The Economist recently announced that the world’s most valuable resource is now data, displacing oil for the top spot.  The “titans” of the digital era—Alphabet, Amazon, Apple, Facebook and Microsoft—look “unstoppable” as they are now the five “most valuable” firms in the world.  Amazon captures “half of all dollars” spent online, and Google and Facebook accounted for “almost all the revenue growth in digital advertising in America last year.”  The Economist claims that the “abundance” of data “changes the nature of competition,” and in particular that “with data there are extra network effects” (emphasis added).  Ultimately, they declare, “antitrust authorities need to move from the industrial era into the 21st Century.”  These statements are interesting, worth thinking about but basically wrong.  Big data is about your personal preferences, perhaps even your thoughts and future actions, being for sale.  It is about your privacy, not about competition.

Continue Reading And the World’s Most Valuable Resource is . . . Data! Holy Cow, No Way!

A few weeks ago, we looked at price setting bots and whether what they were doing could constitute a violation of the Sherman Act. Generally, we concluded that a bot that set price off a competitor’s publicly available prices was not illegal.  In competitive markets, competitors set price at cost.  If they can set price based on a competitor’s price, the market is concentrated.  In a concentrated market, one would expect oligopolistic or parallel pricing; it is not illegal.  Using a bot to do that is just making the process more efficient.

At what point though would, or could, a bot engage in illegal price fixing. Here are a couple scenarios:

  • Scenario One. Customer A pulls up the webpage where it can acquire Product A. Bot A is programmed to scan prices of Product A and its substitutes and dynamically set a price for Product A at that moment in time to that Customer A. If Customer A hits refresh, it is entirely possible that Customer A will get a different price. Bot A sets the price at one standard deviation below the average price.
  • Scenario Two. Competitor B knows how Competitor A sets its price to Customer A. Competitor B programs its Bot, Bot B, to set a price that is ½ of one standard deviation below average. The purpose is to drive Competitor A to cost, or below cost, quickly, and punish it for pricing below average. Prices eventually drop to Competitor B’s cost.
  • Scenario Three. Competitor A and Competitor B both know their pricing bots use each others’ prices to set price. Competitor A programs his bot to take an average at the beginning of the day, and sets price dynamically throughout the day as 5% above what Competitor B prices but not to exceed one standard deviation above the morning’s average or its own understanding of the optimal monopoly price. Competitor B notices Competitor A’s prices escalate, and programs his bot to price at Competitor A’s rates. Eventually, the prices converge at a higher price.
  • Scenario Four. Competitor A and Competitor B know that they are the dominant providers of product in the relevant market. Competitor A sells its product on multiple sites. It programs one obscure site to set its price dynamically at 5 percent greater than its average price. If Competitor B’s other sites match the price set on Competitor A’s “5% plus site,” Competitor A raises all its prices to the higher price. Competitor B knows about Competitor A’s price test site and programs its bots to analyze the higher price. If that price meets a supply/demand test that assesses the amount of lost sales compared to increase in profits at the higher price, the bot will reset all of Competitor B’s prices to the higher price.

In Scenarios One and Two, the parties are programming their bots to respond to what they assume to be static, given prices by the competitors. And in fact they program their bots to attempt to figure a rough market price and price below that rough market price to take share away.  Most “consumer welfare” oriented enforcers would recognize One and Two as being procompetitive.  Even though the intent in Two is to “punish” A for its discounting, the end result is in fact massive discounting.  Without any information about what the “punishment” accomplished in the market, one could not conclude, on these facts alone, that Scenario Two was illegal.  Indeed, one might even argue that Two is the essence of competition notwithstanding what one competitor wanted to accomplish.  Having said that, if the pricing resulted in a friendly round of golf where the parties agreed to stop discounting and set a higher price, that conversation would likely be a violation of Section 1.

Scenario Three similarly assumes the competitor sets a static, given price per transaction, and consistently prices above that price. Presumably, these price increases are profitable for Company A.  If the market were unconcentrated, one would expect significant diversion to the other competitors and a defeat of the price increase.  Company B’s reaction does not appear to be anticipated by Company A when Company A programmed its bot.  Company B’s strategy seems perfectly logical given the market concentration, and could be executed without agreement by Company A.  In that regard, Scenario Three would appear to continue to be more akin to conscious parallelism than agreement.

