Today’s guest post is by Ai Deng, PhD, Bates White Economic Consulting.

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A few weeks ago, Professor Joseph Harrington of the University of Pennsylvania, whose work on cartel economics I first mentioned in another Cartel Capers post, kindly reached out and invited me to make a presentation on cartel issues (discussed here) at the 2016 CRESSE conference on “Advances in the Analysis of Competition Policy and Regulation (here).” I unfortunately cannot participate for both personal and work-related reasons. But it occurred to me that the readers of Cartel Capers may be interested in learning about this and other exciting events at CRESSE this summer. In addition to the 3-day conference, CRESSE also offers 2-week 7-module summer school on competition policy and regulation (here). These modules cover a wide range of antitrust economics, including discussions of industry economics and game theory, market dominance, cartels, mergers, IP, and competition policy and regulation. The detailed schedule can be found here. [Read more…]

Below is a guest post by my friend,  Osayomwanbor Bob Enofe, Sutherland School of Law Doctoral Scholar, UCD.

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The Federal Republic of Nigeria is currently in the process of enacting a competition law, including to criminalise cartel activity amongst competitors. While such is in line with moves made by various other jurisdictions and theories of ‘rational actor’, sanction and deterrence, on ground realities suggest that criminalisation where transplanted might be seriously flawed.

[Read more…]

Last week I attended at the ABA Antitrust Spring meeting, which is the highlight of the year for many in the antitrust bar. Excellent panels, renewing old friendships and making new ones, and open bars at the many receptions– what’s not to like. One program that is always my favorite is the Chair’s Showcase. This year the topic was the Per Se rule. Roxann Henry was the Chair and the stellar panelists were Seth Waxman, Stephen Calkins, Carl Shapiro, and Hillary Greene. The program was a high-level discussion of the history of the per se rule, the contours of the per se rule, and suggestions for possible changes to the rule. I won’t try to recount the whole session. But one part of the discussion focused on how to define hard-core per se behavior—you know, the kind that can land you in jail in the United States, even if you’re price fixing meeting was in Fiji. There was some discussion of whether an agreement can be hard-core if there are pro-competitive effects such as efficiencies and innovation. Is it hard-core per se if there are any vertical aspect to the agreement? There was no easy satisfactory answer, which raised the question, if it is difficult to define hard-core, how do you counsel clients? [Read more…]

The Antitrust Division published its annual Spring Newsletter in connection with the ABA Antitrust Spring Meeting.  The newsletter can be found here.  The newsletter covers highlights of all the Division’s major activities including criminal enforcement.  One highlight of the newsletter is the Division’s charts on criminal enforcement, including number of cases files, fines and average jail sentences.  These charts (here) often find their way into compliance or other presentations.

Also in the newsletter is a short YouTube video of Bill Baer speaking about the highlights of the past year.  Mr. Baer was recently elevated from his position as head of the Antitrust Division to Acting Associate Attorney General, the number three post in the Department of Justice.  Not much is expected to change at the Division, however, as Mr. Baer will still supervise the Antitrust Division in his new role.  Additionally, Renata Hesse, a current deputy at the Division, will assume the role of Acting Assistant Attorney General for the Antitrust Division.  Ms. Hesse has held many senior positions in the Antitrust Division, including a previous stint as Acting Assistant Attorney General.

Thanks for reading.

Below is a guest post by a regular Cartel Capers contributor Ai Deng PhD.  Mr. Deng is an economist with Bates White Economic Consulting.

Mind-reading salmon, the law of truly large numbers, and two recent Daubert rulings

Have you ever gotten an email saying that a large amount of money will be transferred to you if you first make some initial deposit? And if you immediately recognized that message as a scam, did you also wonder why people are still sending these emails?

With today’s technology, the cost of compiling even a large mailing list is small. The cost of sending out messages is even smaller. While the probability that 90% of the recipients will send money to a stranger is almost nil and the senders probably know that, they also know that the more people get the email, the better the odds that someone will be tricked. That potential payoff likely explains why such mailings continue.

In his book The Improbability Principle, David Hand, Emeritus Professor of Mathematics and a Senior Research Investigator at Imperial College London, calls this phenomenon “the Law of Truly Large Numbers.” He defines the principle succinctly: “With a large enough number of opportunities, any outrageous thing is likely to happen.”

The principle is at work more generally. In a 2011 Scientific American article, “The Mind-Reading Salmon,” Professor Charles Seife of Columbia University illustrated this point with drug efficacy testing. This testing compares the effectiveness of a drug with that of a placebo. Professor Seife pointed out that with a sufficiently large number of comparisons, it is almost guaranteed that at least one comparison will appear to show that a drug is “effective,” when, in fact, it is not.[1] In the same article, Professor Seife also recounted a study that a team of neuroscientists once conducted on a salmon:

When they presented the fish with pictures of people expressing emotions, regions of the salmon’s brain lit up. …; however, as the researchers argued, there are so many possible patterns that a statistically significant result was virtually guaranteed, so the result was totally worthless. …, there was no way that the fish could have reacted to human emotions. The salmon in the fMRI happened to be dead.

If proper care is not taken in such circumstances, statistical analysis runs the risk of what is known as “data snooping.” Other colorful names for this concept include “data dredging” and “data torturing.” [2] The term “data mining” is sometimes also used, although it means something different in other fields.

This topic has received attention in two recent Daubert rulings. In In re Processes Egg Products Antitrust Litigation, the plaintiffs’ expert used a regression model to relate prices to other factors. The defendants’ expert applied the same model to “just one certain defendant’s transactions” and argued that the model was unreliable because some aspects of the regression results had changed. The plaintiffs countered that the defendants’ results were “the product of inappropriate ‘data mining.’” District court Judge Gene E. K. Pratter (E.D. Pa.) found the plaintiffs’ argument to be intuitive and convincing for the purpose of assessing reliability under Daubert standards.

In In re Karlo v. Pittsburgh Glass Works, an age discrimination case, Judge Terrence F. McVerry (W.D. Pa.) found one expert’s analysis of impact to be “improper” because it did not correct for “the likelihood of a false indication of statistical significance.” He added that it was “data-snooping, plain and simple.”

With only public information, it is impossible to comment on the merits of the arguments in these cases. But it is encouraging that important yet sometimes subtle statistical issues are being discussed in the courts. In particular, given the precedents established in the two cases cited here, I will not be surprised if this topic is discussed more often and in other types of litigation.

Finally, I should mention that there is also a fun side to the Law of Truly Large Numbers. Just think of the Twin Strangers project, which tries to bring together total strangers who look like identical twins.

[Disclaimer: Bates White was not and is not, at the time of writing, involved in either case cited here.]

[1] Technically, the false inference of “effectiveness” mentioned here arises when it is based on some unadjusted statistical procedure. Certain adjustment or corrections to account for the phenomenon discussed here are well-known.

[2] While these terms may have a negative connotation, the concept itself is just a statistical phenomenon.

On March 1, 2016 Federal District Court Judge William Alsup sentenced Alex Yeh to six months in prison for his participation in the international cathode ray tubes (CRT) cartel. Yeh, a citizen of Taiwan, voluntarily agreed to come to the United States five years after he had been indicted. Taiwan has no extradition treaty with the United States. While Yeh had agreed to an eight-month sentence in a plea agreement with the Antitrust Division, the judge imposed a shorter sentence of six months. Mr. Yeh attended cartel meetings on behalf of Chunghwa. The company received a leniency deal, but after Mr. Yeh had left. To date, he is the only individual from the cartel to plead guilty and be sentenced. [Read more…]