Search Results

Last week I linked to my new study on “search bias.”  At the time I noted I would have a few blog posts in the coming days discussing the study.  This is the first of those posts.

A lot of the frenzy around Google turns on “search bias,” that is, instances when Google references its own links or its own content (such as Google Maps or YouTube) in its search results pages.  Some search engine critics condemn such references as inherently suspect and almost by their very nature harmful to consumers.  Yet these allegations suffer from several crucial shortcomings.  As I’ve noted (see, e.g., here and here), these naked assertions of discrimination are insufficient to state a cognizable antitrust claim, divorced as they are from consumer welfare analysis.  Indeed, such “discrimination” (some would call it “vertical integration”) has a well-recognized propensity to yield either pro-competitive or competitively neutral outcomes, rather than concrete consumer welfare losses.  Moreover, because search engines exist in an incredibly dynamic environment, marked by constant innovation and fierce competition, we would expect different engines, utilizing different algorithms and appealing to different consumer preferences, to emerge.  So when search engines engage in product differentiation of this sort, there is no reason to be immediately suspicious of these business decisions.

No reason to be immediately suspicious – but there could, conceivably, be a problem.  If there is, we would want to see empirical evidence of it—of both the existence of bias, as well as the consumer harm emanating from it.  But one of the most notable features of this debate is the striking lack of empirical data.  Surprisingly little research has been done in this area, despite frequent assertions that own-content bias is commonly practiced and poses a significant threat to consumers (see, e.g., here).

My paper is an attempt to rectify this.  In the paper, I investigate the available data to determine whether and to what extent own-content bias actually occurs, by analyzing and replicating a study by Ben Edelman and Ben Lockwood (E&L) and conducting my own study of a larger, randomized set of search queries.

In this post I discuss my analysis and critique of E&L; in future posts I’ll present my own replication of their study, as well as the results of my larger study of 1,000 random search queries.  Finally, I’ll analyze whether any of these findings support anticompetitive foreclosure theories or are otherwise sufficient to warrant antitrust intervention.

E&L “investigate . . . [w]hether search engines’ algorithmic results favor their own services, and if so, which search engines do most, to what extent, and in what substantive areas.”  Their approach is to measure the difference in how frequently search engines refer to their own content relative to how often their rivals do so.

One note at the outset:  While this approach provides useful descriptive facts about the differences between how search engines link to their own content, it does little to inform antitrust analysis because Edelman and Lockwood begin with the rather odd claim that competition among differentiated search engines for consumers is a puzzle that creates an air of suspicion around the practice—in fact, they claim that “it is hard to see why results would vary . . . across search engines.”  This assertion, of course, is simply absurd.  Indeed, Danny Sullivan provides a nice critique of this claim:

It’s not hard to see why search engine result differ at all.  Search engines each use their own “algorithm” to cull through the pages they’ve collected from across the web, to decide which pages to rank first . . . . Google has a different algorithm than Bing.  In short, Google will have a different opinion than Bing.  Opinions in the search world, as with the real world, don’t always agree.

Moreover, this assertion completely discounts both the vigorous competitive product differentiation that occurs in nearly all modern product markets as well as the obvious selection effects at work in own-content bias (Google users likely prefer Google content).  This combination detaches E&L’s analysis from the consumer welfare perspective, and thus antitrust policy relevance, despite their claims to the contrary (and the fact that their results actually exhibit very little bias).

Several methodological issues undermine the policy relevance of E&L’s analysis.  First, they hand select 32 search queries and execute searches on Google, Bing, Yahoo, AOL and Ask.  This hand-selected non-random sample of 32 search queries cannot generate reliable inferences regarding the frequency of bias—a critical ingredient to understanding its potential competitive effects.  Indeed, E&L acknowledge their queries are chosen precisely because they are likely to return results including Google content (e.g., email, images, maps, video, etc.).

E&L analyze the top three organic search results for each query on each engine.  They find that 19% of all results across all five search engines refer to content affiliated with one of them.  They focus upon the first three organic results and report that Google refers to its own content in the first (“top”) position about twice as often as Yahoo and Bing refer to Google content in this position.  Additionally, they note that Yahoo is more biased than Google when evaluating the first page rather than only the first organic search result.

E&L also offer a strained attempt to deal with the possibility of competitive product differentiation among search engines.  They examine differences among search engines’ references to their own content by “compar[ing] the frequency with which a search engine links to its own pages, relative to the frequency with which other search engines link to that search engine’s pages.”  However, their evidence undermines claims that Google’s own-content bias is significant and systematic relative to its rivals’.  In fact, almost zero evidence of statistically significant own-content bias by Google emerges.

