Search Results

In my last post, I discussed Edelman & Lockwood’s (E&L’s) attempt to catch search engines in the act of biasing their results—as well as their failure to actually do so.  In this post, I present my own results from replicating their study.  Unlike E&L, I find that Bing is consistently more biased than Google, for reasons discussed further below, although neither engine references its own content as frequently as E&L suggest.

I ran searches for E&L’s original 32 non-random queries using three different search engines—Google, Bing, and Blekko—between June 23 and July 5 of this year.  This replication is useful, as search technology has changed dramatically since E&L recorded their results in August 2010.  Bing now powers Yahoo, and Blekko has had more time to mature and enhance its results.  Blekko serves as a helpful “control” engine in my study, as it is totally independent of Google and Microsoft, and so has no incentive to refer to Google or Microsoft content unless it is actually relevant to users.  In addition, because Blekko’s model is significantly different than Google and Microsoft’s, if results on all three engines agree that specific content is highly relevant to the user query, it lends significant credibility to the notion that the content places well on the merits rather than being attributable to bias or other factors.

How Do Search Engines Rank Their Own Content?

Focusing solely upon the first position, Google refers to its own products or services when no other search engine does in 21.9% of queries; in another 21.9% of queries, both Google and at least one other search engine rival (i.e. Bing or Blekko) refer to the same Google content with their first links.

But restricting focus upon the first position is too narrow.  Assuming that all instances in which Google or Bing rank their own content first and rivals do not amounts to bias would be a mistake; such a restrictive definition would include cases in which all three search engines rank the same content prominently—agreeing that it is highly relevant—although not all in the first position. 

The entire first page of results provides a more informative comparison.  I find that Google and at least one other engine return Google content on the first page of results in 7% of the queries.  Google refers to its own content on the first page of results without agreement from either rival search engine in only 7.9% of the queries.  Meanwhile, Bing and at least one other engine refer to Microsoft content in 3.2% of the queries.  Bing references Microsoft content without agreement from either Google or Blekko in 13.2% of the queries:

This evidence indicates that Google’s ranking of its own content differs significantly from its rivals in only 7.9% of queries, and that when Google ranks its own content prominently it is generally perceived as relevant.  Further, these results suggest that Bing’s organic search results are significantly more biased in favor of Microsoft content than Google’s search results are in favor of Google’s content.

Examining Search Engine “Bias” on Google

The following table presents the percentages of queries for which Google’s ranking of its own content differs significantly from its rivals’ ranking of that same content.

Note that percentages below 50 in this table indicate that rival search engines generally see the referenced Google content as relevant and independently believe that it should be ranked similarly.

So when Google ranks its own content highly, at least one rival engine typically agrees with this ranking; for example, when Google places its own content in its Top 3 results, at least one rival agrees with this ranking in over 70% of queries.  Bing especially agrees with Google’s rankings of Google content within its Top 3 and 5 results, failing to include Google content that Google ranks similarly in only a little more than a third of queries.

Examining Search Engine “Bias” on Bing

Bing refers to Microsoft content in its search results far more frequently than its rivals reference the same Microsoft content.  For example, Bing’s top result references Microsoft content for 5 queries, while neither Google nor Blekko ever rank Microsoft content in the first position:

This table illustrates the significant discrepancies between Bing’s treatment of its own Microsoft content relative to Google and Blekko.  Neither rival engine refers to Microsoft content Bing ranks within its Top 3 results; Google and Blekko do not include any Microsoft content Bing refers to on the first page of results in nearly 80% of queries.

Moreover, Bing frequently ranks Microsoft content highly even when rival engines do not refer to the same content at all in the first page of results.  For example, of the 5 queries for which Bing ranks Microsoft content in its top result, Google refers to only one of these 5 within its first page of results, while Blekko refers to none.  Even when comparing results across each engine’s full page of results, Google and Blekko only agree with Bing’s referral of Microsoft content in 20.4% of queries.

Although there are not enough Bing data to test results in the first position in E&L’s sample, Microsoft content appears as results on the first page of a Bing search about 7 times more often than Microsoft content appears on the first page of rival engines.  Also, Google is much more likely to refer to Microsoft content than Blekko, though both refer to significantly less Microsoft content than Bing.