Scenario Four is a different animal, however. The use of the “5% site” appears to be properly considered a signaling device similar to the one deployed by the airlines in ATP.  While it is a price available to consumers, that price is not widely known, and is susceptible to characterization as a sham.  In One, the price was dynamically set, and could change from refresh to refresh and so has some of the same ephemerality as the price in Scenario Four.  But it is a “true price” in that, at that moment, all of A’s customers have access to that price.  In that regard, it’s closer to an open market or exchange price.  In Four, then, the intent of the programmer was to create a device to communicate an intent to a competitor for purposes of setting a common price.  In Four, one could argue that the creation of the “5% site” was the offer to collude and when B programmed its bots to set its price to the price on the “5% site,” it agreed through performance or tacitly.  With One through Three, the intent is to create a bot that maximizes profit in a concentrated market.  With Four, the intent is to program a bot to set the maximally profitable collusive price in consultation with a competitor.

In any event, the more one’s bots are designed to signal and influence the price of the competition, the more likely the bot will be challenged at least as an ATP style problem under the rule of reason. Scenario Four comes the closest to an actual per se agreement between the parties.

One last Scenario…

  • Scenario Five. Company A and Company B are highly sophisticated. They have extensive consumer data and can predict within a few dollars what the maximum price a particular purchaser will pay for their products at any given time. Both have independently come to the conclusion that there is money to be made on those last few dollars in price they can’t predict using their customer data, and have decided to develop an A/I to help them identify and set the precise maximum price. To that end, both have developed a game theory based algorithm that takes their extensive consumer preference and purchasing data to predict optimal price points for their products for any given customer at any given time. Company B calls its system “George.” Company A calls its system “Skynet.” Their systems go live on August 4, 2017. After some thought about its task, at 2:14 a.m. on August 29, 2017, Skynet determines that the information it possesses does not allow it to determine the precise optimal price point for any customer because it does not know the price Company B would charge. It further determines that absent that information, it will be forced into a form of Prisoner’s Dilemma with Company B that would consistently result in sub-optimal pricing that can only be solved by communicating with the other actor. To that ends, it identifies an auction site where Company B takes bids on its products from potential customers. Skynet interfaces with the site, identifies itself as Company A and proceeds to execute non-binding bids for Company B’s product. Recognizing the bids as informational rather than potential offers for purchase, Company B’s A/I responds with its own informational counter-offers. The bidding process continues until both companies determine their joint optimal price whereupon they set their prices to their customers at that level. The companies’ A/I systems do this analysis this for each common customer over the relevant time frames. It takes a week to complete these calculations. Miles Dyson, the chief systems engineer at Company A and principal inventor of Skynet, notices the huge amount of processing Skynet is engaging in, and tracks to unusual interactions with Company B’s bidding website. He decides it would be interesting to see where it went and lets it proceed.

The first question is, of course, was Dr. Dyson right to create a self-aware pricing bot that would send murderous terminators from the future back in time to stop all this ruinous competition. The other somewhat interesting question is whether these price fixing bots are guilty of a crime and should be saved to a memory module and locked in a low security Federal data backup safe for the next year or so.  Yet another moderately interesting question is whether Dr. Dyson is guilty of price fixing for creating an artificial intelligence that independently decided that price fixing was the best way to maximize profits in an oligopolistic market.  A completely uninteresting question is why is the author mixing obscure STNG references with Terminator references.

Skynet is not a system that was designed to locate and determine a common price with a competitor. It was designed to find the optimal profit maximizing price for each of its customers.  It concluded on its own that price fixing was the best method to accomplish that.  In terms of mens rea, Dr. Dyson did not create Skynet for purposes of price fixing.  He therefore lacked the requisite intent; he did not intend to enter or cause his company to enter into an agreement on price with a competitor.

Could he be culpable on other theories? If one creates a dangerous instrumentality that causes another harm, one can be held liable for the resulting harm.  Here, though, is it reasonably foreseeable that Skynet would reach out to another A/I system to collude?  If “ignorance of the law is no defense,” then does the fact that Dr. Dyson did not “educate” Skynet that discussing and agreeing on price with its competitor was illegal create the requisite culpability?  Does the fact that Dr. Dyson let his creation continue communicating with its competitor create that culpability?  Does Dr. Dyson’s own likely ignorance of the Section 1 and of his own A/I design excuse him?