E&L find, in general, Google is no more likely to refer to its own content than other search engines are to refer to that same content, and across the vast majority of their results, E&L find Google search results are not statistically more likely to refer to Google content than rivals’ search results.

The same data can be examined to test the likelihood that a search engine will refer to content affiliated with a rival search engine.  Rather than exhibiting bias in favor of an engine’s own content, a “biased” search engine might conceivably be less likely to refer to content affiliated with its rivals.  The table below reports the likelihood (in odds ratios) that a search engine’s content appears in a rival engine’s results.

The first two columns of the table demonstrate that both Google and Yahoo content are referred to in the first search result less frequently in rivals’ search results than in their own.  Although Bing does not have enough data for robust analysis of results in the first position in E&L’s original analysis, the next three columns in Table 1 illustrate that all three engines’ (Google, Yahoo, and Bing) content appears less often on the first page of rivals’ search results than on their own search engine.  However, only Yahoo’s results differ significantly from 1.  As between Google and Bing, the results are notably similar.

E&L also make a limited attempt to consider the possibility that favorable placement of a search engine’s own content is a response to user preferences rather than anticompetitive motives.  Using click-through data, they find, unsurprisingly, that the first search result tends to receive the most clicks (72%, on average).  They then identify one search term for which they believe bias plays an important role in driving user traffic.  For the search query “email,” Google ranks its own Gmail first and Yahoo Mail second; however, E&L also find that Gmail receives only 29% of clicks while Yahoo Mail receives 54%.  E&L claim that this finding strongly indicates that Google is engaging in conduct that harms users and undermines their search experience.

However, from a competition analysis perspective, that inference is not sound.  Indeed, the fact that the second-listed Yahoo Mail link received the majority of clicks demonstrates precisely that Yahoo was not competitively foreclosed from access to users.  Taken collectively, E&L are not able to muster evidence of potential competitive foreclosure.

While it’s important to have an evidence-based discussion surrounding search engine results and their competitive implications, it’s also critical to recognize that bias alone is not evidence of competitive harm.  Indeed, any identified bias must be evaluated in the appropriate antitrust economic context of competition and consumers, rather than individual competitors and websites.  E&L’s analysis provides a useful starting point for describing how search engines differ in their referrals to their own content.  But, taken at face value, their results actually demonstrate little or no evidence of bias—let alone that the little bias they do find is causing any consumer harm.

As I’ll discuss in coming posts, evidence gathered since E&L conducted their study further suggests their claims that bias is prevalent, inherently harmful, and sufficient to warrant antitrust intervention are overstated and misguided.

Filed under: antitrust, business, economics, google, Internet search, law and economics, monopolization, technology Tagged: antitrust, Bing, google, search, search bias, Search Engines, search neutrality, Web search engine, Yahoo

Summary

Search engines produce immense value by identifying, organizing, and presenting the Internet´s information in response to users´ queries.1 Search engines efficiently provide better and faster answers to users´ questions than alternatives.

Recently, critics have taken issue with the various methods search engines use to identify relevant content and rank search results for users. Google, in particular, has been the subject of much of this criticism on the grounds that its organic search results—those generated algorithmically—favor its own products and services at the expense of those of its rivals. It is widely understood that search engines´ algorithms for ranking various web pages naturally differ. Likewise, there is widespread recognition that competition among search engines is vigorous, and that differentiation between engines´ ranking functions is not only desirable, but a natural byproduct of competition, necessary to survival, and beneficial to consumers.2 Nonetheless, despite widespread recognition of the consumer benefits of such differentiation, complaints from rival search engines have persisted and succeeded in attracting attention from a number of state, federal and international regulatory agencies. Unfortunately, much of this attention has focused on the impact upon individual websites of differences among search engines´ algorithmic methods of identifying and ranking relevant content, rather than analyzing these differences from a conventional consumer?welfare driven antitrust analysis.

