Archives For HHI

Germán Gutiérrez and Thomas Philippon have released a major rewrite of their paper comparing the U.S. and EU competitive environments. 

Although the NBER website provides an enticing title — “How European Markets Became Free: A Study of Institutional Drift” — the paper itself has a much more yawn-inducing title: “How EU Markets Became More Competitive Than US Markets: A Study of Institutional Drift.”

Having already critiqued the original paper at length (here and here), I wouldn’t normally take much interest in the do-over. However, in a recent episode of Tyler Cowen’s podcast, Jason Furman gave a shout out to Philippon’s work on increasing concentration. So, I thought it might be worth a review.

As with the original, the paper begins with a conclusion: The EU appears to be more competitive than the U.S. The authors then concoct a theory to explain their conclusion. The theory’s a bit janky, but it goes something like this:

  • Because of lobbying pressure and regulatory capture, an individual country will enforce competition policy at a suboptimal level.
  • Because of competing interests among different countries, a “supra-national” body will be more independent and better able to foster pro-competitive policies and to engage in more vigorous enforcement of competition policy.
  • The EU’s supra-national body and its Directorate-General for Competition is more independent than the U.S. Department of Justice and Federal Trade Commission.
  • Therefore, their model explains why the EU is more competitive than the U.S. Q.E.D.

If you’re looking for what this has to do with “institutional drift,” don’t bother. The term only shows up in the title.

The original paper provided evidence from 12 separate “markets,” that they say demonstrated their conclusion about EU vs. U.S. competitiveness. These weren’t really “markets” in the competition policy sense, they were just broad industry categories, such as health, information, trade, and professional services (actually “other business sector services”). 

As pointed out in one of my earlier critiques, In all but one of these industries, the 8-firm concentration ratios for the U.S. and the EU are below 40 percent and the HHI measures reported in the original paper are at levels that most observers would presume to be competitive. 

Sending their original markets to drift in the appendices, Gutiérrez and Philippon’s revised paper focuses its attention on two markets — telecommunications and airlines — to highlight their claims that EU markets are more competitive than the U.S. First, telecoms:

To be more concrete, consider the Telecom industry and the entry of the French Telecom company Free Mobile. Until 2011, the French mobile industry was an oligopoly with three large historical incumbents and weak competition. … Free obtained its 4G license in 2011 and entered the market with a plan of unlimited talk, messaging and data for €20. Within six months, the incumbents Orange, SFR and Bouygues had reacted by launching their own discount brands and by offering €20 contracts as well. … The relative price decline was 40%: France went from being 15% more expensive than the US [in 2011] to being 25% cheaper in about two years [in 2013].

While this is an interesting story about how entry can increase competition, the story of a single firm entering a market in a single country is hardly evidence that the EU as a whole is more competitive than the U.S.

What Gutiérrez and Philippon don’t report is that from 2013 to 2019, prices declined by 12% in the U.S. and only 8% in France. In the EU as a whole, prices decreased by only 5% over the years 2013-2019.

Gutiérrez and Philippon’s passenger airline story is even weaker. Because airline prices don’t fit their narrative, they argue that increasing airline profits are evidence that the U.S. is less competitive than the EU. 

The picture above is from Figure 5 of their paper (“Air Transportation Profits and Concentration, EU vs US”). They claim that the “rise in US concentration and profits aligns closely with a controversial merger wave,” with the vertical line in the figure marking the Delta-Northwest merger.

Sure, profitability among U.S. firms increased. But, before the “merger wave,” profits were negative. Perhaps predatory pricing is pro-competitive after all.

Where Gutiérrez and Philippon really fumble is with airline pricing. Since the merger wave that pulled the U.S. airline industry out of insolvency, ticket prices (as measured by the Consumer Price Index), have decreased by 6%. In France, prices increased by 4% and in the EU, prices increased by 30%. 

The paper relies more heavily on eyeballing graphs than statistical analysis, but something about Table 2 caught my attention — the R-squared statistics. First, they’re all over the place. But, look at column (1): A perfect 1.00 R-squared. Could it be that Gutiérrez and Philippon’s statistical model has (almost) as many parameters as variables?

