by restaurants. Vertical integration by a soda manufacturer into restaurants would eliminate double marginalization with the vertically integrated firm reaping most of the gains. The folklore fits nicely with economic theory. But, the facts may not fit the theory.
PepsiCo acquired Pizza Hut in 1977, Taco Bell in 1978, and Kentucky Fried Chicken in 1986. Prior to PepsiCo’s purchase, KFC had been owned by spirits company Heublein and conglomerate RJR Nabisco. This was the period of conglomerates—Pillsbury owned Burger King and General Foods owned Burger Chef (or maybe they were vertically integrated into bun distribution).
In the early 1990s Pepsi also bought California Pizza Kitchen, Chevys Fresh Mex, and D’Angelo Grilled Sandwiches.
In 1997, PepsiCo exited the restaurant business. It spun off Pizza Hut, Taco Bell, and KFC to Tricon Global Restaurants, which would later be renamed Yum! Brands. CPK and Chevy’s were purchased by private equity investors. D’Angelo was sold to Papa Gino’s Holdings, a restaurant chain. Since then, both Chevy’s and Papa Gino’s have filed for bankruptcy and Chevy’s has had some major shake-ups.
Professor Salop’s story focuses on the spin-off as an example of the failure of vertical mergers. But there is also a story of success. PepsiCo was in the restaurant business for two decades. More importantly, it continued its restaurant acquisitions over time. If PepsiCo’s restaurants strategy was a failure, it seems odd that the company would continue acquisitions into the early 1990s.
It’s easy, and largely correct, to conclude that PepsiCo’s restaurant acquisitions involved some degree of vertical integration, with upstream PepsiCo selling beverages to downstream restaurants. At the time PepsiCo bought Kentucky Fried Chicken, the New York Times reported KFC was Coke’s second-largest fountain account, behind McDonald’s.
But, what if vertical efficiencies were not the primary reason for the acquisitions?
Growth in U.S. carbonated beverage sales began slowing in the 1970s. It was also the “decade of the fast-food business.” From 1971 to 1977, Pizza Hut’s profits grew an average of 40% per year. Colonel Sanders sold his ownership in KFC for $2 million in 1964. Seven years later, the company was sold to Heublein for $280 million; PepsiCo paid $850 million in 1986.
Although KFC was Coke’s second largest customer at the time, about 20% of KFC’s stores served Pepsi products, “PepsiCo stressed that the major reason for the acquisition was to expand its restaurant business, which last year accounted for 26 percent of its revenues of $8.1 billion,” according to the New York Times.
Viewed in this light, portfolio diversification goes a much longer way toward explaining PepsiCo’s restaurant purchases than hoped-for vertical efficiencies. In 1997, former PepsiCo chairman Roger Enrico explained to investment analysts that the company entered the restaurant business in the first place, “because it didn’t see future growth in its soft drink and snack” businesses and thought diversification into restaurants would provide expansion opportunities.
Prior to its Pizza Hut and Taco Bell acquisitions, PepsiCo owned companies as diverse as Frito-Lay, North American Van Lines, Wilson Sporting Goods, and Rheingold Brewery. This further supports a diversification theory rather than a vertical integration theory of PepsiCo’s restaurant purchases.
The mid 1990s and early 2000s were tough times for restaurants. Consumers were demanding healthier foods and fast foods were considered the worst of the worst. This was when Kentucky Fried Chicken rebranded as KFC. Debt hangovers from the leveraged buyout era added financial pressure. Many restaurant groups were filing for bankruptcy and competition intensified among fast food companies. PepsiCo’s restaurants could not cover their cost of capital, and what was once a profitable diversification strategy became a financial albatross, so the restaurants were spun off.
Thus, it seems more reasonable to conclude PepsiCo’s exit from restaurants was driven more by market exigencies than by a failure to achieve vertical efficiencies. While the folklore of locking up distribution channels to eliminate double marginalization fits nicely with theory, the facts suggest a more mundane model of a firm scrambling to deliver shareholder wealth through diversification in the face of changing competition.
If a firm is too big, it will be because it is “a merger for monopoly”;
If the firms aren’t that big, it will be for “coordinated effects”;
If a firm is small, then it will be because it will “eliminate a maverick”.
It’s a version of Ronald Coase’s complaint about antitrust, asrelated by William Landes:
Ronald said he had gotten tired of antitrust because when the prices went up the judges said it was monopoly, when the prices went down, they said it was predatory pricing, and when they stayed the same, they said it was tacit collusion.
Of all the reasons to block a merger, the maverick notion is the weakest, and it’s well past time to ditch it.
TheHorizontal Merger Guidelines define a “maverick” as “a firm that plays a disruptive role in the market to the benefit of customers.” According to the Guidelines, this includes firms:
With a new technology or business model that threatens to disrupt market conditions;
With an incentive to take the lead in price cutting or other competitive conduct or to resist increases in industry prices;
That resist otherwise prevailing industry norms to cooperate on price setting or other terms of competition; and/or
With an ability and incentive to expand production rapidly using available capacity to “discipline prices.”
There appears to be no formal model of maverick behavior that does not rely on some a priori assumption that the firm is a maverick.
For example, John Kwoka’s 1989model assumes the maverick firm has different beliefs about how competing firms would react if the maverick varies its output or price. Louis Kaplow and Carl Shapiro developed a simplemodel in which the firm with the smallest market share may play the role of a maverick. They note, however, that this raises the question—in a model in which every firm faces the same cost and demand conditions—why would there be any variation in market shares? The common solution, according to Kaplow and Shapiro, is cost asymmetries among firms. If that is the case, then “maverick” activity is merely a function of cost, rather than some uniquely maverick-like behavior.
The idea of the maverick firm requires that the firm play a critical role in the market. The maverick must be the firm that outflanks coordinated action or acts as a bulwark against unilateral action. By this loosey goosey definition of maverick, a single firm can make the difference between success or failure of anticompetitive behavior by its competitors. Thus, the ability and incentive to expand production rapidly is a necessary condition for a firm to be considered a maverick. For example, Kaplow and Shapiroexplain:
Of particular note is the temptation of one relatively small firm to decline to participate in the collusive arrangement or secretly to cut prices to serve, say, 4% rather than 2% of the market. As long as price cuts by a small firm are less likely to be accurately observed or inferred by the other firms than are price cuts by larger firms, the presence of small firms that are capable of expanding significantly is especially disruptive to effective collusion.
A “maverick” firm’s ability to “discipline prices” depends crucially on its ability to expand output in the face of increased demand for its products. Similarly, the other non-maverick firms can be “disciplined” by the maverick only in the face of a credible threat of (1) a noticeable drop in market share that (2) leads to lower profits.
Relying on its disruptive pricing plans, its improved high-speed HSPA+ network, and a variety of other initiatives, T-Mobile aimed to grow its nationwide share to 17 percent within the next several years, and to substantially increase its presence in the enterprise and government market. AT&T’s acquisition of T-Mobile would eliminate the important price, quality, product variety, and innovation competition that an independent T-Mobile brings to the marketplace.