For example, many of these complaints ignore the fact that search engine users self?select into different engines or use multiple engines for different types of searches when considering the competitive implications of search rankings.3 Rather than focus upon competition among search engines in how results are identified and presented to users, critics and complainants craft their arguments around alleged search engine “discrimination” or “bias.”4 The complainants must have in mind something other than competitive decisions to rank content that differ from the decisions made by rivals; bias in this sense is both necessary to and inherent within any useful indexing tool. Yet, critics have generally avoided a precise definition of the allegedly troublesome conduct. Indeed, the term “bias” is used colloquially and is frequently invoked in the search engine debate to encompass a wide array of behavior—generally suggesting a latent malignancy within search engine conduct—with some critics citing mere differences in results across engines as evidence of harmful conduct.5

The more useful attempts to define “bias,” however, focus upon differences in organic rankings attributable to the search engine ranking its own content (“owncontent bias”); that is, a sufficient condition for own?content bias is that a search engine ranks its own content more prominently than its rivals do. To be even more precise about the nature of the alleged “own?content bias,” it should be clear that this form of  bias refers exclusively to organic results, i.e., those results the search engine produces algorithmically, as distinguished from the paid advertisements that might appear at the top, bottom, or right?hand side of a search result page.6 Critics at the Senate’s recent hearing on the “Power of Google” were particularly vociferous on this front, accusing Google of having “cooked”7 its algorithm and of “rig[ging] its results, biasing in favor of Google.”8

Competition economists and regulatory agencies are familiar with business arrangements which give rise to concerns of own?content bias.9 Complaints and economic theories of harm assert that a vertically integrated firm (in this case, Google offers search results as well as products like YouTube and Google Maps) might discriminate against its rivals by “foreclosing” them from access to a critical input. Here, the critical input necessary for rivals´ success is alleged to be prominent placement in Google´s search results. The economics of the potential anticompetitive exclusion of rivals involving vertically integrated firms are well understood in antitrust. The conditions that must be satisfied for these concerns to generate real risk to consumers are also well known. Over a century of antitrust jurisprudence, economic study, and enforcement agency practice have produced a well?understood economic analysis of the competitive effects of a vertically integrated firm´s “discrimination” in favor of its own products or services, including widespread recognition that such arrangements generally produce significant benefits for consumers. Modern competition policy recognizes that vertical integration and contractual arrangements are generally procompetitive; it also understands that discrimination of this sort may create the potential for competitive harm under some conditions. Sensible competition policy involving vertical integration and contractual arrangements requires one to be sensitive to the potential consumer welfare?enhancing potential of such vertical integration while also taking seriously the possibility that a firm might successfully harm competition itself (and not merely a rival).

In addition to the failure to distinguish procompetitive conduct from anticompetitive behavior, critics´ allegations of own?content bias suffer deeper conceptual ambiguities. The perceived issue for Google´s rivals is not merely that Google links to a map when responding to search queries, suggesting one might be  relevant for the user; indeed, rival search engines frequently respond to similar user queries with their own or other map products. Rather, critics find problematic that Google responds to user queries with a Google Map. This is a critical distinction because it concedes that rivals´ complaints are not satisfied by the response that consumers are better off with the map; nor do critics pause to consider that perhaps the Google search user prefers the Google Map to rival products.10 Thus, critics brazenly take issue with the relationship between Google and the search result even where they concede Google produces more relevant results for consumers.11 Rather than focusing upon consumers, critics argue that the fact that Google is affiliated with the referred search result is itself prima facie evidence of competitively harmful bias.12 On its face, this argument turns conventional antitrust wisdom on its head. Conduct that harms rivals merely because it attracts consumers from rivals is the essence of competition and the logical core of the maxim that antitrust protects “competition, not competitors.?13

Critics´ failure to account for the potential consumer benefits from ?own?content bias? extends beyond ignoring the fact that users might prefer Google´s products to rivals´. Most critics simply ignore the myriad of procompetitive explanations for vertical integration in the economics literature. This omission by critics, and especially by economist critics, is mystifying given that economists have documented not only a plethora of procompetitive justifications for such integration, but also that such vertical relationships are much more likely to be competitively beneficial or benign than to raise serious threats of foreclosure.14

The critical antitrust question is always whether the underlying conduct creates or maintains monopoly power and thus reduces competition and consumer welfare, or is more likely efficient and procompetitive. To be clear, documenting the mere existence of own?content bias itself does little to answer this question. Bias is not a sufficient condition for competitive harm as a matter of economics because it can increase, decrease, or have no impact at all upon consumer welfare; neither is bias, without more, sufficient to state a cognizable antitrust claim.15

Nonetheless, documenting whether and how much of the alleged bias exists in Google´s and its rivals´ search results can improve our understanding of its competitive implications—that is, whether the evidence of discrimination in favor of one´s own content across search engines is more consistent with anticompetitive foreclosure or with competitive differentiation.