Notice that all the regressions with an R-squared of 0.9 or higher include country fixed effects. The two regressions with R-squareds of 0.95 and 0.96 also include country-industry fixed effects. It’s very possible that the regressions results are driven entirely by idiosyncratic differences among countries and industries. 

Gutiérrez and Philippon provide no interpretation for their results in Table 2, but it seems to work like this, using column (1): A 10% increase in the 4-firm concentration ratio (which is different from a 10 percentage point increase), would be associated with a 1.8% increase in prices four years later. So, an increase in CR4 from 20% to 22% (or an increase from 60% to 66%) would be associated with a 1.8% increase in prices over four years, or about 0.4% a year. On the one hand, I just don’t buy it. On the other hand, the effect is so small that it seems economically insignificant. 

I’m sure Gutiérrez and Philippon have put a lot of time into this paper and its revision. But there’s an old saying that the best thing about banging your head against the wall is that it feels so good when it stops. Perhaps, it’s time to stop with this paper and let it “drift” into obscurity.

[TOTM: The following is part of a blog series by TOTM guests and authors on the law, economics, and policy of the ongoing COVID-19 pandemic. The entire series of posts is available here.

This post is authored by Eric Fruits, (Chief Economist, International Center for Law & Economics).]

Earlier this week, merger talks between Uber and food delivery service Grubhub surfaced. House Antitrust Subcommittee Chairman David N. Cicilline quickly reacted to the news:

Americans are struggling to put food on the table, and locally owned businesses are doing everything possible to keep serving people in our communities, even under great duress. Uber is a notoriously predatory company that has long denied its drivers a living wage. Its attempt to acquire Grubhub—which has a history of exploiting local restaurants through deceptive tactics and extortionate fees—marks a new low in pandemic profiteering. We cannot allow these corporations to monopolize food delivery, especially amid a crisis that is rendering American families and local restaurants more dependent than ever on these very services. This deal underscores the urgency for a merger moratorium, which I and several of my colleagues have been urging our caucus to support.

Pandemic profiteering rolls nicely off the tongue, and we’re sure to see that phrase much more over the next year or so. 

Grubhub shares jumped 29% Tuesday, the day the merger talks came to light, shown in the figure below. The Wall Street Journal reports companies are considering a deal that would value Grubhub stock at around 1.9 Uber shares, or $60-65 dollars a share, based on Thursday’s price.

But is that “pandemic profiteering?”

After Amazon announced its intended acquisition of Whole Foods, the grocer’s stock price soared by 27%. Rep. Cicilline voiced some convoluted concerns about that merger, but said nothing about profiteering at the time. Different times, different messaging.

Rep. Cicilline and others have been calling for a merger moratorium during the pandemic and used the Uber/Grubhub announcement as Exhibit A in his indictment of merger activity.

A moratorium would make things much easier for regulators. No more fighting over relevant markets, no HHI calculations, no experts debating SSNIPs or GUPPIs, no worries over consumer welfare, no failing firm defenses. Just a clear, brightline “NO!”

Even before the pandemic, it was well known that the food delivery industry was due for a shakeout. NPR reports, even as the business is growing, none of the top food-delivery apps are turning a profit, with one analyst concluding consolidation was “inevitable.” Thus, even if a moratorium slowed or stopped the Uber/Grubhub merger, at some point a merger in the industry will happen and the U.S. antitrust authorities will have to evaluate it.

First, we have to ask, “What’s the relevant market?” The government has a history of defining relevant markets so narrowly that just about any merger can be challenged. For example, for the scuttled Whole Foods/Wild Oats merger, the FTC famously narrowed the market to “premium natural and organic supermarkets.” Surely, similar mental gymnastics will be used for any merger involving food delivery services.

While food delivery has grown in popularity over the past few years, delivery represents less than 10% of U.S. food service sales. While Rep. Cicilline may be correct that families and local restaurants are “more dependent than ever” on food delivery, delivery is only a small fraction of a large market. Even a monopoly of food delivery service would not confer market power on the restaurant and food service industry.