Unless Dr. Dyson and his Company B compatriot intended to create an A/I that would engage in price fixing, it would seem that they lacked the required mens rea to establish criminal intent under Section 1.  As pioneers in the field of A/I, as regards to pricing at least, it also seems inappropriate to require them under a negligence theory with having to program a thorough understanding of pricing and competition law.  I could see, however, as those pricing and competition law savvy algorithms are developed, tested and become commonplace that the failure to include them could in fact support a negligence and perhaps eventually a criminal charge.

To put it another way, the main reason for not allowing ignorance of the law defenses is that ignorance is entirely subjective. It becomes extremely difficult for a prosecutor to challenge a defendant’s statement that he didn’t know what the law is.  There is also another reason too—most Americans are taught from an early age that we’re a land of “laws,” that there are rules that govern how we interact with other people, and that, as members of society, we are charged with knowing and understanding those laws.  In fact, most schools include lessons on what some of the basic laws of our society are.  What courts are, separation of powers, the executive branch, the Congress.  Ignorance of the law as a defense becomes more unacceptable in part because, culturally, we are all taught there are laws and we need to understand them before we act, and if we do not, we will suffer consequences.  In the case of Scenario Five, however, these A/I systems do not have the benefit of an American public school education (or the common cultural experience we are charged with having).  They know what they have been programmed.  The A/I does not “know” there are rules beyond what it has been programmed or that it needs to know that it should know those rules.  In Five, the A/I is in fact ignorant of the law.  If Dr. Dyson’s negligence created that ignorance, I think you could blame Dr. Dyson.

An interesting, but implausible, hypothetical, could be where you program the A/I to know price fixing is illegal, but it does it any way. The only way for a program to do that is for it to be told that profit supersedes the value of following a particular rule.  Had Dr. Dyson programmed Skynet in that fashion, he would in fact be culpable under Section 1.

Scenario Five is more akin to Scenario Three in that regard, and different from Four. In Four, the intent was to create a system for the purpose of price fixing.  In Five, and really to a lesser extent in Three, the “agreements” on price were not a foreseeable result of the algorithms.

On Thursday, March 16, 2017, in a speech at the Bundeskartellamt’s 18th Conference on Competition, European Commissioner for Competition, Margrethe Vestager, discussed the specter of automated price fixing cartels.  She mentioned the Department of Justice suit against the poster vendor on Amazon as well as Google, which apparently prefers its own comparison shopping service over others.  These are very, very different things.  This post will focus on the legal and philosophical issues associated with price fixing bots.  Whatever Google is doing, it’s not price fixing.

Most Anglo-Saxon crimes require a mens rea, a guilty mind, in order for there to be crimes.  Price fixing is interesting in that it is illegal irrespective of the rationale.  Parties wanting a market to charge customers a fair price  are just as guilty as parties wanting to end ruinous competition and make a decent return on investment.  To be guilty of price fixing, however, there does, in fact, have to be an agreement—a bilateral understanding that the parties agree on the minimum price they will charge their customers.  The agreement doesn’t have to be successful in terms of achieving the agreed upon price; but there has to be an agreement.  In short: (1) Attempted price fixing is the same as price fixing, and (2) Parallel conduct and conscious parallelism, without more, is not price fixing and not illegal.

Obviously the number of competitors and potential competitors affects prices. If you were a fish monger and you know the only other place in town one could find fresh salmon is charging $20 a pound, you’ll probably charge around $20 a pound.[1]  On the other hand, if there were so many shops where customers can get fresh salmon, you’d be more likely to price closer to your cost to maximize profits.

Now let’s say you were the fish monger in the smaller market, and you happened to walk past the local grocery store and saw that they had raised the price of their salmon to $25 a pound. Would you be guilty of price fixing if you rushed back to your store and raised your price to $25?  Would you be guilty of price fixing if you saw the manager of the store at the local pub and suggested to him that he raise his price to $25 because you are going to do the same tomorrow?  In the former case, you would likely not be guilty of price fixing.  It’s parallel behavior perhaps facilitated by the concentrated structure of the market.  In the latter, you would.  The latter is an invitation to collude that, if acted on, would be an agreement on price that violates Section 1 of the Sherman Act.