Critically, in order to generate plausible competitive concerns, search bias must, at minimum, be sufficient in magnitude to foreclose rivals from achieving minimum efficient scale (otherwise, if it merely represents effective competition that makes life harder for competitors, it is not an antitrust concern at all). It follows from this necessary condition that not all evidence of ?bias? is relevant to this competitive concern; in particular, Google referring to its own products and services more prominently than its rivals rank those same services has little to do with critics´ complaints unless they implicate general or vertical search.

Despite widespread discussion of search engine bias, virtually no evidence exists indicating that bias abounds—and very little that it exists at all. Edelman & Lockwood recently addressed this dearth of evidence by conducting a small study focused upon own?content bias in 32 search queries. They contend that their results are indicative of systemic and significant bias demanding antitrust intervention.16 The authors define and measure ?bias? as the extent to which a search engine´s ranking of its own content differs from how its rivals rank the same content. This approach provides some useful information concerning differences among search engine rankings. However, the study should not be relied upon to support broad sweeping antitrust policy concerns with Google.

The small sample of search queries provides one reason for caution. Perhaps more importantly, the non?random sample of search queries undermines its utility for addressing the critical antitrust policy questions focusing upon the magnitude of search bias, both generally and as it relates to whether the degree and nature of observed bias satisfies the well?known conditions required for competitive foreclosure. Further, evaluating their evidence at face value, Edelman & Lockwood misinterpret its relevance (Edelman & Lockwood in fact find almost no evidence of bias) and, most problematically, simply assume that own?content bias is inherently suspect from a consumer welfare perspective rather than considering the well?known consumer benefits of vertical integration. Despite these shortcomings, Edelman & Lockwood´s study has received considerable attention, both in the press and from Google´s critics, who cite it as evidence of harmful and anticompetitive search engine behavior.17 In the present analysis, as a starting point, we first “replicate” and analyze Edelman & Lockwood´s earlier study of a small, non?random sample of search queries in the modern search market. We then extend this methodology to a larger random sample of search queries in order to draw more reliable inferences concerning the answers to crucial questions for the competition policy debate surrounding search engine bias, including: (1) what precisely is search engine bias?; (2) what are its  competitive implications?; (3) how common is it?; (4) what explains its existence and relative frequency across search engines?; and, most importantly, (5) does observed search engine bias pose a competitive threat or is it a feature of competition between search engines?

Part I of this paper articulates an antitrust?appropriate framework for analyzing claims of “own?content bias” and delineates its utility and shortcomings as a theory of antitrust harm; it further evaluates Edelman & Lockwood’s study, methodology and analysis using this framework. Part II lays out the methodology employed in our own studies. Part III presents the results of our replication of Edelman & Lockwood and analyzes antitrust implications for the search engine bias debate; Part IV does the same for our larger, random sample of search queries. Part V concludes.

Our search neutrality paper has received some recent attention.  While the initial response from Gordon Crovitz in the Wall Street Journal was favorable, critics are now voicing their responses.  Although we appreciate FairSearch’s attempt to engage with our paper’s central claims, its response is really little more than an extended non-sequitur and fails to contribute to the debate meaningfully.

Read the full piece here.

Excerpt

Ten years ago this week, an appeals court upheld Microsoft’s conviction for monopolizing the PC operating system market. The decision became a key legal precedent for U.S. antitrust enforcement. It also cemented the government’s confidence in its ability to pick winners and losers in fast-moving technology markets–a confidence not borne out by subsequent events.

Now this sad history seems to be repeating itself: By uncanny coincidence, news broke just last Friday that the FTC had begun an antitrust investigation into Google’s business practices. Unfortunately, there’s no reason to expect the outcome to be any better for consumers this time around.

There is, in fact, no evidence that the case against Microsoft or its settlement contributed to the spectacular innovation in the IT sector over the last decade. Indeed, they may even have solidified Microsoft’s role as the perennial also-ran in this latest wave of technological progress, as the company struggled to keep innovating under the threat of constant antitrust scrutiny in the U.S. and abroad.

The true lesson of the Microsoft case is this: antitrust intervention in information technology has a poor track record of serving consumers. Even Harvard law professor Lawrence Lessig, who was a court-appointed Special Master in that case and has since championed government tinkering with the Internet, finally admitted in 2007 that he “blew it on Microsoft” by underestimating the potential for innovation and market forces to dethrone Microsoft, particularly through the rise of open-source software (which now in part powers Apple’s popular iOS).

