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TOTM As the U.S. House Energy and Commerce Subcommittee on Oversight and Investigations convenes this morning for a hearing on overseeing federal funds for broadband deployment, it bears . . .
As the U.S. House Energy and Commerce Subcommittee on Oversight and Investigations convenes this morning for a hearing on overseeing federal funds for broadband deployment, it bears mention that one of the largest U.S. broadband-subsidy programs is actually likely run out of money within the next year. Writing in Forbes, Roslyn Layton observes of the Affordable Connectivity Program (ACP) that it has enrolled more than 14 million households, concluding that it “may be the most effective broadband benefit program to date with its direct to consumer model.”
Read the full piece here.
Regulatory Comments I. Introduction On behalf of the International Center for Law & Economics (ICLE), we thank the Federal Communications Commission (FCC or the Commission) for the . . .
On behalf of the International Center for Law & Economics (ICLE), we thank the Federal Communications Commission (FCC or the Commission) for the opportunity to comment on this Notice of Proposed Rulemaking in the Matter of Implementing the Infrastructure, Investment, and Jobs Act: Prevention and Elimination of Digital Discrimination (NPRM).[1]
The Commission is contemplating creating a definition of “digital discrimination of access” under Section 60506 as “(1) policies or practices, not justified by genuine issues of technical or economic feasibility, that differentially impact consumers’ access to broadband internet access service based on their income level, race, ethnicity, color, religion, or national origin” and/or (2) “policies or practices, not justified by genuine issues of technical or economic feasibility, that are intended to differentially impact consumers’ access to broadband internet access service based on their income level, race, ethnicity, color, religion, or national origin.”[2]
Finding ways to increase deployment to those Americans who have been persistently difficult to connect is a laudable goal, but there are better and worse ways to proceed. Section 60506 is about making sure that broadband is deployed fairly, given existing technological and economic constraints. It is not a radical prescription from Congress, but a request that the FCC ensure that impermissible discrimination doesn’t affect broadband deployment.
This requires accounting for the current state of deployment, the economic realities that constrain deployment decisions, and the existing legal framework that constrains the manner in which the Commission can interpret Section 60506.
As a baseline, it’s important to recognize that broadband providers have, by and large, done an excellent job of deploying to most households, while the data the FCC is currently gathering to assemble new broadband maps will enhance our ability to identify those problem areas that remain. Some of the comments in the record illustrate this baseline well. For example, NCTA observes in its comments that more than 98% of homes across income levels have access to fiber connections with speeds of at least one gigabit per second,[3] and that more than “97% of all homes and businesses in cable provider service areas have gigabit access regardless of race.”[4] As the FCC interprets Section 60506, the goal should be to work with this track record of success and not erect roadblocks that could prevent building on this base.
Moreover, broadband providers have been actively courting low-income consumers, particularly since Congress enacted successful programs such as the $14.2 billion Affordable Connectivity Program (ACP). By actively participating in these programs and offering tailored low-cost options, broadband providers are working to bridge the digital divide and reach unserved consumers. For example, Comcast’s “Internet Essentials” and “Internet Essentials Plus” programs offer affordable high-speed Internet service to eligible low-income households,[5] while AT&T’s “Access” program provides low-cost broadband plans to qualifying families.[6] Additionally, providers such as Charter Communications, through their “Spectrum Internet Assist” initiative, extend discounted Internet services to qualifying individuals and families.[7]
Section 60506 directs the FCC to prevent discrimination in broadband access based on income level. It also instructs the Commission to consider issues of technical and economic feasibility. A fundamental challenge presented by the intersection of these two directives is that a prospective broadband territory’s income level is related, albeit indirectly, to the economic feasibility of deployment projects to serve that territory. Economic feasibility is driven largely by population density and anticipated broadband adoption and retention. Broadband adoption and retention are, in turn, driven by income, willingness-to-pay, and many other factors. This present an “income conundrum,” in that it is nearly impossible to completely disentangle a given customer base’s anticipated rates of broadband adoption and retention from their income level.