At the time of the proposed merger, T-Mobileaccounted for 11% of U.S. wireless subscribers. At the end of 2016, its market share had hit 17%. About half of the increase can be attributed to its 2012 merger with MetroPCS. Over the same period, Verizon’s market share increased from 33% to 35% and AT&T market share remained stable at 32%. It appears that T-Mobile’s so-called maverick behavior did more to disrupt the market shares of smaller competitors Sprint and Leap (which was acquired by AT&T). Thus, it is not clear, ex post, that T-Mobile posed any threat to AT&T or Verizon’s market shares.
Geoffrey Manne raised somequestions about the government’s maverick theory which also highlights a fundamental problem with the willy nilly way in which firms are given the maverick label:
. . . it’s just not enough that a firm may be offering products at a lower price—there is nothing “maverick-y” about a firm that offers a different, less valuable product at a lower price. I have seen no evidence to suggest that T-Mobile offered the kind of pricing constraint on AT&T that would be required to make it out to be a maverick.
While T-Mobile had a reputation for lower mobile prices, in 2011, the firm waslagging behind Verizon, Sprint, and AT&T in the rollout of 4G technology. In other words, T-Mobile was offering an inferior product at a lower price. That’s not a maverick, that’s product differentiation with hedonic pricing.
More recently, in his opposition to the proposed T-Mobile/Sprint merger, Gene Kimmelman from Public Knowledgeasserts that both firms are mavericks and their combination would cause their maverick magic to disappear:
Sprint, also, can be seen as a maverick. It has offered “unlimited” plans and simplified its rate plans, for instance, driving the rest of the industry forward to more consumer-friendly options. As Sprint CEO Marcelo Claure stated, “Sprint and T-Mobile have similar DNA and have eliminated confusing rate plans, converging into one rate plan: Unlimited.” Whether both or just one of the companies can be seen as a “maverick” today, in either case the newly combined company would simply have the same structural incentives as the larger carriers both Sprint and T-Mobile today work so hard to differentiate themselves from.
Kimmelman provides no mechanism by which the magic would go missing, but instead offers a version of an adversity-builds-character argument:
Allowing T-Mobile to grow to approximately the same size as AT&T, rather than forcing it to fight for customers, will eliminate the combined company’s need to disrupt the market and create an incentive to maintain the existing market structure.
For 30 years, the notion of the maverick firm has been a concept in search of a model. If the concept cannot be modeled decades after being introduced, maybe the maverick can’t be modeled.
What’s left are ad hoc assertions mixed with speculative projections in hopes that some sympathetic judge can be swayed. However, some judges seem to be more skeptical than sympathetic, as inH&R Block/TaxACT :
The parties have spilled substantial ink debating TaxACT’s maverick status. The arguments over whether TaxACT is or is not a “maverick” — or whether perhaps it once was a maverick but has not been a maverick recently — have not been particularly helpful to the Court’s analysis. The government even put forward as supposed evidence a TaxACT promotional press release in which the company described itself as a “maverick.” This type of evidence amounts to little more than a game of semantic gotcha. Here, the record is clear that while TaxACT has been an aggressive and innovative competitor in the market, as defendants admit, TaxACT is not unique in this role. Other competitors, including HRB and Intuit, have also been aggressive and innovative in forcing companies in the DDIY market to respond to new product offerings to the benefit of consumers.
It’s time to send the maverick out of town and into the sunset.
Thomas Wollmann has a new paper — “Stealth Consolidation: Evidence from an Amendment to the Hart-Scott-Rodino Act” — in American Economic Review: Insights this month. Greg Ip included this research in an article for the WSJ in which he claims that “competition has declined and corporate concentration risen through acquisitions often too small to draw the scrutiny of antitrust watchdogs.” In other words, “stealth consolidation”.
Wollmann’s study uses a difference-in-differences approach to examine the effect on merger activity of the 2001 amendment to the Hart-Scott-Rodino (HSR) Antitrust Improvements Act of 1976 (15 U.S.C. 18a). The amendment abruptly increased the pre-merger notification threshold from $15 million to $50 million in deal size. Strictly on those terms, the paper shows that raising the pre-merger notification threshold increased merger activity.
However, claims about “stealth consolidation” are controversial because they connote nefarious intentions and anticompetitive effects. As Wollmann admits in the paper, due to data limitations, he is unable to show that the new mergers are in fact anticompetitive or that the social costs of these mergers exceed the social benefits. Therefore, more research is needed to determine the optimal threshold for pre-merger notification rules, and claiming that harmful “stealth consolidation” is occurring is currently unwarranted.
Background: The “Unscrambling the Egg” Problem
In general, it is more difficult to unwind a consummated anticompetitive merger than it is to block a prospective anticompetitive merger. As Wollmann notes, for example, “El Paso Natural Gas Co. acquired its only potential rival in a market” and “the government’s challenge lasted 17 years and involved seven trips to the Supreme Court.”
Rolling back an anticompetitive merger is so difficult that it came to be known as “unscrambling the egg.” As William J. Baer, a former director of the Bureau of Competition at the FTC, described it, “there were strong incentives for speedily and surreptitiously consummating suspect mergers and then protracting the ensuing litigation” prior to the implementation of a pre-merger notification rule. These so-called “midnight mergers” were intended to avoid drawing antitrust scrutiny.
In 2001, Congress amended the HSR Act and effectively raised the threshold for premerger notification from $15 million in acquired firm assets to $50 million. This sudden and dramatic change created an opportunity to use a difference-in-differences technique to study the relationship between filing an HSR notification and merger activity.
According to Wollmann, here’s what notifications look like for never-exempt mergers (>$50M):
And here’s what notifications for newly-exempt ($15M < X < $50M) mergers look like:
So what does that mean for merger investigations? Here is the number of investigations into never-exempt mergers:
We see a pretty consistent relationship between number of mergers and number of investigations. More mergers means more investigations.
How about for newly-exempt mergers?
Here, investigations go to zero while merger activity remains relatively stable. In other words, it appears that some mergers that would have been investigated had they required an HSR notification were not investigated.
Wollmann then uses four-digit SIC code industries to sort mergers into horizontal and non-horizontal categories. Here are never-exempt mergers:
He finds that almost all of the increase in merger activity (relative to the counterfactual in which the notification threshold were unchanged) is driven by horizontal mergers. And here are newly-exempt mergers:
Policy Implications & Limitations
The charts show a stark change in investigations and merger activity. The difference-in-differences methodology is solid and the author addresses some potential confounding variables (such as presidential elections). However, the paper leaves the broader implications for public policy unanswered.
Furthermore, given the limits of the data in this analysis, it’s not possible for this approach to explain competitive effects in the relevant antitrust markets, for three reasons:
Four-digit SIC code industries are not antitrust markets
Wollmann chose to classify mergers “as horizontal or non-horizontal based on whether or not the target and acquirer operate in the same four-digit SIC code industry, which is common convention.” But as Werden & Froeb (2018) notes, four-digit SIC code industries are orders of magnitude too large in most cases to be useful for antitrust analysis:
The evidence from cartel cases focused on indictments from 1970–80. Because the Justice Department prosecuted many local cartels, for 52 of the 80 indictments examined, the Commerce Quotient was less than 0.01, i.e., the SIC 4-digit industry was at least 100 times the apparent scope of the affected market. Of the 80 indictments, 19 involved SIC 4-digit industries that had been thought to comport well with markets, so these were the most instructive. For 16 of the 19, the SIC 4-digit industry was at least 10 times the apparent scope of the affected market (i.e., the Commerce Quotient was less than 0.1).
