Read the 10 best academic and business antitrust articles published in 2012!

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Back to Basics: the (Over)Use Of Economic Models in Antitrust

Shepard Goldfein and Neal R. Stoll, New York Law Journal, July 2012

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To bring an action under Sections 1 or 2 of the Sherman Act or Section 7 of the Clayton Act a plaintiff, whether the Federal Trade Commission (FTC), the Department of Justice or a private party must demonstrate, among other things, that the defendant’s conduct or the challenged transaction will reduce or harm competition. Indubitably, the plaintiff and defendant retain economic experts to inform the fact-finder why the challenged conduct will or will not harm competition in defined relevant product and geographic markets.

The plaintiff’s expert economist will review information in the record and, summoning his experience and training, postulate a hypothesis, based on economic principles, that utilizes a methodology sufficient to defeat a Daubert motion and concludes that the defendant’s alleged conduct will result in market-wide anticompetitive effects. The defendant then reacts equally and oppositely by retaining its own economic expert to rebut the opinion of the plaintiff’s economist, and to proffer an alternative economic theory suggesting that the defendant’s conduct not only doesn’t harm competition, but, perhaps, is even beneficial to consumer welfare.

Throughout the customary antitrust investigation, and especially at trial, the economists’ expert opinions and the economic theories and models that buttress the competing opinions take center stage. However, even for counsel who are experienced in the practice of antitrust jurisprudence, an economist’s expert opinion is oftentimes convoluted or difficult to follow. Generally, the economist’s opinion will rely on empirical evidence and interpret available quantitative data. In merger cases, economists will use the Herfindahl-Hirschman Index (HHI) to measure competitive effects, and rely on models, including the GUPPI (Gross Upward Pricing Pressure Index), the newly discovered vGUPPI (Vertical GUPPI), [1] diversion ratios, SSNIPs, and Bertrand behavior, etc.

Somewhat more evolved than the popular freshwater aquarium fish species, GUPPIs forecast post-merger effects by scoring the merger’s predicted upward pricing pressure based on an economic model. While this tool and others like it are certainly sophisticated, they can obfuscate and overcomplicate matters over the course of a case. Further compounding the problem is the overwhelming menu of economic suppositions and schools of ideology to which economists subscribe and on which economists base their opinions. The difficulty of using the arsenal of today’s advanced economic weaponry is exacerbated by the fact that judges, lawyers and juries often lack the training, judgment, and experience necessary to decide which of the competing economic opinions to credit.

A little more than four decades ago, the economic rationale employed by courts resembled a Sargasso Sea. Although antitrust precedent was somewhat consistent, in that courts frequently ruled in favor of the government, there was considerable unpredictability as to how a court would apply the antitrust laws to a given set of facts. [2] Most tortured were the cases on merger law, where
courts haphazardly (and by today’s standards, inaccurately) defined relevant markets based on a potpourri of observations about the industry and usually ended with the judge’s visceral reaction that the merger would harm competition. The recurring motif in antitrust law was that courts proscribed a variety of business practices based on unsubstantiated theories of consumer harm and blocked several mergers, often without providing guidance concerning the economic principles to be applied in the future. While economics certainly played a role in antitrust law, it was considered a random, minor element of many antitrust court decisions.

Emerging from the floating mass of sargassum, the Chicago School of Economics sought to provide a firm economic basis to undermine the government’s interventionist ideology. [3] Far from simply endorsing a laissez faire approach to antitrust policy, however, the Chicago School advanced comprehensive price theory and introduced the downward-sloping demand curve. Most notable is the school’s neoclassical assumption that individuals and firms can be expected to act rationally, meaning in their self-interested profit-maximizing best interest. As a corollary to this, Chicagoans implemented the assumption of marketplace efficiency, meaning that markets selfcorrect and that in the long term, prices reflect all available information. The promulgation of the 1982 Merger Guidelines represented a significant step forward in the acceptance of the application of Chicago School economic theory to antitrust law, introducing such staples of modern day antitrust analysis as the hypothetical monopolist test, and the case law responded in kind.