A Closer Look at Google v. Bing

On E&L’s own terms, Bing results are more biased than Google results; rivals are more likely to agree with Google’s algorithmic assessment (than with Bing’s) that its own content is relevant to user queries.  Bing refers to Microsoft content other engines do not rank at all more often than Google refers its own content without any agreement from rivals.  Figures 1 and 2 display the same data presented above in order to facilitate direct comparisons between Google and Bing.

As Figures 1 and 2 illustrate, Bing search results for these 32 queries are more frequently “biased” in favor of its own content than are Google’s.  The bias is greatest for the Top 1 and Top 3 search results.

My study finds that Bing exhibits far more “bias” than E&L identify in their earlier analysis.  For example, in E&L’s study, Bing does not refer to Microsoft content at all in its Top 1 or Top 3 results; moreover, Bing refers to Microsoft content within its entire first page 11 times, while Google and Yahoo refer to Microsoft content 8 and 9 times, respectively.  Most likely, the significant increase in Bing’s “bias” differential is largely a function of Bing’s introduction of localized and personalized search results and represents serious competitive efforts on Bing’s behalf.

Again, it’s important to stress E&L’s limited and non-random sample, and to emphasize the danger of making strong inferences about the general nature or magnitude of search bias based upon these data alone.  However, the data indicate that Google’s own-content bias is relatively small even in a sample collected precisely to focus upon the queries most likely to generate it.  In fact—as I’ll discuss in my next post—own-content bias occurs even less often in a more representative sample of queries, strongly suggesting that such bias does not raise the competitive concerns attributed to it.

Filed under: antitrust, business, economics, google, Internet search, law and economics, monopolization, technology Tagged: antitrust, Bias, Bing, Blekko, google, microsoft, search, Web search engine, Yahoo

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.

Stewart Baker at the Volokh Conspiracy has a very interesting post on the new Amazon browser.  He thinks it might revolutionize doing business on the Web, with a tremendous increase in security.  This increase in security will entail a loss in privacy, so let’s hope the privacy guys don’t stop it.

Filed under: business, Internet search, markets, privacy Tagged: Amazon’s new browser

In the last post, I discussed possible characterizations of Google’s conduct for purposes of antitrust analysis.  A firm grasp of the economic implications of the different conceptualizations of Google’s conduct is a necessary – but not sufficient – precondition for appreciating the inconsistencies underlying the proposed remedies for Google’s alleged competitive harms.  In this post, I want to turn to a different question: assuming arguendo a competitive problem associated with Google’s algorithmic rankings – an assumption I do not think is warranted, supported by the evidence, or even consistent with the relevant literature on vertical contractual relationships – how might antitrust enforcers conceive of an appropriate and consumer-welfare-conscious remedy?  Antitrust agencies, economists, and competition policy scholars have all appropriately stressed the importance of considering a potential remedy prior to, rather than following, an antitrust investigation; this is good advice not only because of the benefits of thinking rigorously and realistically about remedial design, but also because clear thinking about remedies upfront might illuminate something about the competitive nature of the conduct at issue.

Somewhat ironically, former DOJ Antitrust Division Assistant Attorney General Tom Barnett – now counsel for Expedia, one of the most prominent would-be antitrust plaintiffs against Google – warned (in his prior, rather than his present, role) that “[i]mplementing a remedy that is too broad runs the risk of distorting markets, impairing competition, and prohibiting perfectly legal and efficient conduct,” and that “forcing a firm to share the benefits of its investments and relieving its rivals of the incentive to develop comparable assets of their own, access remedies can reduce the competitive vitality of an industry.”  Barnett also noted that “[t]here seems to be consensus that we should prohibit unilateral conduct only where it is demonstrated through rigorous economic analysis to harm competition and thereby harm consumer welfare.”  Well said.  With these warnings well in-hand, we must turn to two inter-related concerns necessary to appreciating the potential consequences of a remedy for Google’s conduct: (1) the menu of potential remedies available for an antitrust suit against Google, and (2) the efficacy of these potential remedies from a consumer-welfare, rather than firm-welfare, perspective.

What are the potential remedies?