It is well known and widely accepted that income is correlated with many factors that are not identified in Section 60506, including population density, age, educational attainment, home-ownership status, home-computer ownership and usage, and rates of broadband adoption and un-adoption. Because each of these additional factors is correlated with income level, many effects-based statistical tests of broadband adoption are likely to produce false positives, concluding the presence of digital discrimination even where explicit efforts are made to avoid such discrimination.
This problem is exacerbated if providers are not allowed to point to the relative profitability of prospective deployment investments. Like all firms, broadband providers have limited resources to invest. While profitability is a necessary precondition for investment, not all profitable investments can be undertaken. At any given time, firms must choose from numerous potentially profitable projects, some more apparently profitable than others. Firms must be allowed to choose the mix of profitable investments that they believe will best advance long-term deployment without fear of having to defend claims of income discrimination.
While the NPRM[8] and several commenters[9] suggest the statute can be read to give the FCC broad authority to redress the disparate impact of deployment decisions based on income and race (among other impermissible deployment factors), principles of statutory interpretation preclude that reading. Supreme Court precedent on antidiscrimination statutes makes clear how Congress can write disparate-impact law.[10] It also makes clear that many provisions of antidiscrimination statutes apply only to intentional discrimination.[11] The difference turns on the language of the operative text and the statutory purpose, as illustrated by things like the overall structure of the legislation and the stated policy objective (including legislative intent, if it can be known).[12] Applying this rubric to Section 60506, we find that it lacks requisite “results-oriented language” that would make it into an effects-oriented statute. Thus, the prohibition against digital discrimination “based on income level, race, ethnicity, color, religion, or national origin” would apply only in cases of intentional discrimination in deployment decisions. Mere statistical correlation between deployment and protected characteristics is insufficient to support a finding of discrimination.
As to the overall structure of the Act, while the Infrastructure, Investment, and Jobs Act (IIJA) incorporates some of its provisions into the Communications Act, Section 60506 is not among them. The IIJA is concerned chiefly with promoting broadband buildout through the use of subsidies. As to the policy objective, the scant congressional record on Section 60506 fails to illuminate the text, leaving us to consider the plain meaning of the statute. The “statement of policy” in subsection (a) holds that subscribers “should” benefit from equal access to broadband and that the Commission “should” take steps to ensure such equal access.[13] This “precatory”[14] section tells us the goal of the operative text: to make sure the Commission takes steps to promote broadband buildout. The mandate to create rules that facilitate equal access to broadband service—including by “preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin”—grants the Commission authority to set up a regulatory structure that would prevent intentional discrimination in deployment decisions, using language akin to those antidiscrimination provisions that speak only to intent.[15] This limited authority doesn’t allow for disparate-impact analysis, nor does it create a private right of action to enforce against any broadband provider. Instead, it empowers the Commission (and the Office of the Attorney General) to ensure federal policies promote equal access by prohibiting such deployment discrimination.[16]
Broadband buildout is big business, in the sense that a lot of money is invested by providers and governments (in the form of subsidies) alike. How these providers are regulated is a “major question” of “vast economic [and] political significance.”[17] To allow the Commission to exercise broad authority to ameliorate disparate impact, as suggested by some commenters, would be to find the proverbial “elephants in mouseholes”[18] in this statute, which the U.S. Supreme Court has not permitted.
In Part II, we review specific questions in the NPRM, the economics underlying deployment decisions, and how these relate to potential digital discrimination.
In Part III, we review some of the legal implications of attempting to regulate “digital discrimination” under both an intent-based and effects-based approach.
In Part IV, we consider the need for safe harbors and other procedural protections.
In Part V, we conclude and offer some thoughts on how to give best effect to Section 60506.
Section 60506 directs the FCC to prevent discrimination in broadband access based on income level, race, ethnicity, color, religion, or national origin, while also directing the Commission to consider issues of technical and economic feasibility.