Antitrust authorities do not rely on SIC 4-digit industry codes and instead establish a market definition based on the facts of each case. It is not possible to infer competitive effects from census data as Wollmann attempts to do.
The data cannot distinguish between anticompetitive mergers and procompetitive mergers
As Wollmann himself notes, the results tell us nothing about the relative costs and benefits of the new HSR policy:
Even so, these findings do not on their own advocate for one policy over another. To do so requires equating industry consolidation to a specific amount of economic harm and then comparing the resulting figure to the benefits derived from raising thresholds, which could be large. Even if the agencies ignore the reduced regulatory burden on firms, introducing exemptions can free up agency resources to pursue other cases (or reduce public spending). These and related issues require careful consideration but simply fall outside the scope of the present work.
For instance, firms could be reallocating merger activity to targets below the new threshold to avoid erroneous enforcement or they could be increasing merger activity for small targets due to reduced regulatory costs and uncertainty.
The study is likely underpowered for effects on blocked mergers
While the paper provides convincing evidence that investigations of newly-exempt mergers decreased dramatically following the change in the notification threshold, there is no equally convincing evidence of an effect on blocked mergers. As Wollmann points out, blocked mergers were exceedingly rare both before and after the Amendment (emphasis added):
Over 57,000 mergers comprise the sample, which spans eighteen years. The mean number of mergers each year is 3,180. The DOJ and FTC receive 31,464 notifications over this period, or 1,748 per year. Also, as stated above, blocked mergers are very infrequent: there are on average 13 per year pre-Amendment and 9 per-year post-Amendment.
Since blocked mergers are such a small percentage of total mergers both before and after the Amendment, we likely cannot tell from the data whether actual enforcement action changed significantly due to the change in notification threshold.
Greg Ip’s write-up for the WSJ includes some relevant charts for this issue. Ironically for a piece about the problems of lax merger review, the accompanying graphs show merger enforcement actions slightly increasing at both the FTC and the DOJ since 2001:
Overall, Wollmann’s paper does an effective job showing how changes in premerger notification rules can affect merger activity. However, due to data limitations, we cannot conclude anything about competitive effects or enforcement intensity from this study.
Will the merger between T-Mobile and Sprint make consumers better or worse off? A central question in the review of this merger—as it is in all merger reviews—is the likely effects that the transaction will have on consumers. In this post, we look at one study that opponents of the merger have been using to support their claim that the merger will harm consumers.
Along with my earlier posts on data problems and public policy (1, 2, 3, 4, 5), this provides an opportunity to explore why seemingly compelling studies can be used to muddy the discussion and fool observers into seeing something that isn’t there.
This merger—between the third and fourth largest mobile wireless providers in the United States—has been characterized as a “4-to-3” merger, on the grounds that it will reduce the number of large, ostensibly national carriers from four to three. This, in turn, has led to concerns that further concentration in the wireless telecommunications industry will harm consumers. Specifically, some opponents of the merger claim that “it’s going to be hard for someone to make a persuasive case that reducing four firms to three is actually going to improve competition for the benefit of American consumers.”
A number of previous mergers around the world can or have also been characterized as 4-to-3 mergers in the wireless telecommunications industry. Several econometric studies have attempted to evaluate the welfare effects of 4-to-3 mergers in other countries, as well as the effects of market concentration in the wireless industry more generally. These studies have been used by both proponents and opponents of the proposed merger of T-Mobile and Sprint to support their respective contentions that the merger will benefit or harm consumer welfare.
One particular study has risen to prominence among opponents of 4-to-3 mergers in telecom in general and the T-Mobile/Sprint merger in specific. This is worrying because the study has several fundamental flaws.
This study, by Finnish consultancy Rewheel, has been cited by, among others, Phillip Berenbroick of Public Knowledge, who in Senate testimony, asserted that “Rewheel found that consumers in markets with three facilities-based providers paid twice as much per gigabyte as consumers in four firm markets.”
The Rewheel report upon which Mr. Berenbroick relied, is, however, marred by a number of significant flaws, which undermine its usefulness.
The Rewheel report
Rewheel’s report purports to analyze the state of 4G pricing across 41 countries that are either members of the EU or the OECD or both. The report’s conclusions are based mainly on two measures:
Estimates of the maximum number of gigabytes available under each plan for a specific hypothetical monthly price, ranging from €5 to €80 a month. In other words, for each plan, Rewheel asks, “How many 4G gigabytes would X euros buy?” Rewheel then ranks countries by the median amount of gigabytes available at each hypothetical price for all the plans surveyed in each country.
Estimates of what Rewheel describes as “fully allocated gigabyte prices.” This is the monthly retail price (including VAT) divided by the number of gigabytes included in each plan. Rewheel then ranks countries by the median price per gigabyte across all the plans surveyed in each country.
Rewheel’s convoluted calculations
Rewheel’s use of the country median across all plans is problematic. In particular it gives all plans equal weight, regardless of consumers’ use of each plan. For example, a plan targeted for a consumer with a “high” level of usage is included with a plan targeted for a consumer with a “low” level of usage. Even though a “high” user would not purchase a “low” plan (which would be relatively expensive for a “high” user), all plans are included, thereby skewing upward the median estimates.
But even if that approach made sense as a way of measuring consumers’ willingness to pay, in execution Rewheel’s analysis contains the following key defects:
The Rewheel report is essentially limited to quantity effects alone (i.e., how many gigabytes available under each plan for a given hypothetical price) or price effects alone (i.e., price per included gigabyte for each plan). These measures can mislead the analysis by missing, among other things, innovation and quality effects.
Rewheel’s analysis is not based on an impartial assessment of relevant price data. Rather, it is based on hypothetical measures. Such comparisons say nothing about the plans actually chosen by consumers or the actual prices paid by consumers in those countries, rendering Rewheel’s comparisons virtually meaningless. As Affeldt & Nitsche (2014) note in their assessment of the effects of concentration in mobile telecom markets:
Such approaches are taken by Rewheel (2013) and also the Austrian regulator rtr (when tracking prices over time, see rtr (2014)). Such studies face the following problems: They may pick tariffs that are relatively meaningless in the country. They will have to assume one or more consumption baskets (voice minutes, data volume etc.) in order to compare tariffs. This may drive results. Apart from these difficulties such comparisons require very careful tracking of tariffs and their changes. Even if one assumes studying a sample of tariffs is potentially meaningful, a comparison across countries (or over time) would still require taking into account key differences across countries (or over time) like differences in demand, costs, network quality etc.
The Rewheel report bases its comparison on dissimilar service levels by not taking into account, for instance, relevant features like comparable network capacity, service security, and, perhaps most important, overall quality of service.
Rewheel’s unsupported conclusions
Rewheel uses its analysis to come to some strong conclusions, such as the conclusion on the first page of its report declaring the median gigabyte price in countries with three carriers is twice as high as in countries with four carriers.