No reasonable person would claim an Uber/Grubhub merger would increase market power in the restaurant and food service industry. But, it might convey market power in the food delivery market. Much attention is paid to the “Big Four”–DoorDash, Grubhub, Uber Eats, and Postmates. But, these platform delivery services are part of the larger food service delivery market, of which platforms account for about half of the industry’s revenues. Pizza accounts for the largest share of restaurant-to-consumer delivery.

This raises the big question of what is the relevant market: Is it the entire food delivery sector, or just the platform-to-consumer sector? 

Based on the information in the figure below, defining the market narrowly would place an Uber/Grubhub merger squarely in the “presumed to be likely to enhance market power” category.

  • 2016 HHI: <3,175
  • 2018 HHI: <1,474
  • 2020 HHI: <2,249 pre-merger; <4,153 post-merger

Alternatively, defining the market to encompass all food delivery would cut the platforms’ shares roughly in half and the merger would be unlikely to harm competition, based on HHI. Choosing the relevant market is, well, relevant.

The Second Measure data suggests that concentration in the platform delivery sector decreased with the entry of Uber Eats, but subsequently increased with DoorDash’s rising share–which included the acquisition of Caviar from Square.

(NB: There seems to be a significant mismatch in the delivery revenue data. Statista reports platform delivery revenues increased by about 40% from 2018 to 2020, but Second Measure indicates revenues have more than doubled.) 

Geoffrey Manne, in an earlier post points out “while national concentration does appear to be increasing in some sectors of the economy, it’s not actually so clear that the same is true for local concentration — which is often the relevant antitrust market.” That may be the case here.

The figure below is a sample of platform delivery shares by city. I added data from an earlier study of 2017 shares. In all but two metro areas, Uber and Grubhub’s combined market share declined from 2017 to 2020. In Boston, the combined shares did not change and in Los Angeles, the combined shares increased by 1%.

(NB: There are some serious problems with this data, notably that it leaves out the restaurant-to-consumer sector and assumes the entire platform-to-consumer sector is comprised of only the “Big Four.”)

Platform-to-consumer delivery is a complex two-sided market in which the platforms link, and compete for, both restaurants and consumers. Platforms compete for restaurants, drivers, and consumers. Restaurants have a choice of using multiple platforms or entering into exclusive arrangements. Many drivers work for multiple platforms, and many consumers use multiple platforms. 

Fundamentally, the rise of platform-to-consumer is an evolution in vertical integration. Restaurants can choose to offer no delivery, use their own in-house delivery drivers, or use a third party delivery service. Every platform faces competition from in-house delivery, placing a limit on their ability to raise prices to restaurants and consumers.

The choice of delivery is not an either-or decision. For example, many pizza restaurants who have their own delivery drivers also use platform delivery service. Their own drivers may serve a limited geographic area, but the platforms allow the restaurant to expand its geographic reach, thereby increasing its sales. Even so, the platforms face competition from in-house delivery.

Mergers or other forms of shake out in the food delivery industry are inevitable. Mergers will raise important questions about relevant product and geographic markets as well as competition in two-sided markets. While there is a real risk of harm to restaurants, drivers, and consumers, there is also a real possibility of welfare enhancing efficiencies. These questions will never be addressed with an across-the-board merger moratorium.

A recent NBER working paper by Gutiérrez & Philippon attempts to link differences in U.S. and EU antitrust enforcement and product market regulation to differences in market concentration and corporate profits. The paper’s abstract begins with a bold assertion:

Until the 1990’s, US markets were more competitive than European markets. Today, European markets have lower concentration, lower excess profits, and lower regulatory barriers to entry.

The authors are not clear what they mean by lower, however its seems they mean lower today relative to the 1990s.

This blog post focuses on the first claim: “Today, European markets have lower concentration …”

At the risk of being pedantic, Gutiérrez & Philippon’s measures of market concentration for which both U.S. and EU data are reported cover the period from 1999 to 2012. Thus, “the 1990s” refers to 1999, and “today” refers to 2012, or six years ago.