We assert that the FCC should adopt an intent-based discriminatory-treatment standard, rather than one that opens the doors to disparate-impact claims. The high risk of false positives under a disparate-impact standard would stifle broadband deployment through additional costs, delays, and risk of litigation. Similarly, FCC rules should articulate a presumption of nondiscrimination in which allegations of digital discrimination must be demonstrated, rather than a presumption of discrimination that must be rebutted for each deployment decision.
It is clear that population density and anticipated broadband adoption are the key factors affecting the economic feasibility of broadband-deployment investments. Affordability and willingness to pay are the primary drivers of broadband adoption where it is available. Indeed, Congress has recognized this reality in its recent legislation. The IIJA’s Broadband Equity and Access program provides more than $42 billion in grants to state programs to help them support providers and give assistance directly to users.[19] The Affordable Connectivity Program provided another $14 billion in funding to help users pay for devices and broadband connections.[20]
If the Commission has good evidence of intentional discrimination in the deployment of broadband, it has a role to play in preventing it. But attempts to use the regulatory process to root out digital discrimination will do little to shrink the digital divide without substantial resources to increase adoption and retention of broadband services.
The NPRM asks “how does a consumer’s income level, or the average income level of a geographical area, relate to economic feasibility in the deployment and provision of broadband internet access services?”[21]
The short answer is that income level is only indirectly related to economic feasibility. When evaluating the economic feasibility of a potential investment, broadband providers consider that territory’s anticipated adoption rate.[22] There is evidence that income, willingness to pay, and many other factors affect consumers’ adoption and retention decisions. Thus, it can be said that income level is related to deployment decisions only through a daisy chain linking anticipated adoption and retention rates to consumers’ willingness to pay, with willingness to pay loosely correlated with income level.
Population density is widely acknowledged to be the most important factor driving broadband-deployment decisions. For example, the U.S. Government Accountability Office (GAO) reports that population density is the “most frequently cited cost factor” and “a critical determinant of companies’ deployment decisions.”[23] Academic research supports the GAO’s conclusions. Brian Whitacre & Roberto Gallardo describe population density as one of “the main determinants of Internet availability.”[24] Similarly, Tonny Oyana, citing earlier research, concluded that “[l]imited broadband access is common in rural communities because of geographic remoteness and low population density.”[25]
Several other factors also affect the profitability of broadband-deployment investments, including:
Juan Schneir & Yupeng Xiong note that firms are more likely to deploy broadband in urban and suburban areas, rather than rural areas, due to both cost and demand factors. They conclude this is “because of the high density of users willing to pay for high-speed broadband services and the relatively low network rollout costs in urban and suburban areas.”[29] Consistent with Schneir & Xiong’s conclusion, the GAO also finds that population density is an important factor on the demand side of deployment decisions. In particular, the GAO concludes that it is more difficult to “aggregate sufficient demand” to pay for broadband service in low-density rural areas.[30]
But broadband access alone also may not be sufficient to drive greater rates of broadband adoption. For example, Brian Whitacre and his co-authors found that while the reduced levels of broadband access in rural areas explained 38% of the rural-urban broadband-adoption gap in 2011, differences in other general characteristics—such as income and education—explain “roughly half of the gap.”[31] Another GAO report concluded that “even where broadband service is available … an adoption gap may persist due to the affordability of broadband and lack of digital skills.”[32] The report further notes that nearly one-third of those with access to broadband do not subscribe to it and that “lower-income households have lower rates of home broadband subscriptions.”[33]
The price of broadband services is another significant factor that affects adoption. A National Telecommunications and Information Administration (NTIA) survey of Internet use identified “affordability as a driving factor around why some households continue to remain offline, confirming that cost of service is an essential part of increasing Internet adoption.”[34] The survey reported that the average price that offline households wanted to pay for Internet access was approximately $10 per month, and about 75% of households gave $0 or “none” as their answer. Kenneth Flamm & Anindya Chaudhuri’s empirical research finds that broadband price is a “statistically significant driver” of broadband demand.[35] They conclude that broadband-price declines in the early 2000s explain “some portion” of increased broadband adoption.[36] Victor Glass & Stela Stefanova’s empirical study found that higher prices “depress” demand for broadband.[37]