Continue reading on C-NET

No surprise here.  The WSJ announced it was coming yesterday, and today Google publicly acknowledged that it has received subpoenas related to the Commission’s investigation.  Amit Singhal of Google acknowledged the FTC subpoenas at the Google Public Policy Blog…

Read the full piece here.

Josh and I have just completed a white paper on search neutrality/search bias and the regulation of search engines.  The paper is this year’s first in the ICLE Antitrust & Consumer Protection White Paper Series:

If Search Neutrality Is the Answer, What’s the Question?

 

Geoffrey A. Manne

(Lewis & Clark Law School and ICLE)

and

Joshua D. Wright

(George Mason Law School & Department of Economics and ICLE)

In this paper we evaluate both the economic and non-economic costs and benefits of search bias. In Part I we define search bias and search neutrality, terms that have taken on any number of meanings in the literature, and survey recent regulatory concerns surrounding search bias. In Part II we discuss the economics and technology of search. In Part III we evaluate the economic costs and benefits of search bias. We demonstrate that search bias is the product of the competitive process and link the search bias debate to the economic and empirical literature on vertical integration and the generally-efficient and pro-competitive incentives for a vertically integrated firm to discriminate in favor of its own content. Building upon this literature and its application to the search engine market, we conclude that neither an ex ante regulatory restriction on search engine bias nor the imposition of an antitrust duty to deal upon Google would benefit consumers. In Part V we evaluate the frequent claim that search engine bias causes other serious, though less tangible, social and cultural harms. As with the economic case for search neutrality, we find these non-economic justifications for restricting search engine bias unconvincing, and particularly susceptible to the well-known Nirvana Fallacy of comparing imperfect real world institutions with romanticized and unrealistic alternatives

Search bias is not a function of Google’s large share of overall searches. Rather, it is a feature of competition in the search engine market, as evidenced by the fact that its rivals also exercise editorial and algorithmic control over what information is provided to consumers and in what manner. Consumers rightly value competition between search engine providers on this margin; this fact alone suggests caution in regulating search bias at all, much less with an ex ante regulatory schema which defines the margins upon which search providers can compete. The strength of economic theory and evidence demonstrating that regulatory restrictions on vertical integration are costly to consumers, impede innovation, and discourage experimentation in a dynamic marketplace support the conclusion that neither regulation of search bias nor antitrust intervention can be justified on economic terms. Search neutrality advocates touting the non-economic virtues of their proposed regime should bear the burden of demonstrating that they exist beyond the Nirvana Fallacy of comparing an imperfect private actor to a perfect government decision-maker, and further, that any such benefits outweigh the economic costs.

CLICK HERE TO DOWNLOAD THE PAPER

 

Filed under: announcements, antitrust, economics, error costs, essential facilities, exclusionary conduct, google, law and economics, markets, monopolization, technology, truth on the market Tagged: antitrust, foundem, google, search, search bias, Search Engines, search neutrality, tradecomet, Vertical integration

[UPDATE:  Josh links to a WSJ article telling us that EU antitrust enforcers raided several (unnamed) e-book publishers as part of an apparent antitrust investigation into the agency model and whether it is “improperly restrictive.”  Whatever that means.  Key grafs:

At issue for antitrust regulators is whether agency models are improperly restrictive. Europe, in particular, has strong anticollusion laws that limit the extent to which companies can agree on the prices consumers will eventually be charged.

Amazon, in particular, has vociferously opposed the agency practice, saying it would like to set prices as it sees fit. Publishers, by contrast, resist the notion of online retailers’ deep discounting.

It is unclear whether the animating question is whether the publishers might have agreed to a particular pricing model, or to particular prices within that model.  As a legal matter that distinction probably doesn’t matter at all; as an economic matter it would seem to be more complicated–to be explored further another day . . . .]

A year ago I wrote about the economics of the e-book publishing market in the context of the dispute between Amazon and some publishers (notably Macmillan) over pricing.  At the time I suggested a few things about how the future might pan out (never a god good idea . . . ):

And that’s really the twist.  Amazon is not ready to be a platform in this business.  The economic conditions are not yet right and it is clearly making a lot of money selling physical books directly to its users.  The Kindle is not ubiquitous and demand for electronic versions of books is not very significant–and thus Amazon does not want to take on the full platform development and distribution risk.  Where seller control over price usually entails a distribution of inventory risk away from suppliers and toward sellers, supplier control over price correspondingly distributes platform development risk toward sellers.  Under the old system Amazon was able to encourage the distribution of the platform (the Kindle) through loss-leader pricing on e-books, ensuring that publishers shared somewhat in the costs of platform distribution (from selling correspondingly fewer physical books) and allowing Amazon to subsidize Kindle sales in a way that helped to encourage consumer familiarity with e-books.  Under the new system it does not have that ability and can only subsidize Kindle use by reducing the price of Kindles–which impedes Amazon from engaging in effective price discrimination for the Kindle, does not tie the subsidy to increased use, and will make widespread distribution of the device more expensive and more risky for Amazon.