As the Chicago School took shape, offshoots and opponents of Chicago economic thought, such as the Harvard and Post-Chicago Schools, expanded on, added caveats to, and identified limitations of some of the basic findings of the Chicago School. That evolution has continued into the 21st century with the advent of the Neo-Chicago School and Behavioral Economics, Johnny-come-latelys on the antitrust economics scene. Although the Neo-Chicago School has provoked considerable conversation, [4] the majority of the attention in both academic circles and among antitrust practitioners has been paid to the emergence of behavioral economics.

Why all the clamor about behavioral economics? In essence, the Behavioral School challenges the fundamental assumption of the Chicago School, i.e., that we act in our long-term profitmaximizing best interest. [5] We can all think of times where we bought something that we did not really need or like, made an improvident investment decision, valued something improperly or were otherwise short-sighted and unwise. Behaviorists argue that we often make decisions that contradict our long-term best interests due to a number of cognitive biases and limitations that are a part of our hardwiring.

These limitations, they say, render the Chicago School’s assumption of rational decision-making fatally flawed, and thereby undermine the claim that Chicago-based economic models are accurate predictors of competitive effects. A handful of recent studies have demonstrated that, in certain situations, people tend to do things that contradict the Chicago model’s predictions of behavior. By organizing and interpreting these empirical observations and other real-world data, behaviorists aim to create economic models that quantify deviations from expected behavior and thereby more accurately predict economic effects.

Models and Reality

While behavioral economics has gained many proponents over recent years, criticisms of the nascent school abound. [6] Among the critics are neoclassical economists who point out that the last 30 years of antitrust jurisprudence is firmly established on the Chicago-School concept that people act rationally and that the market disciplines individuals or firms that act irrationally. Herbert Hovenkamp wrote that antitrust “is dedicated to the proposition that business firms behave rationally,” [7] and that assumption has led to the development of reasonably accurate predictive economic models and a predictable antitrust regime.

A model by definition aims to simplify a complicated real world, and thus must make some generalized hypotheses about human conduct. The models based on the rational actor assumption both are reasonably accurate and adequately account for their own limitations. In light of the fact that the antitrust community is generally satisfied with the structure and policy of the current system and that recent merger retrospectives have not definitively shown that antitrust policy based on the rational actor assumption has led to a net negative for consumer welfare, [8] jettisoning the rational actor model is deemed imprudent by these critics. (Didn’t we all go through a period of high anxiety upon hearing the reports that CERN observed a subatomic particle (neutrino) exceeding the speed of light? Such a result would have required revisiting all of the laws of nature derived from Einstein’s special theory of relativity.)

Critics also argue that unlike its rivals, behavioral economics does not have a singular unifying, guiding principle or default position, and that by trying to account for actual human conduct, it sacrifices feasibility for reality. Some have argued that behavioral economics does not and cannot predict accurately deviations from perfectly “rational” behavior and therefore cannot produce an economic model that accounts for the many variables it identifies and that predict competitive effects more accurately than competing models.

Although the debate on which model’s assumptions most accurately account for marketplace realities is interesting, it is at this point too academic to garner significant attention in formulating antitrust policy or law, or in contributing to the courts’ antitrust opinions. Rather than pose the quixotic question of what economic theory or model most accurately predicts competitive effects, the antitrust policy makers and decision makers should re-emphasize the importance of the careful application of good judgment and attention to details about marketplace dynamics in resolving antitrust disputes. After all, the best way to predict what will happen in the real world is to consider every available piece of evidence— quantitative or not—about what happens in the real world.

We like models that explain human behavior because they are easy shortcuts that comprehensively explain seemingly random events. But there is an inherent risk in relying too much on these heuristic models. Models are only as reliable as their inputs, and in some industries there is insufficient or incomplete reliable data that can form the basis for a reliable quantitative model—especially one based on behavioral economics.