Price sensitivity is linked to income. Christopher Reddick and his co-authors concluded that “[i]ncome is a major factor that is likely to influence broadband adoption especially where technology is available.”[38] Glass & Stefanova find broadband service to be a normal good, which means that increased incomes are associated with increased broadband adoption—a finding consistent with previous research.[39] Similarly, the GAO reports: “A recent nationally representative survey by Consumer Reports reported that nearly a third of respondents who lack a broadband subscription said it was because it costs too much, while about a quarter of respondents who do have broadband said they find it difficult to afford.”[40] Alison Powell and her co-authors report that a significant number of low-income Americans engage in a cycle of broadband adoption and “un-adoption,” in which they adopt broadband and then drop it for financial or other reasons, and then re-adopt when circumstances improve for them.[41]
In addition to price and income guiding a household’s broadband-adoption decisions, other factors are also relevant. Oyana’s empirical research concludes that income, the share of a population who are senior citizens, and the share with some college education are the “three most important demand-side factors” affecting both access and adoption.[42] On the demand side, the GAO reports that “demand will be greater in areas where potential customers are familiar with computers and broadband.”[43] The GAO reports that “[o]ther barriers include lack of digital skills,” citing a 2016 Pew Research Center report finding that “about half of American adults were hesitant when it comes to new technologies and building their digital skills.”[44]
It can be argued that the gap between rates of broadband access and broadband adoption may present the real digital divide. That is, large numbers of American who have access to broadband do not adopt it, and some who do may “un-adopt” it. While income is a key factor in a household’s adoption choice, it is only one of several important factors, which also include age, educational attainment, and home-computer ownership and usage—each of which is, in turn, also correlated with income.
If firms do not expect sufficient levels of adoption, then deployment may be unprofitable. It would be a mistake to infer that income discrimination in deployment causes low rates of broadband adoption in low-income communities when low income itself—and other factors correlated with income—may be a primary cause of low rates of broadband adoption, even where broadband access is available.
The NPRM asks, “should a provider be permitted to defend a claim of income-based intentional discrimination by offering projections showing that deploying to a particular community would likely produce a lower-than-normal rate of return on investment?”[45]
Section 60506 requires the Commission to take account of “issues of technical and economic feasibility.” There is broad understanding that “economic feasibility” here refers to profitability.[46] More precisely, a project is economically feasible if it provides an adequate return on investment (ROI). Like all firms, broadband providers have limited resources with which to make their investments. While profitability is a necessary precondition for investment, not all profitable investments can be undertaken. Among the universe of potentially profitable projects, firms are likely to give priority to those that promise greater returns on investment relative to those with lower ROI.[47] Thus, any evaluation of potential digital discrimination must examine not only whether a given deployment is likely to be profitable, but also how its expected returns compare to other investment opportunities.
This concept—opportunity cost—is fundamental not just to economics, but to our daily lives. Indeed, we all live in a world of endless wants, but only limited resources (e.g., money, time, natural resources) to satisfy them. As a result, we must make choices about how best to use those resources to satisfy our wants. By choosing to pursue one activity, we must forgo another. The value of what we have foregone is our opportunity cost.[48] A worker contemplating quitting their job to start a business is certain to consider the income they would be giving up as an opportunity cost of entrepreneurship.
Similarly, a broadband provider who invests in region A recognizes that it is giving up the opportunity to invest in region B. But the provider faces another factor the would-be entrepreneur does not. If the provider regularly chooses low-ROI investments over higher ROI investments, then its shareholders may choose to replace management with a team that can provide better returns. The opportunity-cost calculus is unavoidable.