The table below is based on Figure 26 in Gutiérrez & Philippon. In 2012, there appears to be no significant difference in market concentration between the U.S. and the EU, using either the 8-firm concentration ratio or HHI. Based on this information, it cannot be concluded broadly that EU sectors have lower concentration than the U.S.

CR826% (+5%)27% (-7%)
HHI640 (+150)600 (-190)

Gutiérrez & Philippon focus on the change in market concentration to draw their conclusions. However, the levels of market concentration measures are strikingly low. In all but one of the industries (telecommunications) in Figure 27 of their paper, the 8-firm concentration ratios for the U.S. and the EU are below 40 percent. Similarly, the HHI measures reported in the paper are at levels that most observers would presume to be competitive. In addition, in 7 of the 12 sectors surveyed, the U.S. 8-firm concentration ratio is lower than in the EU.

The numbers in parentheses in the table above show the change in the measures of concentration since 1999. The changes suggests that U.S. markets have become more concentrated and EU markets have become less concentrated. But, how significant are the changes in concentration?

A simple regression of the relationship between CR8 and a time trend finds that in the EU, CR8 has decreased an average of 0.5 percentage point a year, while the U.S. CR8 increased by less than 0.4 percentage point a year from 1999 to 2012. Tucked in an appendix to Gutiérrez & Philippon, Figure 30 shows that CR8 in the U.S. had decreased by about 2.5 percentage points from 2012 to 2014.

A closer examination of Gutiérrez & Philippon’s 8-firm concentration ratio for the EU shows that much of the decline in EU market concentration occurred over the 1999-2002 period. After that, the change in CR8 for the EU is not statistically significantly different from zero.

A regression of the relationship between HHI and a time trend finds that in the EU, HHI has decreased an average of 12.5 points a year, while the U.S. HHI increased by less than 16.4 points a year from 1999 to 2012.

As with CR8, a closer examination of Gutiérrez & Philippon’s HHI for the EU shows that much of the decline in EU market concentration occurred over the 1999-2002 period. After that, the change in HHI for the EU is not statistically significantly different from zero.

Readers should be cautious in relying on Gutiérrez & Philippon’s data to conclude that the U.S. is “drifting” toward greater market concentration while the EU is “drifting” toward lower market concentration. Indeed, the limited data presented in the paper point toward a convergence in market concentration between the two regions.



As Thom previously posted, he and I have a new paper explaining The Case for Doing Nothing About Common Ownership of Small Stakes in Competing Firms. Our paper is a response to cries from the likes of Einer Elhauge and of Eric Posner, Fiona Scott Morton, and Glen Weyl, who have called for various types of antitrust action to reign in what they claim is an “economic blockbuster” and “the major new antitrust challenge of our time,” respectively. This is the first in a series of posts that will unpack some of the issues and arguments we raise in our paper.

At issue is the growth in the incidence of common-ownership across firms within various industries. In particular, institutional investors with broad portfolios frequently report owning small stakes in a number of firms within a given industry. Although small, these stakes may still represent large block holdings relative to other investors. This intra-industry diversification, critics claim, changes the managerial objectives of corporate executives from aggressively competing to increase their own firm’s profits to tacitly colluding to increase industry-level profits instead. The reason for this change is that competition by one firm comes at a cost of profits from other firms in the industry. If investors own shares across firms, then any competitive gains in one firm’s stock are offset by competitive losses in the stocks of other firms in the investor’s portfolio. If one assumes corporate executives aim to maximize total value for their largest shareholders, then managers would have incentive to soften competition against firms with which they share common ownership. Or so the story goes (more on that in a later post.)

Elhague and Posner, et al., draw their motivation for new antitrust offenses from a handful of papers that purport to establish an empirical link between the degree of common ownership among competing firms and various measures of softened competitive behavior, including airline prices, banking fees, executive compensation, and even corporate disclosure patterns. The paper of most note, by José Azar, Martin Schmalz, and Isabel Tecu and forthcoming in the Journal of Finance, claims to identify a causal link between the degree of common ownership among airlines competing on a given route and the fares charged for flights on that route.