The figure below is a revised version of the figure on the first page of Rewheel’s report. The yellow blocks (gray dots) show the range of prices in countries with three carriers the blue blocks (pink dots) shows the range of prices in countries with four carriers. The darker blocks show the overlap of the two. The figure makes clear that there is substantial overlap in pricing among three and four carrier countries. Thus, it is not obvious that three carrier countries have significantly higher prices (as measured by Rewheel) than four carrier countries.
A simple “eyeballing” of the data can lead to incorrect conclusions, in which case statistical analysis can provide some more certainty (or, at least, some measure of uncertainty). Yet, Rewheel provides no statistical analysis of its calculations, such as measures of statistical significance. However, information on page 5 of the Rewheel report can be used to perform some rudimentary statistical analysis.
I took the information from the columns for hypothetical monthly prices of €30 a month and €50 a month, and converted data into a price per gigabyte to generate the dependent variable. Following Rewheel’s assumption, “unlimited” is converted to 250 gigabytes per month. Greece was dropped from the analysis because Rewheel indicates that no data is available at either hypothetical price level.
My rudimentary statistical analysis includes the following independent variables:
Number of carriers (or mobile network operators, MNOs) reported by Rewheel in each country, ranging from three to five. Israel is the only country with five MNOs.
A dummy variable for EU28 countries. Rewheel performs separate analysis for EU28 countries, suggesting they think this is an important distinction.
GDP per capita for each country, adjusted for purchasing power parity. Several articles in the literature suggest higher GDP countries would be expected to have higher wireless prices.
Population density, measured by persons per square kilometer. Several articles in the literature argue that countries with lower population density would have higher costs of providing wireless service which would, in turn, be reflected in higher prices.
The tables below confirm what an eyeballing of the figure suggest: Rewheel’s data show number of MNOs in a country have no statistically significant relationship with price per gigabyte, at either the €30 a month level or the €50 a month level.
While the signs on the MNO coefficient are negative (i.e., more carriers in a country is associated with lower prices), they are not statistically significantly different from zero at any of the traditional levels of statistical significance.
Also, the regressions suffer from relatively low measures of goodness-of-fit. The independent variables in the regression explain approximately five percent of the variation in the price per gigabyte. This is likely because of the cockamamie way Rewheel measures price, but is also due to the known problems with performing cross-sectional analysis of wireless pricing, as noted by Csorba & Pápai (2015):
Many regulatory policies are based on a comparison of prices between European countries, but these simple cross-sectional analyses can lead to misleading conclusions because of at least two reasons. First, the price difference between countries of n and (n + 1) active mobile operators can be due to other factors, and the analyst can never be sure of having solved the omitted variable bias problem. Second and more importantly, the effect of an additional operator estimated from a cross-sectional comparison cannot be equated with the effect of an actual entry that might have a long-lasting effect on a single market.
The Rewheel report cannot be relied upon in assessing consumer benefits or harm associated with the T-Mobile/Sprint merger, or any other merger
Rewheel apparently has a rich dataset of wireless pricing plans. Nevertheless, the analyses presented in its report are fundamentally flawed. Moreover, Rewheel’s conclusions regarding three vs. four carrier countries are not only baseless, but clearly unsupported by closer inspection of the information presented in its report. The Rewheel report cannot be relied upon to inform regulatory oversight of the T-Mobile/Spring merger or any other. This study isn’t unique and it should serve as a caution to be wary of studies that merely eyeball information.
[TOTM: The following is the third in a series of posts by TOTM guests and authors on the FTC v. Qualcomm case, currently awaiting decision by Judge Lucy Koh in the Northern District of California. The entire series of posts is available here.
This post is authored by Douglas H. Ginsburg, Professor of Law, Antonin Scalia Law School at George Mason University; Senior Judge, United States Court of Appeals for the District of Columbia Circuit; and former Assistant Attorney General in charge of the Antitrust Division of the U.S. Department of Justice; and Joshua D. Wright, University Professor, Antonin Scalia Law School at George Mason University; Executive Director, Global Antitrust Institute; former U.S. Federal Trade Commissioner from 2013-15; and one of the founding bloggers at Truth on the Market.]
[Ginsburg & Wright: Professor Wright is recused from participation in the FTC litigation against Qualcomm, but has provided counseling advice to Qualcomm concerning other regulatory and competition matters. The views expressed here are our own and neither author received financial support.]
The Department of Justice Antitrust Division (DOJ) and Federal Trade Commission (FTC) have spent a significant amount of time in federal court litigating major cases premised upon an anticompetitive foreclosure theory of harm. Bargaining models, a tool used commonly in foreclosure cases, have been essential to the government’s theory of harm in these cases. In vertical merger or conduct cases, the core theory of harm is usually a variant of the claim that the transaction (or conduct) strengthens the firm’s incentives to engage in anticompetitive strategies that depend on negotiations with input suppliers. Bargaining models are a key element of the agency’s attempt to establish those claims and to predict whether and how firm incentives will affect negotiations with input suppliers, and, ultimately, the impact on equilibrium prices and output. Application of bargaining models played a key role in evaluating the anticompetitive foreclosure theories in the DOJ’s litigation to block the proposed merger of AT&T and Time Warner Cable. A similar model is at the center of the FTC’s antitrust claims against Qualcomm and its patent licensing business model.
Modern antitrust analysis does not condemn business practices as anticompetitive without solid economic evidence of an actual or likely harm to competition. This cautious approach was developed in the courts for two reasons. The first is that the difficulty of distinguishing between procompetitive and anticompetitive explanations for the same conduct suggests there is a high risk of error. The second is that those errors are more likely to be false positives than false negatives because empirical evidence and judicial learning have established that unilateral conduct is usually either procompetitive or competitively neutral. In other words, while the risk of anticompetitive foreclosure is real, courts have sensibly responded by requiring plaintiffs to substantiate their claims with more than just theory or scant evidence that rivals have been harmed.
An economic model can help establish the likelihood and/or magnitude of competitive harm when the model carefully captures the key institutional features of the competition it attempts to explain. Naturally, this tends to mean that the economic theories and models proffered by dueling economic experts to predict competitive effects take center stage in antitrust disputes. The persuasiveness of an economic model turns on the robustness of its assumptions about the underlying market. Model predictions that are inconsistent with actual market evidence give one serious pause before accepting the results as reliable.
For example, many industries are characterized by bargaining between providers and distributors. The Nash bargaining framework can be used to predict the outcomes of bilateral negotiations based upon each party’s bargaining leverage. The model assumes that both parties are better off if an agreement is reached, but that as the utility of one party’s outside option increases relative to the bargain, it will capture an increasing share of the surplus. Courts have had to reconcile these seemingly complicated economic models with prior case law and, in some cases, with direct evidence that is apparently inconsistent with the results of the model.
Indeed, Professor Carl Shapiro recently used bargaining models to analyze harm to competition in two prominent cases alleging anticompetitive foreclosure—one initiated by the DOJ and one by the FTC—in which he served as the government’s expert economist. In United States v. AT&T Inc., Dr. Shapiro testified that the proposed transaction between AT&T and Time Warner would give the vertically integrated company leverage to extract higher prices for content from AT&T’s rival, Dish Network. Soon after, Dr. Shapiro presented a similar bargaining model in FTC v. Qualcomm Inc. He testified that Qualcomm leveraged its monopoly power over chipsets to extract higher royalty rates from smartphone OEMs, such as Apple, wishing to license its standard essential patents (SEPs). In each case, Dr. Shapiro’s models were criticized heavily by the defendants’ expert economists for ignoring market realities that play an important role in determining whether the challenged conduct was likely to harm competition.