Many Chicago-based models, for example, use proxies to arrive at key financial metrics, such as marginal costs, because such information is not widely and publicly available. Any behavioral model would likewise have to use proxies in order to be comprehensive, but this would seem to defy altogether the central idea of behavioral economics. There are limitations to both models and human judgment (consider the recent financial crisis), but because competitive dynamics vary from industry to industry, antitrust cases demand case-by-case, fact-intensive scrutiny.

Antitrust law has moved away from the era of per se prohibitions concerning conduct because the answer to most close antitrust questions is that “it depends.” Certain variables or facts have greater implications on competition in one industry than in another, and a model that does not capture the importance of those factors for a given industry does not achieve the goal of accurately predicting effects. Empirical evidence may shed light on certain irrationalities of the marketplace, which should be observed and can be incorporated into this balancing, but the point remains that good judgment within the context of a consistent and coherent policy regime is what antitrust law truly needs.

Examining Case Law

Antitrust case law suggests that courts are not obsessed on selecting among complex economic models, but on interpreting available evidence regarding marketplace dynamics. From the mid- 1970s, by which time the Chicago School had gained recognition, to today, judges have shown hesitance to base their decisions on expert economic models, but instead have decided cases based on facts and available marketplace information.

One such case that comes to mind is FTC v.Coca-Cola, [9] where the FTC challenged Coke’s proposed acquisition of Dr. Pepper. In ruling for the FTC, U.S. District Judge of the D.C. District, Gerhard A. Gesell, relied not on the FTC economist’s predictive model showing that increased market concentration of the merged entity would reduce competition, but on the fact that post-merger, one of Coke’s foremost direct competitors would be removed from the marketplace, leaving PepsiCo as Coke’s only major competitor. Gessell wrote that because Congress “desire[d] to curb the economic concentration of power, it is unnecessary to speculate about the economic effect of the proposed acquisition. Without more, substantial mergers of this kind in heavily concentrated industries are presumed illegal.”

More recently, in In re Southeastern Milk Antitrust Litigation, [10] the court excluded an expert opinion on the relevant geographic market after the expert essentially admitted that his opinion, based on the vaunted Cournot economic model, did not follow the relevant Supreme Court standard on geographic market definition stated in Tampa Electric. [11] The U.S. District Court for the Eastern District of Tennessee noted that the expert’s theoretical model failed to consider certain marketplace realities, and thus misapplied the hypothetical monopolist test that satisfies the Tampa Electric standard when applied correctly. These cases, and others like them, show that judges who thoroughly interpret available marketplace information in making difficult decisions often reach a fair and reasonable result.

In cases where judges have relied on economic evidence, the results have sometimes strained logic. For example, in FTC v. Lundbeck, [12] the U.S. District Court in Minnesota rejected as unpersuasive the FTC’s expert testimony opining that drugs for a rare heart condition affecting premature babies were competitors based on sales data and ordinary course documents. Instead, the court credited an economist’s testimony that the cross-price elasticity between drugs was low, even though he had no calculations to prove it. The court recognized that the relevant drugs were functional substitutes, but maintained that they were not in the same relevant product market, ostensibly because of the FTC economist’s failure to speak to the level of cross elasticity of demand between the two functionally equivalent drugs. This decision shows that courts sometimes err in choosing among economic explanations, and even dismiss compelling marketplace information in doing so.

The theory of Ockham’s Razor states that, among competing models that explain a phenomenon, the simplest one is usually correct. If Ockham were a modern day antitrust commentator, he would probably find that the debate regarding the appropriate economic models and which schools of economic thought should guide antitrust decision making as unproductive. Regulators and judges must resolve actual, live controversies by using available data and information to predict whether conduct or a business combination will in fact harm consumers. Until there is robust empirical evidence establishing that one economic model or school has superior predictive capabilities over another, regulators and judges should focus not on what economic theory best applies to a given set of competitive conditions, but on the careful consideration of the relevant facts and marketplace evidence, including ordinary course documents, testimony of competent businesspeople, consumers and competitors, and other data reflecting market observations of the state of competition that exists in the relevant industry. Most important, courts should apply Einstein’s principle that if a theory or hypothesis can’t be explained simply, such a thesis is not understood well enough.