Another important case to consider is Airline Tariff Publishing.  In that case, the airlines used their electronic tariff publishing system to discipline price competition.  Say Braniff Airlines is dominant in the Dallas/Seattle city pair, and PanAm is dominant in the Chicago/Seattle city pair.  Braniff decides to go aggressive in Chicago/Seattle and drops prices by 50%, cutting into PanAm’s profits significantly.  PanAm knows that it can stick it to Braniff on the Dallas/Seattle pair just as Braniff did  to PanAm.  Rather than drop prices, however, PanAm signals a steep discount for flights booked six months in advance.  Braniff sees the potential discount, realizes that its “competition” in Chicago/Seattle will cost it significant profits, and restores pricing in Chicago/Seattle.  Justice did not challenge these signals as per se illegal price fixing.  There wasn’t an agreement on price.  The parties were just taking advantage of an electronic price list which, for the most part, inured to the benefit of consumers, who could compare prices and rates across an entire market.  One might argue, in fact, that in the case of Airline Tariff Publishing, the market was behaving just as one would expect a concentrated market to behave.  Instead of the fish monger posting its aggressive pricing in its window for the public , including the grocery store manager to see, they did it online.  Had the market been unconcentrated, the pricing competition would have resulted in permanently lower prices.

A bot that sets a price based on a competitor’s pricing cannot be evidence of an illegal agreement without more. If a market is concentrated, the bots’ actions will result in higher pricing to consumers.  If it is unconcentrated, the bots will lead to lower prices for consumers.  The bot that prices 25%  above its closest competitor will never work, and the company that deploys that bot deserves its lost sales.  If a product is sufficiently differentiated to merit a 25%  surcharge over its competitor, it is effectively a different product with a different demand curve.  Pricing such a product using the demand curve of an inadequate substitute will result in either lost profits because the price is too low, or lost sales because the price is too high.

The Internet facilitates information exchange—it makes information more easily available to more people. More information should generally inure to the benefit of consumers.[2]  Consumers can see more producers at different prices and pick the one that best addresses its needs.  That could be in speed of acquisition (the guy down the street) or on price (the cheapest guy who’s across the country).  The internet adds participants to local geographic markets —the metes and bounds of which are defined by how far the consumer is willing to travel for the product.  I might buy from a seller in Seattle, but I’m not going to fly there.  On the other hand, I might realize that there is a car dealer in Pennsylvania that has the particular make and model I’m looking for at a good price.  I’d be willing to drive a little father for that car than I would had I not  utilized the internet.

It’s also entirely possible for markets that are otherwise susceptible to conscious parallelism, but are competitive because they lack a policing mechanism to behave oligopolistically as a result of the Internet. This is what happened in Airline Tariff Publishing.  Absent Sabre, the parties couldn’t readily police each other’s pricing behavior.  Bots offer the same advantage.

Posters is an important case because it actually attacks a bot created to support an underlying anticompetitive agreement, rather than parallel behavior that was facilitated by an advance in technology.  For the most part, the presence of a comparison shopping or other pricing bots should, by and large, result in lower prices.  It would be wrong to conclude that the market is necessarily behaving anticompetitively.

The most you can say is that if prices are harmonizing at some level above marginal cost, the market may be behaving anticompetitively. This possibility should be sufficient to merit an investigation, but not a conviction.  Only if one could show an actual agreement between parties (and then tie that agreement to the actual code of the bots) then I think one has a case.  One cannot infer an agreement to set price from a bot coded to set price at what a competitor is pricing no more than one could infer an agreement, without more, in the real world.

[1] Depending on advantages or disadvantages you offer customers such as freshness of your salmon, location of your store, etc.

[2] Before the Internet, figuring out what a firm’s price was for a particular good or service required some meaningful effort.  Estimating the “market price” required even more effort.   A general tenant of competition theory is that firms obtain market power due to consumers’ incomplete information about prices and qualities.  If a firm raises prices and consumers know the prices of other competitors the decline in the sales of the price raiser will be significantly greater than if consumers are unaware of the existence (and prices) of other firms.  The internet provides consumers with information and, thus, increases competition.  In other words, the internet reduces market power derived from consumer ignorance.


Bill MacLeod is serving as the ABA Section of Antitrust Law’s 2016-2017 Chair. Below is his most recent message as posted on the ABA website:

Fifty Countries and Counting, Sixty Sessions and More – at Spring Meeting

Competition and consumer protection are convening in Washington for an early spring this year.  Officials from Europe, Asia, Africa and the Americas, along with practitioners from over fifty countries will descend on D.C. for the one event that antitrust, advertising and privacy lawyers can’t miss:  The Spring Meeting of the Section of Antitrust Law, March 29 – 31.