Measuring common ownership with MHHI

Azar, et al.’s airline paper uses a metric of industry concentration called a Modified Herfindahl–Hirschman Index, or MHHI, to measure the degree of industry concentration taking into account the cross-ownership of investors’ stakes in competing firms. The original Herfindahl–Hirschman Index (HHI) has long been used as a measure of industry concentration, debuting in the Department of Justice’s Horizontal Merger Guidelines in 1982. The HHI is calculated by squaring the market share of each firm in the industry and summing the resulting numbers.

The MHHI is rather more complicated. MHHI is composed of two parts: the HHI measuring product market concentration and the MHHI_Delta measuring the additional concentration due to common ownership. We offer a step-by-step description of the calculations and their economic rationale in an appendix to our paper. For this post, I’ll try to distill that down. The MHHI_Delta essentially has three components, each of which is measured relative to every possible competitive pairing in the market as follows:

  1. A measure of the degree of common ownership between Company A and Company -A (Not A). This is calculated by multiplying the percentage of Company A shares owned by each Investor I with the percentage of shares Investor I owns in Company -A, then summing those values across all investors in Company A. As this value increases, MHHI_Delta goes up.
  2. A measure of the degree of ownership concentration in Company A, calculated by squaring the percentage of shares owned by each Investor I and summing those numbers across investors. As this value increases, MHHI_Delta goes down.
  3. A measure of the degree of product market power exerted by Company A and Company -A, calculated by multiplying the market shares of the two firms. As this value increases, MHHI_Delta goes up.

This process is repeated and aggregated first for every pairing of Company A and each competing Company -A, then repeated again for every other company in the market relative to its competitors (e.g., Companies B and -B, Companies C and -C, etc.). Mathematically, MHHI_Delta takes the form:

where the Ss represent the firm market shares of, and Betas represent ownership shares of Investor I in, the respective companies A and -A.

As the relative concentration of cross-owning investors to all investors in Company A increases (i.e., the ratio on the right increases), managers are assumed to be more likely to soften competition with that competitor. As those two firms control more of the market, managers’ ability to tacitly collude and increase joint profits is assumed to be higher. Consequently, the empirical research assumes that as MHHI_Delta increases, we should observe less competitive behavior.

And indeed that is the “blockbuster” evidence giving rise to Elhauge’s and Posner, et al.,’s arguments  For example, Azar, et. al., calculate HHI and MHHI_Delta for every US airline market–defined either as city-pairs or departure-destination pairs–for each quarter of the 14-year time period in their study. They then regress ticket prices for each route against the HHI and the MHHI_Delta for that route, controlling for a number of other potential factors. They find that airfare prices are 3% to 7% higher due to common ownership. Other papers using the same or similar measures of common ownership concentration have likewise identified positive correlations between MHHI_Delta and their respective measures of anti-competitive behavior.

Problems with the problem and with the measure

We argue that both the theoretical argument underlying the empirical research and the empirical research itself suffer from some serious flaws. On the theoretical side, we have two concerns. First, we argue that there is a tremendous leap of faith (if not logic) in the idea that corporate executives would forgo their own self-interest and the interests of the vast majority of shareholders and soften competition simply because a small number of small stakeholders are intra-industry diversified. Second, we argue that even if managers were so inclined, it clearly is not the case that softening competition would necessarily be desirable for institutional investors that are both intra- and inter-industry diversified, since supra-competitive pricing to increase profits in one industry would decrease profits in related industries that may also be in the investors’ portfolios.

On the empirical side, we have concerns both with the data used to calculate the MHHI_Deltas and with the nature of the MHHI_Delta itself. First, the data on institutional investors’ holdings are taken from Schedule 13 filings, which report aggregate holdings across all the institutional investor’s funds. Using these data masks the actual incentives of the institutional investors with respect to investments in any individual company or industry. Second, the construction of the MHHI_Delta suffers from serious endogeneity concerns, both in investors’ shareholdings and in market shares. Finally, the MHHI_Delta, while seemingly intuitive, is an empirical unknown. While HHI is theoretically bounded in a way that lends to interpretation of its calculated value, the same is not true for MHHI_Delta. This makes any inference or policy based on nominal values of MHHI_Delta completely arbitrary at best.