Thus, it is surprising to see comments to this proceeding that suggest the FCC should ignore opportunity cost in evaluating economic feasibility.[49] Section 60506 specifically calls on the FCC to consider economic feasibility—not financial feasibility or accounting feasibility. There is no evidence that this was an accident or mistake. Because opportunity cost is a cornerstone of economic analysis, it would be reasonable to conclude that the law’s mandate to consider economic feasibility was meant to rely on economic analysis and, in turn, to consider the opportunity costs of foregone deployment investments. We strongly encourage the Commission to include opportunity costs that providers face whenever it evaluates alleged digital discrimination in deployment.
The NPRM asks, “[S]hould a provider be permitted to defend a claim of income-based intentional discrimination by offering projections showing that deploying to a particular community would likely produce a lower-than-normal rate of return on investment? How are we to determine whether a proffered economic justification, such as rate of return, is a pretext for income-based discrimination?”[50] The NPRM reports that some have argued a sub-normal profit margin should not be considered sufficient reason to claim economic infeasibility and that the Commission should rarely excuse discrimination on such grounds.[51]
A provider should be permitted to defend a claim of income-based intentional discrimination by demonstrating that deploying to a particular community would likely produce a lower return on investment relative to other likely alternatives investments. Thus, a provider should be able to defend a claim of income-based intentional discrimination even if deploying to a particular community would likely produce a higher than “normal” ROI—so long as other deployment alternatives produce anticipated ROIs that are greater still. As noted above, a positive ROI is a necessary precondition for investment, but not all profitable investments can be undertaken. Evaluations of potential digital discrimination must examine not only whether a given deployment is likely to be profitable, but also how its expected returns compare to other investment opportunities.
It would be near-impossible to evaluate demographic, economic, and financial data to determine whether profitability, ROI, or other economic reasons constitute a pretext for a pattern of so-called income-based discrimination. Our research indicates that such an approach would likely lead to a huge number of “false positives”—finding discrimination where no discrimination is intended or, indeed, where it was explicitly avoided. This presents what we call the “income conundrum,” because it is virtually impossible to disentangle the factors affecting economic feasibility from factors correlated with membership in certain income and other protected classes.[52]As such, alleged patterns of income-based discrimination provide very little (if any) information, and certainly not enough information to sufficiently prove a violation of Section 60506.
Former FCC Chief Economist Glenn Woroch combined recent census-block-level wireline-broadband deployment data from the Commission’s Form 477 reports with demographic and income data published by the U.S. Census Bureau to evaluate broadband availability rates for wireline 100/20 Mbps service (1) between census-based “white” and “non-white” households and (2) between households above and below the Federal Poverty Guidelines.[53] His statistical analysis indicates broadband availability rates are about 5 percentage points higher for non-white households than for white households, and that broadband availability rates are nearly identical for households above and below the Federal Poverty Guidelines.
Woroch’s results are consistent with the statistical analysis published by Randolph Beard & George Ford.[54] Their data indicate that U.S. Census blocks with higher population densities are associated with a higher share of minority residents and lower average incomes. Beard & Ford also report that blocks with a higher share of minority residents have lower fixed-broadband adoption rates and a higher share of mobile-only broadband use. Their empirical model includes four demand factors for each Census block: fixed-broadband adoption rate, mobile-broadband adoption rate, the share of persons with a tertiary education, and the share of homes with a computer. The model also includes five cost factors: population density, the share of rural blocks within the Census-block group, and three cost categories from CostQuest. Using this information, they evaluate: (1) fiber deployment by race, (2) fiber deployment by income level, (3) download speeds by race, and (4) download speeds by income level. Beard & Ford conclude from their statistical analysis that there is “no meaningful evidence of digital discrimination in either race or income for fiber deployments or for download speeds.”