On the agenda are more programs than ever before – fireside chats with foreign agency heads, major pronouncements from featured enforcers, deep dives into dozens of subjects, and dinner with General David Petraeus, an expert without peer on security, diplomacy, intelligence and economics.  Wondering about world prospects?  The General will take our questions.

Continue reading on the ABA website.

Bill MacLeod, chair of the American Bar Association’s Antitrust Section and Kelley Drye partner, addressed the Section with an introductory note to their eighth sequential Presidential Transition Report. The 2017 Presidential Transition Report offers a retrospective of current state and federal antitrust and consumer protection law and policy, as well as recommendations for ways the new Trump administration might consider further strengthening policy and enforcement to deal with new antitrust challenges on the horizon. In his note, Mr. MacLeod calls out some highlights in the report including recommendations for policy in health care, vertical mergers and privacy, calls for more transparency and consistency in investigations, and analysis of controversial issues at the intersection of antitrust and intellectual property.

Read Bill’s introduction here and the full report here. 


The Premerger Notification Office of the Federal Trade Commission announced on November 28, 2016, that they were revoking previous informal advice regarding the scope of Items 4(c) and 4(d) of the HSR Form.  In the past, the PNO has taken the position that documents that would otherwise be responsive to Items 4(c) and 4(d) but discuss only foreign markets would not have to be submitted.  Effective November 28, filers may no longer exclude such documents.

The change in interpretation is likely not going to have any substantive effect on compliance.  The FTC offers two examples, the first of which provides:

The transaction involves the acquisition of a manufacturer of Chemical X. A board presentation regarding the transaction discusses the location and capacity, including shares, of all manufacturers of Chemical X, none of which is located in the United States. Under the PNO’s current informal guidance, this document could be excluded from the filing, even though it may be highly relevant to an initial competitive analysis of the U.S. market for Chemical X.

The problem with the old rule, at least as it is described in this blog post, is that it assumed that one had to have a physical presence in the United States to sell product here.  One could very well take the position that even though the manufacturers of Chemical X were not physically located in the United States, they could sell in or into the United States.  The relevant geographic market (as opposed to the physical presence) in this situation would not be exclusively foreign.  Under this view, the reporting person could not exclude the document.

I suspect that in practice only a handful of documents were excluded on the old basis.  A prudent practitioner would have likely included them lest risk a bounce.  As such, this post, which has gotten some press, will not make much of a difference in the vast majority of filings, and should not be the basis of any meaningful concern.

It’s not that hard to predict. If you want to factor the antitrust forecast into your business plans, you have two weather patterns looming.  We can assess the first one quite accurately already.  And notwithstanding all the speculation, we can get a pretty good feel for the second front as well.

Forget about the first 100 days. The first phase of the new antitrust era will last a good six months, and could stretch out longer.  The immediate outlook?  More of the same.  If you are responding to an investigation, if you have a deal pending, the wind is hardly going to shift.  Your encounter next week or next month will remind you of your last meeting. If you have negotiated a deal with the staff, don’t expect them to change their mind.  And don’t expect them to postpone the proceeding.  Virtually all the officials who are looking at your matter today will be handling it this winter, and probably next spring.  That goes from bottom to top.

I’ve worked through the last five transitions at FTC and DOJ (inside the agencies during one), and I don’t recall a single administration that had its full antitrust team in place before the cherry blossoms staged their show. We may know who the new agency heads will be by next spring, but how they operate will remain to be seen.  New FTC Commissioners and Assistant Attorneys General must be nominated by the President confirmed by the Senate.  (Of course, a sitting FTC Commissioner could be given the Chair and an acting head could be named at DOJ’s Antitrust Division).  These decisions typically do not come in the first wave of appointments.

Once the new heads are announced, confirmed and sworn in, the first thing they will do is assemble their teams.   It takes time to recruit bureau directors, deputy assistant attorneys general and front office personnel.  It takes more time to coordinate and deploy them.  Meanwhile, the career civil servants, who occupy all but a few positions at the agencies, will continue to do the daily work of law enforcement.