The burgeoning search neutrality crowd presents no lack of proposed remedies; indeed, if there is one segment in which Google’s critics have proven themselves prolific, it is in their constant ingenuity conceiving ways to bring governmental intervention to bear upon Google.  Professor Ben Edelman has usefully aggregated and discussed several of the alternatives, four of which bear mention:  (1) a la Frank Pasquale and Oren Bracha, the creation of a “Federal Search Commission,” (2) a la the regulations surrounding the Customer Reservation Systems (CRS) in the 1990s, a prohibition on rankings that order listings “us[ing] any factors directly or indirectly relating to” whether the search engine is affiliated with the link, (3) mandatory disclosure of all manual adjustments to algorithmic search, and (4) transfer of the “browser choice” menu of the EC Microsoft litigation to the Google search context, requiring Google to offer users a choice of five or so rivals whenever a user enters particular queries.

Geoff and I discuss several of these potential remedies in our paper, If Search Neutrality is the Answer, What’s the Question?  It suffices to say that we find significant consumer welfare threats from the creation of a new regulatory agency designed to impose “neutral” search results.  For now, I prefer to focus on the second of these remedies – analogized to CRS technology in the 1990s – here; Professor Edelman not only explains proposed CRS-inspired regulation, but does so in effusive terms:

A first insight comes from recognizing that regulators have already – successfully! – addressed the problem of bias in information services. One key area of intervention was customer reservation systems (CRS’s), the computer networks that let travel agents see flight availability and pricing for various major airlines. Three decades ago, when CRS’s were largely owned by the various airlines, some airlines favored their own flights. For example, when a travel agent searched for flights through Apollo, a CRS then owned by United Airlines, United flights would come up first – even if other carriers offered lower prices or nonstop service. The Department of Justice intervened, culminating in rules prohibiting any CRS owned by an airline from ordering listings “us[ing] any factors directly or indirectly relating to carrier identity” (14 CFR 255.4). Certainly one could argue that these rules were an undue intrusion: A travel agent was always free to find a different CRS, and further additional searches could have uncovered alternative flights. Yet most travel agents hesitated to switch CRS’s, and extra searches would be both time-consuming and error-prone. Prohibiting biased listings was the better approach.

The same principle applies in the context of web search. On this theory, Google ought not rank results by any metric that distinctively favors Google. I credit that web search considers myriad web sites – far more than the number of airlines, flights, or fares. And I credit that web search considers more attributes of each web page – not just airfare price, transit time, and number of stops. But these differences only grant a search engine more room to innovate. These differences don’t change the underlying reasoning, so compelling in the CRS context, that a system provider must not design its rules to systematically put itself first.

The analogy is a superficially attractive one, and we’re tempted to entertain it, so far as it goes.  Organizational questions inhere in both settings, and similarly so: both flights and search results must be ordinally ranked, and before CRS regulation, a host airline’s flights often appeared before those of rival airlines.  Indeed, we will take Edelman’s analogy at face value.  Problematically for Professor Edelman and others pushing the CRS-style remedy, a fuller exploration of CRS regulation reveals this market intervention – well, put simply, wasn’t so successful after all.  Not for consumers anyway.  It did, however, generate (economically) predictable consequences: reduced consumer welfare through reduced innovation. Let’s explore the consequences of Edelman’s analogy further below the fold.

History of CRS Antitrust Suits and Regulation

Early air travel primarily consisted of “interline” flights – flights on more than one carrier to reach a final destination.  CRSs arose to enable airlines to coordinate these trips for their customers across multiple airlines, which necessitated compiling information about rival airlines, their routes, fares, and other price- and quality-relevant information.  Major airlines predominantly owned CRSs at this time, which served both competitive and cooperative ends; this combination of economic forces naturally drew antitrust advocates’ attention.

CRS regulation proponents proffered numerous arguments as to the potentially anticompetitive nature and behavior of CRS-owning airlines.  For example, they claimed that CRS-owning airlines engaged in “dirty tricks,” such as using their CRSs to terminate passengers’ reservations on smaller, rival airlines and to rebook customers on their own flights, and refusing to allow smaller airlines to become CRS co-hosts, thereby preventing these smaller airlines from being listed in search results.  CRS-owning airlines faced further allegations of excluding rivals through contractual provisions, such as long-term commitments from travel agents.  Proponents of antitrust enforcement alleged that the nature of the CRS market created significant barriers to entry and provided CRS-owning airlines with significant cost advantages to selling their own flights.  These cost advantages purportedly derived from two main sources: (1) quality advantages that airline-owned CRSs enjoyed, as they could commit to providing comprehensive and accurate information about the owner airline’s flight schedule, and (2) joint ownership of CRSs, which facilitated coordination between airlines and CRSs, thereby decreasing the distribution and information costs.