Judge Leon’s opinion in AT&T/Time Warner—recently upheld on appeal—concluded that Dr. Shapiro’s application of the bargaining model was significantly flawed, based upon unreliable inputs, and undermined by evidence about actual market performance presented by defendant’s expert, Dr. Dennis Carlton. Dr. Shapiro’s theory of harm posited that the combined company would increase its bargaining leverage and extract greater affiliate fees for Turner content from AT&T’s distributor rivals. The increase in bargaining leverage was made possible by the threat of a post-merger blackout of Turner content for AT&T’s rivals. This theory rested on the assumption that the combined firm would have reduced financial exposure from a long-term blackout of Turner content and would therefore have more leverage to threaten a blackout in content negotiations. The purpose of his bargaining model was to quantify how much AT&T could extract from competitors subjected to a long-term blackout of Turner content.
Judge Leon highlighted a number of reasons for rejecting the DOJ’s argument. First, Dr. Shapiro’s model failed to account for existing long-term affiliate contracts, post-litigation offers of arbitration agreements, and the increasing competitiveness of the video programming and distribution industry. Second, Dr. Carlton had demonstrated persuasively that previous vertical integration in the video programming and distribution industry did not have a significant effect on content prices. Finally, Dr. Shapiro’s model primarily relied upon three inputs: (1) the total number of subscribers the unaffiliated distributor would lose in the event of a long-term blackout of Turner content, (2) the percentage of the distributor’s lost subscribers who would switch to AT&T as a result of the blackout, and (3) the profit margin AT&T would derive from the subscribers it gained from the blackout. Many of Dr. Shapiro’s inputs necessarily relied on critical assumptions and/or third-party sources. Judge Leon considered and discredited each input in turn.
The parties in Qualcomm are, as of the time of this posting, still awaiting a ruling. Dr. Shapiro’s model in that case attempts to predict the effect of Qualcomm’s alleged “no license, no chips” policy. He compared the gains from trade OEMs receive when they purchase a chip from Qualcomm and pay Qualcomm a FRAND royalty to license its SEPs with the gains from trade OEMs receive when they purchase a chip from a rival manufacturer and pay a “royalty surcharge” to Qualcomm to license its SEPs. In other words, the FTC’s theory of harm is based upon the premise that Qualcomm is charging a supra-FRAND rate for its SEPs (the“royalty surcharge”) that squeezes the margins of OEMs. That margin squeeze, the FTC alleges, prevents rival chipset suppliers from obtaining a sufficient return when negotiating with OEMs. The FTC predicts the end result is a reduction in competition and an increase in the price of devices to consumers.
Qualcomm, like Judge Leon in AT&T, questioned the robustness of Dr. Shapiro’s model and its predictions in light of conflicting market realities. For example, Dr. Shapiro, argued that the
leverage that Qualcomm brought to bear on the chips shifted the licensing negotiations substantially in Qualcomm’s favor and led to a significantly higher royalty than Qualcomm would otherwise have been able to achieve.
Yet, on cross-examination, Dr. Shapiro declined to move from theory to empirics when asked if he had quantified the effects of Qualcomm’s practice on any other chip makers. Instead, Dr. Shapiro responded that he had not, but he had “reason to believe that the royalty surcharge was substantial” and had “inevitable consequences.” Under Dr. Shapiro’s theory, one would predict that royalty rates were higher after Qualcomm obtained market power.
As with Dr. Carlton’s testimony inviting Judge Leon to square the DOJ’s theory with conflicting historical facts in the industry, Qualcomm’s economic expert, Dr. Aviv Nevo, provided an analysis of Qualcomm’s royalty agreements from 1990-2017, confirming that there was no economic and meaningful difference between the royalty rates during the time frame when Qualcomm was alleged to have market power and the royalty rates outside of that time frame. He also presented evidence that ex ante royalty rates did not increase upon implementation of the CDMA standard or the LTE standard. Moreover, Dr.Nevo testified that the industry itself was characterized by declining prices and increasing output and quality.
Dr. Shapiro’s model in Qualcomm appears to suffer from many of the same flaws that ultimately discredited his model in AT&T/Time Warner: It is based upon assumptions that are contrary to real-world evidence and it does not robustly or persuasively identify anticompetitive effects. Some observers, including our Scalia Law School colleague and former FTC Chairman, Tim Muris, would apparently find it sufficient merely to allege a theoretical “ability to manipulate the marketplace.” But antitrust cases require actual evidence of harm. We think Professor Muris instead captured the appropriate standard in his important article rejecting attempts by the FTC to shortcut its requirement of proof in monopolization cases:
This article does reject, however, the FTC’s attempt to make it easier for the government to prevail in Section 2 litigation. Although the case law is hardly a model of clarity, one point that is settled is that injury to competitors by itself is not a sufficient basis to assume injury to competition …. Inferences of competitive injury are, of course, the heart of per se condemnation under the rule of reason. Although long a staple of Section 1, such truncation has never been a part of Section 2. In an economy as dynamic as ours, now is hardly the time to short-circuit Section 2 cases. The long, and often sorry, history of monopolization in the courts reveals far too many mistakes even without truncation.
Timothy J. Muris, The FTC and the Law of Monopolization, 67 Antitrust L. J. 693 (2000)
We agree. Proof of actual anticompetitive effects rather than speculation derived from models that are not robust to market realities are an important safeguard to ensure that Section 2 protects competition and not merely individual competitors.
The future of bargaining models in antitrust remains to be seen. Judge Leon certainly did not question the proposition that they could play an important role in other cases. Judge Leon closely dissected the testimony and models presented by both experts in AT&T/Time Warner. His opinion serves as an important reminder. As complex economic evidence like bargaining models become more common in antitrust litigation, judges must carefully engage with the experts on both sides to determine whether there is direct evidence on the likely competitive effects of the challenged conduct. Where “real-world evidence,” as Judge Leon called it, contradicts the predictions of a bargaining model, judges should reject the model rather than the reality. Bargaining models have many potentially important antitrust applications including horizontal mergers involving a bargaining component – such as hospital mergers, vertical mergers, and licensing disputes. The analysis of those models by the Ninth and D.C. Circuits will have important implications for how they will be deployed by the agencies and parties moving forward.
First, [my administration would restore competition to the tech sector] by passing legislation that requires large tech platforms to be designated as “Platform Utilities” and broken apart from any participant on that platform.
* * *
For smaller companies…, their platform utilities would be required to meet the same standard of fair, reasonable, and nondiscriminatory dealing with users, but would not be required to structurally separate….
* * * Second, my administration would appoint regulators committed to reversing illegal and anti-competitive tech mergers…. I will appoint regulators who are committed to… unwind[ing] anti-competitive mergers, including:
Let’s consider for a moment what this brave new world will look like — not the nirvana imagined by regulators and legislators who believe that decimating a company’s business model will deter only the “bad” aspects of the model while preserving the “good,” as if by magic, but the inevitable reality of antitrust populism.