This “agency model,” if you recall, is one where, essentially, publishers, rather than Amazon, determine the price for electronic versions of their books sold via Amazon and pay Amazon a percentage.  The problem from Amazon’s point of view, as I mention in the quote above, is that without the ability to control the price of the books it sells, Amazon is limited essentially to fiddling with the price of the reader–the platform–itself in order to encourage more participation on the reader side of the market.  But I surmised (again in the quote above), that fiddling with the price of the platform would be far more blunt and potentially costly than controlling the price of the books themselves, mainly because the latter correlates almost perfectly with usage, and the former does not–and in the end Amazon may end up subsidizing lots of Kindle purchases from which it is then never able to recoup its losses because it accidentally subsidized lots of Kindle purchases by people who had no interest in actually using the devices very much (either because they’re sticking with paper or because Apple has leapfrogged the competition).

It appears, nevertheless, that Amazon has indeed been pursuing this pricing strategy.  According to this post from Kevin Kelly,

In October 2009 John Walkenbach noticed that the price of the Kindle was falling at a consistent rate, lowering almost on a schedule. By June 2010, the rate was so unwavering that he could easily forecast the date at which the Kindle would be free: November 2011.

There’s even a nice graph to go along with it:

So what about the recoupment risk?  Here’s my new theory:  Amazon, having already begun offering free streaming videos for Prime customers, will also begin offering heavily-discounted Kindles and even e-book subsidies–but will also begin rescinding its shipping subsidy and otherwise make the purchase of dead tree books relatively more costly (including by maintaining less inventory–another way to recoup).  It will still face a substantial threat from competing platforms like the iPad but Amazon is at least in a position to affect a good deal of consumer demand for Kindle’s dead tree competitors.

For a take on what’s at stake (here relating to newspapers rather than books, but I’m sure the dynamic is similar), this tidbit linked from one of the comments to Kevin Kelly’s post is eye-opening:

If newspapers switched over to being all online, the cost base would be instantly and permanently transformed. The OECD report puts the cost of printing a typical paper at 28 per cent and the cost of sales and distribution at 24 per cent: so the physical being of the paper absorbs 52 per cent of all costs. (Administration costs another 8 per cent and advertising another 16.) That figure may well be conservative. A persuasive looking analysis in the Business Insider put the cost of printing and distributing the New York Times at $644 million, and then added this: ‘a source with knowledge of the real numbers tells us we’re so low in our estimate of the Times’s printing costs that we’re not even in the ballpark.’ Taking the lower figure, that means that New York Times, if it stopped printing a physical edition of the paper, could afford to give every subscriber a free Kindle. Not the bog-standard Kindle, but the one with free global data access. And not just one Kindle, but four Kindles. And not just once, but every year. And that’s using the low estimate for the costs of printing.

Filed under: antitrust, business, cartels, contracts, doj, e-books, economics, error costs, law and economics, litigation, MFNs, monopolization, resale price maintenance, technology, vertical restraints Tagged: agency model, Amazon, Amazon Kindle, antitrust, Apple, doj, e-book, e-books, iBookstore, Kindle, major publishers, MFN, most favored nations clause, per se, price-fixing, publishing industry, Rule of reason, two-sided markets, vertical restraints

Economist and occasional TOTM guest blogger Steve Salop (Georgetown) recently sent me the following questions spurred by the local debate over Governor McConnell’s proposal to private the retailing of alcoholic beverages…

Read the full piece here. 

Connecticut AG Richard Blumenthal has reportedly contacted Apple and Amazon concerning their pricing arrangements with publishers (WSJ, CNN):

Mr. Blumenthal said he has sent letters to Amazon and Apple asking them to “meet with his office” to address his concerns that agreements in place may restrict rivals from offering cheaper e-books. For instance, he said, “both Amazon and Apple have reached agreements with the largest e-book publishers that ensure both will receive the best prices for e-books over any competitors.”

A “most favored nation” (MFN) clause is a contractual agreement between a supplier and a customer that requires the supplier to sell to the customer on pricing terms at least as favorable as the pricing terms on which that supplier sells to other customers.

Read the full piece here.