[1See, e.g., Serge Moresi & Steven C. Salop, “vGUPPI: Scoring Unilateral Pricing Incentives in Vertical Mergers” (Georgetown Bus., Econ. & Regulatory Law Research Paper No. 12-022), available at; Carl Shapiro, “The 2010 Horizontal Merger Guidelines: From Hedgehog to Fox in Forty Years,” 77 ANTITRUST L.J. 49 (2010).

[2See, e.g., Joshua D. Wright, “Abandoning Antitrust’s Chicago Obsession: The Case for Evidence-Based Antitrust,” 78 ANTITRUST L.J. 241, 253-57 (2012); Maurice E. Stucke, “Behavioral Economists at the Gate: Antitrust in the Twenty-First Century,” 38 LOY. U. CHI. L.J. 513 (2007).

[3See ROBERT BORK, THE ANTITRUST PARADOX (1978); Richard Posner, “The Chicago School of Antitrust Analysis,” 127 U. PA. L. REV. 925 (1979). See also Herbert Hovenkamp, “The Rationalization of Antitrust,” 116 HARV. L. REV. 917 (2003).

[4See, e.g., Su Sun, “Editor’s Note: Schools of Antitrust—a Parallelogram of Forces,” 78 ANTITRUST L.J. 37 (2012).

[5See Christine Jolls, Cass Sunstein and Richard Thaler, “A Behavioral Approach to Law and Economics,” 50 STAN. L. REV. 1471 (1998). See also Max Huffman, “Marrying Neo-Chicago with Behavioral Antitrust,” 78 ANTITRUST L.J. 105, 108-20 (2012); Amanda P. Reeves and Maurice E. Stucke, “Behavioral Antitrust,” 86 IND. L.J. 1527 (2011); Gregory Mitchell, “Taking Behavioralism Too Seriously? The Unwarranted Pessimism of the New Behavioral Analysis of Law,” 43 WM. & MARY L. REV. 1907 (2002).

[6See, e.g., Joshua D. Wright and Judd E. Stone, “Misbehavioral Economics: The Case Against Behavioral Antitrust,” 33 CARDOZO L. REV. 1517 (2012); Douglas H. Ginsburg and Derek W. Moore, “The Future of Behavioral Economics in Antitrust Jurisprudence,” Competition Pol’y Int’l, Spring 2010, at 97.

[7See J. Thomas Rosch, Comm’r, Fed. Trade Comm’n, Remarks before the Vienna Competition Conference: Behavioral Economics: Observations Regarding Issues That Lie Ahead 11 (June 9, 2010) (citing HERBERT HOVENKAMP, THE ANTITRUST ENTERPRISE: PRINCIPLE AND EXECUTION 134 (2005)).

[8See, e.g., Graeme Hunter, Gregory K. Leonard and G. Steven Olley, “Merger Retrospective Studies: A Review,” 23 ANTITRUST 34 (2008) (surveying studies in several industries and finding that “[although] the mergers that have been analyzed cannot in any sense be claimed to represent a random sample of all mergers or even “marginal” mergers, which have been closely scrutinized by the agencies[,]…the results from the studies reviewed here are mixed”).

[9641 F.Supp. 1128, 1133 (D.D.C. 1986), vacated on other grounds 829 F.2d 191 (D.C. Cir. 1987).

[10Master File No. 2:08-MD-1000, 2012 WL 947106 (E.D.Tenn. March 20, 2012).

[11Tampa Electric v. Nashville Coal, 365 U.S. 320 (1961).

[12Civil Nos. 08-6379 (JNE/JJG), 08-6381 (JNE/JJG), 2010 WL 3810015 (D. Minn. Aug. 31, 2010).

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