Utilities? Are you kidding? For an overview of what the future of tech would look like under Warren’s “Platform Utility” policy, take a look at your water, electricity, and sewage service. Have you noticed any improvement (or reduction in cost) in those services over the past 10 or 15 years? How about the roads? Amtrak? Platform businesses operating under a similar regulatory regime would also similarly stagnate. Enforcing platform “neutrality” necessarily requires meddling in the most minute of business decisions, inevitably creating unintended and costly consequences along the way.
Network companies, like all businesses, differentiate themselves by offering unique bundles of services to customers. By definition, this means vertically integrating with some product markets and not others. Why are digital assistants like Siri bundled into mobile operating systems? Why aren’t the vast majority of third-party apps also bundled into the OS? If you want utilities regulators instead of Google or Apple engineers and designers making these decisions on the margin, then Warren’s “Platform Utility” policy is the way to go.
Grocery Stores. To take one specific case cited by Warren, how much innovation was there in the grocery store industry before Amazon bought Whole Foods? Since the acquisition, large grocery retailers, like Walmart and Kroger, have increased their investment in online services to better compete with the e-commerce champion. Many industry analysts expect grocery stores to use computer vision technology and artificial intelligence to improve the efficiency of check-out in the near future.
Smartphones. Imagine how forced neutrality would play out in the context of iPhones. If Apple can’t sell its own apps, it also can’t pre-install its own apps. A brand new iPhone with no apps — and even more importantly, no App Store — would be, well, just a phone, out of the box. How would users even access a site or app store from which to download independent apps? Would Apple be allowed to pre-install someone else’s apps? That’s discriminatory, too. Maybe it will be forced to offer a menu of all available apps in all categories (like the famously useless browser ballot screen demanded by the European Commission in its Microsoft antitrust case)? It’s hard to see how that benefits consumers — or even app developers.
Internet Search. Or take search. Calls for “search neutrality” have been bandied about for years. But most proponents of search neutrality fail to recognize that all Google’s search results entail bias in favor of its own offerings. As Geoff Manne and Josh Wright noted in 2011 at the height of the search neutrality debate:
[S]earch engines offer up results in the form not only of typical text results, but also maps, travel information, product pages, books, social media and more. To the extent that alleged bias turns on a search engine favoring its own maps, for example, over another firm’s, the allegation fails to appreciate that text results and maps are variants of the same thing, and efforts to restrain a search engine from offering its own maps is no different than preventing it from offering its own search results.
Nevermind that Google with forced non-discrimination likely means Google offering only the antiquated “ten blue links” search results page it started with in 1998 instead of the far more useful “rich” results it offers today; logically it would also mean Google somehow offering the set of links produced by any and all other search engines’ algorithms, in lieu of its own. If you think Google will continue to invest in and maintain the wealth of services it offers today on the strength of the profits derived from those search results, well, Elizabeth Warren is probably already your favorite politician.
And regulatory oversight of algorithmic content won’t just result in an impoverished digital experience; it will inevitably lead to an authoritarian one, as well:
Any agency granted a mandate to undertake such algorithmic oversight, and override or reconfigure the product of online services, thereby controls the content consumers may access…. This sort of control is deeply problematic… [because it saddles users] with a pervasive set of speech controls promulgated by the government. The history of such state censorship is one which has demonstrated strong harms to both social welfare and rule of law, and should not be emulated.
Digital Assistants. Consider also the veritable cage match among the tech giants to offer “digital assistants” and “smart home” devices with ever-more features at ever-lower prices. Today the allegedly non-existent competition among these companies is played out most visibly in this multi-featured market, comprising advanced devices tightly integrated with artificial intelligence, voice recognition, advanced algorithms, and a host of services. Under Warren’s nondiscrimination principle this market disappears. Each device can offer only a connectivity platform (if such a service is even permitted to be bundled with a physical device…) — and nothing more.
But such a world entails not only the end of an entire, promising avenue of consumer-benefiting innovation, it also entails the end of a promising avenue of consumer-benefiting competition. It beggars belief that anyone thinks consumers would benefit by forcing technology companies into their own silos, ensuring that the most powerful sources of competition for each other are confined to their own fiefdoms by order of law.
Breaking business models
Beyond the product-feature dimension, Sen. Warren’s proposal would be devastating for innovative business models. Why is Amazon Prime Video bundled with free shipping? Because the marginal cost of distribution for video is close to zero and bundling it with Amazon Prime increases the value proposition for customers. Why is almost every Google service free to users? Because Google’s business model is supported by ads, not monthly subscription fees. Each of the tech giants has carefully constructed an ecosystem in which every component reinforces the others. Sen. Warren’s plan would not only break up the companies, it would prohibit their business models — the ones that both created and continue to sustain these products. Such an outcome would manifestly harm consumers.
Both of Warren’s policy “solutions” are misguided and will lead to higher prices and less innovation. Her cause for alarm is built on a multitude of mistaken assumptions, but let’s address just a few (Warren in bold):
“Nearly half of all e-commerce goes through Amazon.” Yes, but it has only 5% of total retail in the United States. As my colleague Kristian Stout says, “the Internet is not a market; it’s a distribution channel.”
“Amazon has used its immense market power to force smaller competitors like Diapers.com to sell at a discounted rate.” The real story, as the founders of Diapers.com freely admitted, is that they sold diapers as what they hoped would be a loss leader, intending to build out sales of other products once they had a base of loyal customers:
And so we started with selling the loss leader product to basically build a relationship with mom. And once they had the passion for the brand and they were shopping with us on a weekly or a monthly basis that they’d start to fall in love with that brand. We were losing money on every box of diapers that we sold. We weren’t able to buy direct from the manufacturers.
Like all entrepreneurs, Diapers.com’s founders took a calculated risk that didn’t pay off as hoped. Amazon subsequently acquired the company (after it had declined a similar buyout offer from Walmart). (Antitrust laws protect consumers, not inefficient competitors). And no, this was not a case of predatory pricing. After many years of trying to make the business profitable as a subsidiary, Amazon shut it down in 2017.
“In the 1990s, Microsoft — the tech giant of its time — was trying to parlay its dominance in computer operating systems into dominance in the new area of web browsing. The federal government sued Microsoft for violating anti-monopoly laws and eventually reached a settlement. The government’s antitrust case against Microsoft helped clear a path for Internet companies like Google and Facebook to emerge.” The government’s settlement with Microsoft is not the reason Google and Facebook were able to emerge. Neither company entered the browser market at launch. Instead, they leapfrogged the browser entirely and created new platforms for the web (only later did Google create Chrome).
Furthermore, if the Microsoft case is responsible for “clearing a path” for Google is it not also responsible for clearing a path for Google’s alleged depredations? If the answer is that antitrust enforcement should be consistently more aggressive in order to rein in Google, too, when it gets out of line, then how can we be sure that that same more-aggressive enforcement standard wouldn’t have curtailed the extent of the Microsoft ecosystem in which it was profitable for Google to become Google? Warren implicitly assumes that only the enforcement decision in Microsoft was relevant to Google’s rise. But Microsoft doesn’t exist in a vacuum. If Microsoft cleared a path for Google, so did every decision not to intervene, which, all combined, created the legal, business, and economic environment in which Google operates.