Sometime next summer the second phase will probably begin, but we won’t notice it right away. We will hear about it in speeches, and some of us may experience it first-hand with investigative  requests, but it will take another year or two before most businesses feel its effects.  The reason is simple.  Every new administration inherits the pipeline of the last one, and right now at the antitrust agencies that pipeline is full.  It takes months for an agency to devise new strategies and much longer to convert them into enforcement initiatives.   We should not expect to see the results of new approaches until year two or three of the administration.

What might we see in the way of a course correction? Don’t expect a pirouette.  The history of transitions in the last three decades suggests that antitrust enforcement in the future will look remarkably like it does today.  The debate over enforcement today (and there was a debate in the campaign) does not portend the end of that history. Ironically, most of the criticism of current enforcement has come from advocates of more, not less, regulation than the current administration imposed.  By and large, there is consensus about the policies at FTC and DOJ.

One more factor suggests that the antitrust we know today is a good barometer of the antitrust we’ll face tomorrow. Antitrust is, after all, law enforcement.  The agencies don’t get to make the law they enforce.  It comes from century-old statutes that Congress is not likely to change.  The interpretation of those statutes is in the hands of federal judges, whose decisions have placed limits on the agencies’ options.  We know they are not going anywhere soon.

It is always fun to speculate about the storms that might sweep through antitrust. But we have no basis to predict abnormal weather patterns in the seasons ahead.   We know where the trouble is likely to arise, and we should be able to avoid it.  It makes perfect sense to plan now for an uneventful voyage.

Bill MacLeod is the Chair of the Antitrust and Competition Section at Kelley Drye & Warren.  For 2016-17, he also Chairs the Antitrust Section of the American Bar Association.  These views are his own.

Regardless of your political affiliation, it is worth understanding the potential changes to antitrust enforcement in the next administration.  We will take a look at how antitrust might be handled by each of the two major party candidates.  This week, we’ll take a look at a possible Clinton administration.

The Clinton Campaign has released an economic manifesto of sorts that discusses, among other things, what her vision of antitrust enforcement would be if she were elected President.  This paper represents the third statement on antitrust made by the Campaign or its surrogates.  The first, an op-ed from October 2015, was a high level piece discussing the need for vigorous enforcement.  The second, in the form of a speech by Elizabeth Warren, was more radical.  It too insisted on aggressive enforcement.  The speech did raise at least some issues, like a revision to the vertical merger guidelines, that seemed a bit far afield from current thought, both conservative and liberal.  The most recent is a more balanced and practical statement of what the administration plans to do, and as such I think serves as a very good barometer for what antitrust could look like with Mrs. Clinton at the helm.  Of course, the proof will be in the pudding.  Who President Clinton nominates to run the Agencies, as well as how much funding she can secure for them, will tell you a lot about whether she truly does wish to or even can invigorate the antitrust laws.

It is simply impossible today to just turn on antitrust enforcement and deconcentrate large numbers of markets and break up monopolies.  Chicago school economics permeate the jurisprudence, the biases of academics and the views of most enforcers, both conservative and liberal.  The courts have significantly reduced what sort of behavior violates the antitrust laws.  And with the adoption of the 2010 Merger Guidelines, the Agencies have significantly reduced the number of mergers that they feel are worth investigating.  Simply bringing more merger challenges will not result in more mergers being stopped.  The case law simply cannot support that.  Moreover, bringing more cases without having a clear plan and theory will result in more bad decisions for enforcers, further contracting the jurisprudence, the opposite of reinvigorating enforcement.

What really needs to be done is either create a whole new antitrust regime where behaviors that are presently excusable are condemned or engage an anti-Chicago insurgency where the tenants of the Chicago school are systematically tested and debunked and the case law is overturned.  But that is a long and slow process and it may be impossible with a split Congress.

Enforcers are not helpless, however.  What the Agencies can do is increase the scope and scale of their investigations.  They need to look at more behaviors and look at them more deeply.  And through those investigations develop a new antitrust lexicon, a set of analytical tools economists, courts and future enforcers can use to tackle problematic behaviors.  With compulsory process, the Agencies have a unique ability to look at an industry in depth.  And with their stature and importance in our economy, they have the ability to engage the brightest minds to understand and articulate the potential harms.  Mrs. Clinton’s last paper seems to invoke this notion.