These claims suffered from serious shortcomings including both a failure to demonstrate harm to competition rather than injury to specific rivals as well as insufficient appreciation for the value of dynamic efficiency and innovation to consumer welfare.  These latter concerns were especially pertinent in the CRS context, as CRSs arose at a time of incredible change – the deregulated airline industry, joined with novel computer technology, necessitated significant and constant innovation.  Courts accordingly generally denied antitrust remedies in these cases – rejecting claims that CRSs imposed unreasonable restraints on competition, denied access to an essential facility, or facilitated monopoly leverage.

Yet, particularly relevant for present purposes, one of the most popular anticompetitive stories was that CRSs practiced “display bias,” defined as ranking the owner airline’s flights above those of all other airlines.  Proponents claimed display bias was particularly harmful in the CRS setting, because only the travel agent, and not the customer, could see the search results, and travel agents might have incentives to book passengers on more expensive flights for which they receive more commission.  Fred Smith describes the investigations surrounding this claim:

These initial CRS services were used mostly by sophisticated travel agents, who could quickly scroll down to a customer’s preferred airline.  But this extra “effort” was considered discriminatory by some at the DOJ and the DOT, and hearings were held to investigate this threat to competition.  Great attention was paid to the “time” required to execute only a few keystrokes, to the “complexity” of re-designing first screens by computer-proficient travel agents, and to the “barriers” placed on such practices by the host CRS provider.

CRS Rules

While courts declined to intervene in the CRS market, the Department of Transportation (DOT) eagerly crafted rules to govern CRS operations.  The DOT’s two primary goals in enacting the 1984 CRS regulations were (1) to incentivize entry into the CRS market and (2) to prevent airline ownership of CRSs from decreasing competition in the downstream passenger air travel market.  One of the most notable rules introduced in the 1984 CRS regulations prohibited display bias.  The DOT changed both this rule and CRS rules as a whole significantly, and by 1997, the DOT required each CRS “(i) to offer at least one integrated display that uses the same criteria for both online and interline connections and (ii) to use elapsed time or non-stop itinerary as a significant factor in selecting the flight options from the database” (Alexander, 2004).  However, the DOT did not categorically forbid display bias; rather, it created several exceptions to this rule – and even allowed airlines to disseminate software that introduced bias into displays.  Additionally, the DOT expressly refused to enforce its anti-bias rules against travel agent displays.

Other CRS rules attempted to reinforce these two goals of additional market entry and preservation of downstream competition.  CRS rules specifically focused on mitigating travel agent switching costs between CRS vendors and reducing any quality advantage incumbent CRSs allegedly had.  Rules prohibited discriminatory booking fees and the tying of travel agent commissions to CRS use, limited contract lengths, prohibited minimum uses and rollover clauses, and required CRSs to give all participating carriers equal service upgrades.

Evidence of CRS Regulation “Success”?

The CRS regulatory experiment had years to run its course; despite the extent and commitment of its regulatory sweep, these rules failed to improve consumer outcomes in any meaningful way.  CRS regulations precipitated neither innovation nor entry, and likely incurred serious allocative efficiency and consumer welfare losses by attempting to prohibit display bias.

First, CRS regulations unambiguously failed in their goal of increasing ease of entry:

Only six CRS vendors offered their services to domestic airlines and travel agents in the mid-1980s. . . If the rules had actually facilitated entry, the number of CRS vendors should have grown or some new entrants should have been seen during the past twenty years.  The evidence, however, is to the contrary.  It remains that ‘[s]ince the [CAB] first adopted CRS rules, no firm has entered the CRS business.’  Meanwhile, there has been a series of mergers coupled with introduction of multinational CRS; the cumulative effect was to reduce the number of CRSs. . . Even if a regulation could successfully facilitate entry by a supplier of CRS services, the gain from such entry would at this point be relatively small, and possibly negative. (Alexander and Lee, 2004) (emphasis added).