Warren characterizes Big Tech as a weight on the American economy. In fact, nothing could be further from the truth. These superstar companies are the drivers of productivity growth, all ranking at or near the top for most spending on research and development. And while data may not be the new oil, extracting value from it may require similar levels of capital expenditure. Last year, Big Tech spent as much or more on capex as the world’s largest oil companies:
The exact causes of the decline in business dynamism are still uncertain, but recent research points to a much more mundane explanation: demographics. Labor force growth has been declining, which has led to an increase in average firm age, nudging fewer workers to start their own businesses.
Furthermore, it’s not at all clear whether this is actually a decline in business dynamism, or merely a change in business model. We would expect to see the same pattern, for example, if would-be startup founders were designing their software for acquisition and further development within larger, better-funded enterprises.
Will Rinehart recently looked at the literature to determine whether there is indeed a “kill zone” for startups around Big Tech incumbents. One paper finds that “an increase in fixed costs explains most of the decline in the aggregate entrepreneurship rate.” Another shows an inverse correlation across 50 countries between GDP and entrepreneurship rates. Robert Lucas predicted these trends back in 1978, pointing out that productivity increases would lead to wage increases, pushing marginal entrepreneurs out of startups and into big companies.
It’s notable that many in the venture capital community would rather not have Sen. Warren’s “help”:
just to sustain constant growth in GDP per person, the U.S. must double the amount of research effort searching for new ideas every 13 years to offset the increased difﬁculty of ﬁnding new ideas.
If this assessment is correct, it may well be that coming up with productive and profitable innovations is simply becoming more expensive, and thus, at the margin, each dollar of venture capital can fund less of it. Ironically, this also implies that larger firms, which can better afford the additional resources required to sustain exponential growth, are a crucial part of the solution, not the problem.
Warren believes that Big Tech is the cause of our social ills. But Americans have more trust in Amazon, Facebook, and Google than in the political institutions that would break them up. It would be wise for her to reflect on why that might be the case. By punishing our most valuable companies for past successes, Warren would chill competition and decrease returns to innovation.
Finally, in what can only be described as tragic irony, the most prominent political figure who shares Warren’s feelings on Big Tech is President Trump. Confirming the horseshoe theory of politics, far-left populism and far-right populism seem less distinguishable by the day. As our colleague Gus Hurwitz put it, with this proposal Warren is explicitly endorsing the unitary executive theory and implicitly endorsing Trump’s authority to direct his DOJ to “investigate specific cases and reach specific outcomes.” Which cases will he want to have investigated and what outcomes will he be seeking? More good questions that Senator Warren should be asking. The notion that competition, consumer welfare, and growth are likely to increase in such an environment is farcical.
Last week, the DOJ cleared the merger of CVS Health and Aetna (conditional on Aetna’s divesting its Medicare Part D business), a merger that, as I previously noted at a House Judiciary hearing, “presents a creative effort by two of the most well-informed and successful industry participants to try something new to reform a troubled system.” (My full testimony is available here).
Of course it’s always possible that the experiment will fail — that the merger won’t “revolutioniz[e] the consumer health care experience” in the way that CVS and Aetna are hoping. But it’s a low (antitrust) risk effort to address some of the challenges confronting the healthcare industry — and apparently the DOJ agrees.
I discuss the weakness of the antitrust arguments against the merger at length in my testimony. What I particularly want to draw attention to here is how this merger — like many vertical mergers — represents business model innovation by incumbents.
The CVS/Aetna merger is just one part of a growing private-sector movement in the healthcare industry to adopt new (mostly) vertical arrangements that seek to move beyond some of the structural inefficiencies that have plagued healthcare in the United States since World War II. Indeed, ambitious and interesting as it is, the merger arises amidst a veritable wave of innovative, vertical healthcare mergers and other efforts to integrate the healthcare services supply chain in novel ways.
These sorts of efforts (and the current DOJ’s apparent support for them) should be applauded and encouraged. I need not rehash the economic literature on vertical restraints here (see, e.g., Lafontaine & Slade, etc.). But especially where government interventions have already impaired the efficient workings of a market (as they surely have, in spades, in healthcare), it is important not to compound the error by trying to micromanage private efforts to restructure around those constraints.
Current trends in private-sector-driven healthcare reform
In the past, the most significant healthcare industry mergers have largely been horizontal (i.e., between two insurance providers, or two hospitals) or “traditional” business model mergers for the industry (i.e., vertical mergers aimed at building out managed care organizations). This pattern suggests a sort of fealty to the status quo, with insurers interested primarily in expanding their insurance business or providers interested in expanding their capacity to provide medical services.
Today’s health industry mergers and ventures seem more frequently to be different in character, and they portend an industry-wide experiment in the provision of vertically integrated healthcare that we should enthusiastically welcome.
But a number of other recent arrangements and business models center around relationships among drug manufacturers, pharmacies, and PBMs, and these tend to minimize the role of insurers. While not a “vertical” arrangement, per se, Walmart’s generic drug program, for example, offers $4 prescriptions to customers regardless of insurance (the typical generic drug copay for patients covered by employer-provided health insurance is $11), and Walmart does not seek or receive reimbursement from health plans for these drugs. It’s been offering this program since 2006, but in 2016 it entered into a joint buying arrangement with McKesson, a pharmaceutical wholesaler (itself vertically integrated with Rexall pharmacies), to negotiate lower prices. The idea, presumably, is that Walmart will entice consumers to its stores with the lure of low-priced generic prescriptions in the hope that they will buy other items while they’re there. That prospect presumably makes it worthwhile to route around insurers and PBMs, and their reimbursements.
Meanwhile, both Express Scripts and CVS Health (two of the country’s largest PBMs) have made moves toward direct-to-consumer sales themselves, establishing pricing for a small number of drugs independently of health plans and often in partnership with drug makers directly.
Also apparently focused on disrupting traditional drug distribution arrangements, Amazon has recently purchased online pharmacy PillPack (out from under Walmart, as it happens), and with it received pharmacy licenses in 49 states. The move introduces a significant new integrated distributor/retailer, and puts competitive pressure on other retailers and distributors and potentially insurers and PBMs, as well.
Whatever its role in driving the CVS/Aetna merger (and I believe it is smaller than many reports like to suggest), Amazon’s moves in this area demonstrate the fluid nature of the market, and the opportunities for a wide range of firms to create efficiencies in the market and to lower prices.
At the same time, the differences between Amazon and CVS/Aetna highlight the scope of product and service differentiation that should contribute to the ongoing competitiveness of these markets following mergers like this one.
While Amazon inarguably excels at logistics and the routinizing of “back office” functions, it seems unlikely for the foreseeable future to be able to offer (or to be interested in offering) a patient interface that can rival the service offerings of a brick-and-mortar CVS pharmacy combined with an outpatient clinic and its staff and bolstered by the capabilities of an insurer like Aetna. To be sure, online sales and fulfillment may put price pressure on important, largely mechanical functions, but, like much technology, it is first and foremost a complement to services offered by humans, rather than a substitute. (In this regard it is worth noting that McKesson has long been offering Amazon-like logistics support for both online and brick-and-mortar pharmacies. “‘To some extent, we were Amazon before it was cool to be Amazon,’ McKesson CEO John Hammergren said” on a recent earnings call).