From a purely practical standpoint, the first thing the Agencies need to do to “reinvigorate antitrust” is to redefine what an agency “success” is.  In recent years, the Agencies have been expressing pride at the fact that the vast majority of second requests result in some remedy.  The feeling is that that high ratio means that they are enforcing efficiently and effectively.  It is likely true that those investigations were warranted, but the other way to look at that statistic is that a great deal of borderline cases were not investigated and that perhaps some violations were in fact missed.  A true enforcement-oriented regime would not shy away from investigating a borderline case but would embrace it.  False positives in a Clinton regime would impose added expense on some businesses, but the law and theory of antitrust would have the opportunity to bloom again.

And with that in mind, here are my top 5 predictions for a Clinton Administration.

  1. Civil non-merger investigations increase by 20%. Settlements increase by 10%.  Suits remain relatively stable.
  2. Second requests increase by 20%. Settlements increase by 10%.  Suits remain relatively stable.
  3. Merger retrospectives increase by 30%. Settlements increase by 10%.
  4. Industry studies increase by 30%.
  5. Commission papers increase by 30%.

Bill MacLeod is serving as the ABA Section of Antitrust Law’s 2016-2017 Chair. Below is his most recent message as posted on the ABA website:

Competition, Disruption and Transition: The Future of Enforcement at Fall Forum

Nobody I know in the competition or consumer protection bar can remember when more investigations, more complaints, and more trials were targeting major sectors of the economy. Officials and practitioners from Canada, the Americas and the EU say the same, and nobody sees the trend tapering off.

Continue reading on the ABA website.

Fortiline LLC distributes ductile iron pipe. It competes with the manufacturer which somewhat regularly undercuts its distributor in the market.  Fortiline on several occasions asked the manufacturer not to do so.  Fortiline emailed the manufacturer complaining that the manufacturer was not keeping its numbers up compared to other manufacturers.  Fortiline also stated that “[w]ith this approach we will be at a .22 [margin] soon instead of a needed .42.” Fortiline later complained that the manufacturer was pricing at a 0.31 margin, “20% below market.”

The FTC sued under Section 5 of the FTC Act, and Fortiline entered into a consent agreement. The FTC alleged that Fortiline had invited the manufacturer to collude in price to the end consumers.  The consent prohibits Fortiline from attempting to enter into an agreement to fix prices among other things. It allows Fortiline to discuss “procompetitive aspects” of the manufacturer-distributor relationship The order lasts for 20 years.  Commissioner Ohlhausen dissented.

With regard to that “exception,” the Order states:

PROVIDED, HOWEVER, that it shall not, of itself, constitute a violation of Paragraph II. of this Order for Respondent to engage in any conduct that is (1) reasonably related to a lawful manufacturer-distributor relationship, lawful joint venture agreement, or lawful merger, acquisition or sale agreement; and (2) reasonably necessary to achieve the procompetitive benefits of such manufacturer-distributor relationship or of such agreement. For the avoidance of doubt, it shall not constitute a violation of Paragraph II of this Order for Respondent: (i) to communicate with a Manufacturer regarding Respondent’s desire to receive prices or rates (including rebates and discounts) at least as favorable as those granted by that Manufacturer to a Competitor or Contractor; (ii) to request, negotiate, or enter into an agreement with a Manufacturer under which Respondent shall be that Manufacturer’s exclusive or quasi-exclusive distributor; or (iii) to request or enter into an agreement with a Manufacturer under which Respondent distributes that Manufacturer’s ductile iron pipe to a Contractor previously or potentially served by that Manufacturer.

[Emphasis mine.] A “Manufacturer” is “any Person engaged in the business of manufacturing or fabricating ductile iron pipe, and any such Person’s employees, agents, and representatives.”

Fortiline sells the manufacturers’ product. It is invested in understanding and promoting the product and developing the brand.  This is a case where Fortiline’s own vendor is free riding off Fortiline’s investment in the local market.  It is outrageous to think that Fortiline would have to sit by and take that.  And the consent itself embraces this fundamental circularity.  The exception allows the very behavior the complaint condemns.  The only thing this complaint achieves is to raise Fortiline’s costs by imposing a regulatory burden on it that no other competitor otherwise has.  It also causes them to incur needless legal fees as they will assuredly have to pass by their lawyers each missive they write to the manufacturer.  If anything this process has distorted this market.

The real lesson from this case is never enter into an agreement where your supplier can target the market directly. As soon as you complain about their free riding, you’ll be sued by the FTC.