As such, CRS regulations did not achieve one of their primary objectives – a fact which stands in stark contrast to Edelman’s declaration that CRS rules represent an unequivocal regulatory success.

Most relevant to the search engine bias analogy, the CRS regulations prohibiting bias did not positively affect consumer welfare.  To the contrary, by ignoring the reality that most travel agents took consumer interests into account in their initial choice of CRS operator (even if they do so to a lesser extent in each individual search they conduct for consumers), and that even if residual bias remained, consumers were “informed and repeat players who have their own preferences,” CRS regulations imposed unjustified costs.  As Alexander and Lee describe it

[T]he social value of prohibiting display . . . bias solely to improve the quality of information that consumers receive about travel options appears to be low and may be negative.  Travel agents have strong incentives to protect consumers from poor information, through how they customize their internal display screens, and in their choices of CRS vendors.

Moreover, and predictably, CRS regulations appear to have caused serious harm to the competitive process:

The major competitive advantage of the pre-regulation CRS was that it permitted the leading airlines to slightly disadvantage their leading competitors by placing them a bit farther down on the list of available flights.  United would place American slightly farther down the list, and American would return the favor for United flights.  The result, of course, was that the other airlines received slightly higher ranks than they would have otherwise.  When “bias” was eliminated, United moved up on the American system and vice versa, while all other airlines moved down somewhat.  The antitrust restriction on competitive use of the CRS, then, actually reduced competition.  Moreover, the rules ensured that the United/American market leadership would endure fewer challenges from creative newcomers, since any changes to the system would have to undergo DOT oversight, thus making “sneak attacks” impossible.  The resulting slowdown of CRS technology damaged the competitiveness of these systems.  Much of the innovative lead that these systems had enjoyed slowly eroded as the internet evolved.  Today, much of the air travel business has moved to the internet (as have the airlines themselves) (Smith, 1999).

These competitive losses occurred despite evidence suggesting that CRSs themselves enhanced competition and thus had the predictable positive impact for consumers.  For example, one study found that CRS usage increased travel agents’ productivity by an average of 41% and that in the early 1990s over 95% of travel agents used a CRS – indicating that travel agents were able to assist consumers far more effectively once CRSs became available (Ellig, 1991).  The rules governing contractual terms fared no better; indeed, these also likely reduced consumer welfare:

The prohibited contract practices–long-term contracting and exclusive dealing–that had been regarded as exclusionary might not have proved to be such a critical barrier to entry: entry did not occur, independently of those practices.  Evidence on the dealings between travel agents and CRS vendors, post-regulation, suggests that these practices may have enhanced overall allocative efficiency.  Travel agents appear to have agreed to some, if not all, restrictive contracts with CRS vendors as a means of providing those vendors with assurance that they would be repaid gradually, over time, for their up-front investments in the travel agent, such as investments in equipment or training (Alexander and Lee, 2004).

Accordingly, CRS regulations seem to have threatened innovation by decreasing the likelihood that CRS vendors would recover research and development expenditures without providing a commensurate consumer benefit.

Termination of Rules

The DOT terminated CRS regulations in 2004 in light of their failure to improve competitive outcomes in the CRS market and a growing sense that they were making things worse, not better – which Edelman fails to acknowledge and which certainly undermines his claim that regulators addressed this problem “successfully.”  From the time CRS regulations were first adopted in 1984 until 2004, the CRS market and the associated technology changed significantly, rapidly becoming more complex.  As the market increased in complexity, it became increasingly more difficult for the DOT to effectively regulate.  Two occurrences in particular precipitated de-regulation: (1) the major airlines divested themselves of CRS ownership (despite the absence of any CRS regulations requiring or encouraging divestiture!), and (2) the commercialization of the internet introduced novel forms of substitutes to the CRS system that the CRS regulations did not govern.  Online direct-to-traveler services, such as Travelocity, Expedia and Orbitz provide consumers with a method to choose their own flights, entirely absent travel agent assistance.  More importantly, Expedia and Orbitz each developed direct connection technologies that allow them to make reservations directly with an airline’s internal reservation system – bypassing CRS systems almost completely.  Moreover, Travelocity, Expedia, and Orbitz were never forced to comply with CRS regulations, which allowed them to adopt more consumer-friendly products and innovate in meaningful ways, obsoleting traditional CRSs.  It is unsurprising that Expedia has warned against overly broad regulations in the search engine bias debate – it has first-hand knowledge of how crucial the ability to innovate is.)