We’ll expand on each of these concerns in upcoming posts. We will then take on the problems with the policy proposals being offered in response to the common ownership ‘problem.’







I just posted a new ICLE white paper, co-authored with former ICLE Associate Director, Ben Sperry:

When Past Is Not Prologue: The Weakness of the Economic Evidence Against Health Insurance Mergers.

Yesterday the hearing in the DOJ’s challenge to stop the Aetna-Humana merger got underway, and last week phase 1 of the Cigna-Anthem merger trial came to a close.

The DOJ’s challenge in both cases is fundamentally rooted in a timeworn structural analysis: More consolidation in the market (where “the market” is a hotly-contested issue, of course) means less competition and higher premiums for consumers.

Following the traditional structural playbook, the DOJ argues that the Aetna-Humana merger (to pick one) would result in presumptively anticompetitive levels of concentration, and that neither new entry not divestiture would suffice to introduce sufficient competition. It does not (in its pretrial brief, at least) consider other market dynamics (including especially the complex and evolving regulatory environment) that would constrain the firm’s ability to charge supracompetitive prices.

Aetna & Humana, for their part, contend that things are a bit more complicated than the government suggests, that the government defines the relevant market incorrectly, and that

the evidence will show that there is no correlation between the number of [Medicare Advantage organizations] in a county (or their shares) and Medicare Advantage pricing—a fundamental fact that the Government’s theories of harm cannot overcome.

The trial will, of course, feature expert economic evidence from both sides. But until we see that evidence, or read the inevitable papers derived from it, we are stuck evaluating the basic outlines of the economic arguments based on the existing literature.

A host of antitrust commentators, politicians, and other interested parties have determined that the literature condemns the mergers, based largely on a small set of papers purporting to demonstrate that an increase of premiums, without corresponding benefit, inexorably follows health insurance “consolidation.” In fact, virtually all of these critics base their claims on a 2012 case study of a 1999 merger (between Aetna and Prudential) by economists Leemore Dafny, Mark Duggan, and Subramaniam Ramanarayanan, Paying a Premium on Your Premium? Consolidation in the U.S. Health Insurance Industry, as well as associated testimony by Prof. Dafny, along with a small number of other papers by her (and a couple others).

Our paper challenges these claims. As we summarize:

This white paper counsels extreme caution in the use of past statistical studies of the purported effects of health insurance company mergers to infer that today’s proposed mergers—between Aetna/Humana and Anthem/Cigna—will likely have similar effects. Focusing on one influential study—Paying a Premium on Your Premium…—as a jumping off point, we highlight some of the many reasons that past is not prologue.

In short: extrapolated, long-term, cumulative, average effects drawn from 17-year-old data may grab headlines, but they really don’t tell us much of anything about the likely effects of a particular merger today, or about the effects of increased concentration in any particular product or geographic market.

While our analysis doesn’t necessarily undermine the paper’s limited, historical conclusions, it does counsel extreme caution for inferring the study’s applicability to today’s proposed mergers.

By way of reference, Dafny, et al. found average premium price increases from the 1999 Aetna/Prudential merger of only 0.25 percent per year for two years following the merger in the geographic markets they studied. “Health Insurance Mergers May Lead to 0.25 Percent Price Increases!” isn’t quite as compelling a claim as what critics have been saying, but it’s arguably more accurate (and more relevant) than the 7 percent price increase purportedly based on the paper that merger critics like to throw around.

Moreover, different markets and a changed regulatory environment alone aren’t the only things suggesting that past is not prologue. When we delve into the paper more closely we find even more significant limitations on the paper’s support for the claims made in its name, and its relevance to the current proposed mergers.

The full paper is available here.