Other efforts focus on integrating insurance and treatment functions or on bringing together other, disparate pieces of the healthcare industry in interesting ways — all seemingly aimed at finding innovative, private solutions to solve some of the costly complexities that plague the healthcare market.
Walmart, for example, announced a deal with Quest Diagnostics last year to experiment with offering diagnostic testing services and potentially other basic healthcare services inside of some Walmart stores. While such an arrangement may simply be a means of making doctor-prescribed diagnostic tests more convenient, it may also suggest an effort to expand the availability of direct-to-consumer (patient-initiated) testing (currently offered by Quest in Missouri and Colorado) in states that allow it. A partnership with Walmart to market and oversee such services has the potential to dramatically expand their use.
Capping off (for now) a buying frenzy in recent years that included the purchase of PBM, CatamaranRx, UnitedHealth is seeking approval from the FTC for the proposed merger of its Optum unit with the DaVita Medical Group — a move that would significantly expand UnitedHealth’s ability to offer medical services (including urgent care, outpatient surgeries, and health clinic services), give it a significant group of doctors’ clinics throughout the U.S., and turn UnitedHealth into the largest employer of doctors in the country. But of course this isn’t a traditional managed care merger — it represents a significant bet on the decentralized, ambulatory care model that has been slowly replacing significant parts of the traditional, hospital-centric care model for some time now.
And, perhaps most interestingly, some recent moves are bringing together drug manufacturers and diagnostic and care providers in innovative ways. Swiss pharmaceutical company, Roche, announced recently that “it would buy the rest of U.S. cancer data company Flatiron Health for $1.9 billion to speed development of cancer medicines and support its efforts to price them based on how well they work.” Not only is the deal intended to improve Roche’s drug development process by integrating patient data, it is also aimed at accommodating efforts to shift the pricing of drugs, like the pricing of medical services generally, toward an outcome-based model.
Similarly interesting, and in a related vein, early this year a group of hospital systems including Intermountain Health, Ascension, and Trinity Health announced plans to begin manufacturing generic prescription drugs. This development further reflects the perceived benefits of vertical integration in healthcare markets, and the move toward creative solutions to the unique complexity of coordinating the many interrelated layers of healthcare provision. In this case,
[t]he nascent venture proposes a private solution to ensure contestability in the generic drug market and consequently overcome the failures of contracting [in the supply and distribution of generics]…. The nascent venture, however it solves these challenges and resolves other choices, will have important implications for the prices and availability of generic drugs in the US.
More enforcement decisions like CVS/Aetna and Bayer/Monsanto; fewer like AT&T/Time Warner
In the face of all this disruption, it’s difficult to credit anticompetitive fears like those expressed by the AMA in opposing the CVS-Aetna merger and a recent CEA report on pharmaceutical pricing, both of which are premised on the assumption that drug distribution is unavoidably dominated by a few PBMs in a well-defined, highly concentrated market. Creative arrangements like the CVS-Aetna merger and the initiatives described above (among a host of others) indicate an ease of entry, the fluidity of traditional markets, and a degree of business model innovation that suggest a great deal more competitiveness than static PBM market numbers would suggest.
This kind of incumbent innovation through vertical restructuring is an increasingly important theme in antitrust, and efforts to tar such transactions with purported evidence of static market dominance is simply misguided.
While the current DOJ’s misguided (and, remarkably, continuing) attempt to stop the AT&T/Time Warner merger is an aberrant step in the wrong direction, the leadership at the Antitrust Division generally seems to get it. Indeed, in spite of strident calls for stepped-up enforcement in the always-controversial ag-biotech industry, the DOJ recently approved three vertical ag-biotech mergers in fairly rapid succession.
As I noted in a discussion of those ag-biotech mergers, but equally applicable here, regulatory humility should continue to carry the day when it comes to structural innovation by incumbent firms:
But it is also important to remember that innovation comes from within incumbent firms, as well, and, often, that the overall level of innovation in an industry may be increased by the presence of large firms with economies of scope and scale.
In sum, and to paraphrase Olympia Dukakis’ character in Moonstruck: “what [we] don’t know about [the relationship between innovation and market structure] is a lot.”
What we do know, however, is that superficial, concentration-based approaches to antitrust analysis will likely overweight presumed foreclosure effects and underweight innovation effects.
We shouldn’t fetishize entry, or access, or head-to-head competition over innovation, especially where consumer welfare may be significantly improved by a reduction in the former in order to get more of the latter.
Amazon offers Prime discounts to Whole Food customers and offers free delivery for Prime members. Those are certainly consumer benefits. But with those comes a cost, which may or may not be significant. By bundling its products with collective discounts, Amazon makes it more attractive for shoppers to shift their buying practices from local stores to the internet giant. Will this eventually mean that local stores will become more inefficient, based on lower volume, and will eventually close? Do most Americans care about the potential loss of local supermarkets and specialty grocers? No one, including antitrust enforcers, seems to have asked them.
The gist of these arguments is simple. The Amazon / Whole Foods merger would lead to the exclusion of competitors, with Amazon leveraging its swaths of data and pricing below costs. All of this begs a simple question: have these prophecies come to pass?
The problem with antitrust populism is not just that it leads to unfounded predictions regarding the negative effects of a given business practice. It also ignores the significant gains which consumers may reap from these practices. The Amazon / Whole foods offers a case in point.
Even with these caveats, it’s still worth looking at the recent trends. Whole Foods’s sales since 2015 have been flat, with only low single-digit growth, according to data from Second Measure. This suggests Whole Foods is not yet getting a lift from the relationship. However, the percentage of Whole Foods’ new customers who are Prime Members increased post-merger, from 34 percent in June 2017 to 41 percent in June 2018. This suggests that Amazon’s platform is delivering customers to Whole Foods.
The negativity that surrounded the deal at its announcement made Whole Foods seem like an innocent player, but it is important to recall that they were hemorrhaging and were looking to exit. Throughout the 2010s, the company lost its market leading edge as others began to offer the same kinds of services and products. Still, the company was able to sell near the top of its value to Amazon because it was able to court so many suitors. Given all of these features, Whole Foods could have been using the exit as a mechanism to appropriate another firm’s rent.
Brandeis is back, with today’s neo-Brandeisians reflexively opposing virtually all mergers involving large firms. For them, industry concentration has grown to crisis proportions and breaking up big companies should be the animating goal not just of antitrust policy but of U.S. economic policy generally. The key to understanding the neo-Brandeisian opposition to the Whole Foods/Amazon mergers is that it has nothing to do with consumer welfare, and everything to do with a large firm animus. Sabeel Rahman, a Roosevelt Institute scholar, concedes that big firms give us higher productivity, and hence lower prices, but he dismisses the value of that. He writes, “If consumer prices are our only concern, it is hard to see how Amazon, Comcast, and companies such as Uber need regulation.” And this gets to the key point regarding most of the opposition to the merger: it had nothing to do with concerns about monopolistic effects on economic efficiency or consumer prices. It had everything to do with opposition to big firm for the sole reason that they are big.