These developments, taken in harmony, mean that in order to cause any antitrust harm in the first instance, a hypothetical CRS monopolist must have been interacting with (1) airlines, (2) travel agents, and (3) consumers who all had an insufficient incentive to switch to another alternative in the face of a significant price increase.  Given this nearly insurmountable burden, and the failure of CRS regulations to improve consumer welfare in even the earlier and simpler state of the world, Alexander and Lee find that, by the time CRS regulations were terminated in 2004, they failed to pass a cost-benefit analysis.

Overall, CRS regulations incurred significant consumer welfare losses and rendered the entire CRS system nearly obsolete by stifling its ability to compete with dynamic and innovative online services.  As Ellig notes, “[t]he legal and economic debate over CRS. . . frequently overlooked the peculiar economics of innovation and entrepreneurship.”  Those who claim search engine bias exists (as distinct from valuable product differentiation between engines) and can be meaningfully regulated rely upon this same flawed analysis and expect the same flawed regulatory approach to “fix” whatever issues they perceive as ailing the search engine market.  Search engine regulation will make consumers worse off.  In the meantime, proponents of so-called search neutrality and heavy-handed regulation of organic search results battle over which of a menu of cumbersome and costly regulatory schemes should be adopted in the face of evidence that the approaches are more likely to harm consumers than help them, and even stronger evidence that there is no competitive problem with search in the first place.

Indeed, one benefit of thinking hard about remedies in the first instance is that it may illuminate something about the competitive nature of the conduct one seeks to regulate.  I defer to former AAG Barnett in explaining this point:

Put another way, a bad section 2 remedy risks hurting consumers and competition and thus is worse than no remedy at all. That is why it is important to consider remedies at the outset, before deciding whether a tiger needs catching. Doing so has a number of benefits.  …

Furthermore, contemplation of the remedy may reveal that there is no competitive harm in the first place.  Judge Posner has noted that “[t]he nature of the remedy sought in an antitrust case is often . . . an important clue to the soundness of the antitrust claim.”⁽⁴⁾ The classic non-section 2 example is Pueblo Bowl-O-Mat, where plaintiffs claimed that the antitrust laws prohibited a firm from buying and reinvigorating failing bowling alleys and prayed for an award of the “profits that would have been earned had the acquired centers closed.”⁽⁵⁾ The Supreme Court correctly noted that condemning conduct that increased competition “is inimical to the purposes of [the antitrust] laws”⁽⁶⁾–more competition is not a competitive harm to be remedied. In the section 2 context, one might wish that the Supreme Court had focused on the injunctive relief issued in Aspen Skiing–a compelled joint venture whose ability to enhance competition among ski resorts was not discussed⁽⁷⁾–in assessing whether discontinuing a similar joint venture harmed competition in the first place.⁽⁸⁾

A review of my paper with Geoff reveals several common themes among proposed remedies intimated by the above discussion of CRS regulations.  The proposed remedies consistently: (1) disadvantage Google, (2) advantage its rivals, and (3) have little if anything to do with consumers.  Neither economics nor antitrust history supports such a regulatory scheme; unfortunately, it is consumers that might again ultimately pay the inevitable tax for clumsy regulatory tinkering with product design and competition.

Filed under: antitrust, economics, federal trade commission, google, international center for law & economics, monopolization, technology Tagged: antitrust, Federal Trade Commission, google, search

Today at 12:30 at the Capitol Visitor Center, TechFreedom is hosting a discussion on the regulation of search engines:  “Search Engine Regulation: A Solution in Search of a Problem?”

The basics:

Allegations of “search bias” have led to increased scrutiny of Google, including active investigations in the European Union and Texas, a possible FTC investigation, and sharply-worded inquiries from members of Congress. But what does “search bias” really mean? Does it demand preemptive “search neutrality” regulation, requiring government oversight of how search results are ranked? Is antitrust intervention required to protect competition? Or can market forces deal with these concerns?

A panel of leading thinkers on Internet law will explore these questions at a luncheon hosted by TechFreedom, a new digital policy think tank. The event will take place at the Capitol Visitor Center room SVC-210/212 onTuesday, June 14 from 12:30 to 2:30pm, and include a complimentary lunch. CNET’s Declan McCullagh, a veteran tech policy journalist, will moderate a panel of four legal experts:

• Prof. Frank Pasquale, Seton Hall University School of Law, author of Federal Search Commission? Access, Fairness and Accountability in the Law of Search
• Prof. Geoffrey Manne, Lewis & Clark Law School, TechFreedom Adjunct Fellow, and Director of the International Center for Law & Economics, author of If Search Neutrality Is the Answer, What’s the Question?
• Prof. James Grimmelman, New York Law School, author of The Structure of Search Engine Law
• Prof. Eric Goldman, Santa Clara University School of Law, author of Search Engine Bias and the Demise of Search Engine Utopianism

More details are here, and the event will be streaming live from that link as well.  If all goes well, it will also be accessible right here:

http://www.ustream.tv/flash/viewer.swf

Live Broadcasting by Ustream

Filed under: administrative, announcements, essential facilities, google, law and economics, monopolization, regulation, technology Tagged: Declan McCullagh, Eric Goldman, frank pasquale, geoffrey manne, google, james grimmelmann, techfreedom, Web search engine

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

I am disappointed but not surprised to see that my former employer filed an official antitrust complaint against Google in the EU.  The blog post by Microsoft’s GC, Brad Smith, summarizing its complaint is here.

Most obviously, there is a tragic irony to the most antitrust-beleaguered company ever filing an antitrust complaint against its successful competitor.  Of course the specifics are not identical, but all of the atmospheric and general points that Microsoft itself made in response to the claims against it are applicable here.  It smacks of competitors competing not in the marketplace but in the regulators’ offices.  It promotes a kind of weird protectionism, directing the EU’s enforcement powers against a successful US company . . . at the behest of another US competitor.  Regulators will always be fighting last year’s battles to the great detriment of the industry.  Competition and potential competition abound, even where it may not be obvious (Linux for Microsoft; Facebook for Google, for example).  Etc.  Microsoft was once the world’s most powerful advocate for more sensible, restrained, error-cost-based competition policy.  That it now finds itself on the opposite side of this debate is unfortunate for all of us.

Brad’s blog post is eloquent (as he always is) and forceful.  And he acknowledges the irony.  And of course he may be right on the facts.  Unfortunately we’ll have to resort to a terribly-costly, irretrievably-flawed and error-prone process to find out–not that the process is likely to result in a very reliable answer anyway.  Where I think he is most off base is where he draws–and asks regulators to draw–conclusions about the competitive effects of the actions he describes.  It is certain that Google has another story and will dispute most or all of the facts.  But even without that information we can dispute the conclusions that Google’s actions, if true, are necessarily anticompetitive.  In fact, as Josh and I have detailed at length here and here, these sorts of actions–necessitated by the realities of complex, innovative and vulnerable markets and in many cases undertaken by the largest and the smallest competitors alike–are more likely pro-competitive.  More important, efforts to ferret out the anti-competitive among them will almost certainly harm welfare rather than help it–particularly when competitors are welcomed in to the regulators’ and politicians’ offices in the process.

As I said, disappointing.  It is not inherently inappropriate for Microsoft to resort to this simply because it has been the victim of such unfortunate “competition” in the past, nor is Microsoft obligated or expected to demonstrate intellectual or any other sort of consistency.  But knowing what it does about the irretrievable defects of the process and the inevitable costliness of its consequences, it is disingenuous or naive (the Nirvana fallacy) for it to claim that it is simply engaging in a reliable effort to smooth over a bumpy competitive landscape.  That may be the ideal of antitrust enforcement, but no one knows as well as Microsoft that the reality is far from that ideal.  To claim implicitly that, in this case, things will be different is, as I said, disingenuous.  And likely really costly in the end for all of us.

Filed under: antitrust, business, exclusionary conduct, law and economics, markets, monopolization, politics, regulation, technology Tagged: Brad Smith, Competition law, European Commission, google, microsoft, politics, regulation