It is well-known and widely accepted that income is correlated with many factors that are not identified in Section 60506, including population density, age, educational attainment, home-ownership status, home-computer ownership and usage, and broadband adoption and un-adoption. But because each of these other factors is, in turn, correlated with income level, applying an effects-based statistical analysis is likely to produce false positives that conclude the presence of digital discrimination, even if there was an explicit effort to avoid such discrimination. This is a version of Nobel laureate Ronald Coase’s well-known quote: “If you torture the data long enough, it will confess.”[55]
Indeed, as the Competitive Enterprise Institute (CEI) notes, even if the Commission were to adopt a disparate-impact standard (discussed infra), it would be exceedingly difficult, if not impossible, to prove income discrimination through a series of correlated proxies under existing Supreme Court precedent:
Thus, as Hazen demonstrates that as long as the motivating factor for digital discrimination of access is analytically distinct from the protected characteristic (even if one is correlated with the other, like age when set against years of service), the person who is wholly motivated by other factors wouldn’t be discriminating based on protected characteristics. [56]
Thus, even if correlational evidence is introduced, it will be of such little probative value as to contribute very little information to a proceeding. For example, even if statistical analysis indicated a relationship between income and some other non-protected characteristic (e.g., education), under 1993’s Hazen Paper Co. v. Biggins decision, that information could not be used to demonstrate income discrimination. The only way that a prohibition on income-based discrimination would make sense at all would be if Section 60506 were construed as prohibiting intentional discrimination. In this sense, claims would have to be brought on the basis that a provider intentionally discriminated against a low-income household, or against a territory for being low-income, with all else being equal. That is, if a particular opportunity would otherwise have been included in a provider’s deployment plans, discrimination could be found if that provider refrained from deploying based on an intent not to serve low-income households in the area.
Congress did not, with Section 60506, turn the FCC into a general-purpose civil-rights agency. It did, however, give the Commission a set of tools to identify and remedy particular acts of discrimination.
In the NPRM, the Commission proposes:
to define “digital discrimination of access,” for purposes of this proceeding, as one or a combination of the following: (1) “policies or practices, not justified by genuine issues of technical or economic feasibility, that differentially impact consumers’ access to broadband internet access service based on their income level, race, ethnicity, color, religion, or national origin”; and/or (2) “policies or practices, not justified by genuine issues of technical or economic feasibility, that are intended to differentially impact consumers’ access to broadband internet access service based on their income level, race, ethnicity, color, religion, or national origin.”[57]
Although some commenters have called for the FCC to employ an effects-based “disparate impact” analysis under Section 60506,[58] we continue to believe this would be a mistake under both the structure of Section 60506 and the Supreme Court’s established jurisprudence on disparate-impact analysis. A more reasonable approach for the Commission would be to construe Section 60506 as directing an analysis of intentional discrimination in deployment.
Statutes that define impermissible discrimination, such as the Civil Rights Act of 1964, can be analyzed legally either as addressed toward explicit discriminatory intent, referred to as “discriminatory treatment,” or toward behavior inferred from discriminatory effects, such as the “disparate impact” that the challenged behavior or policy has on a protected class.[59] A case involving discriminatory treatment is somewhat more straightforward,[60] insofar as it demands evidence demonstrating that decisions adversely affecting some protected class were made based on bias toward members of that class. In this context, where deployment decisions are made on the basis of discriminatory intent, the Commission is on much firmer legal ground to pursue them.
By contrast, were the Commission to adopt a “disparate impact” assessment as part of Section 60506, it would face a steep uphill legal climb. Among the primary justifications for disparate-impact analysis is to remedy those historical patterns of de jure segregation that left an indelible mark on minority communities.[61] While racial discrimination has not been purged from society, broadband only became prominent in the United States well after all forms of de jure segregation were made illegal, and after Congress and the courts had invested decades in rooting out impermissible de facto discrimination. Any policy intended to tackle disparate impact in broadband deployment needs to take this history into account.
Commenters like Public Knowledge point to Section 60506’s stated policy objective to make the case that the statute encompasses disparate-impact analysis.[62] They also situate the IIJA as a part of the universal service regime of the Communications Act.[63] However, Section 60506 was not incorporated into the Communications Act, unlike other parts of the IIJA. In other words, the FCC’s general enforcement authority doesn’t apply to the regulatory scheme of Section 60506. The FCC must rely on the statute alone for that authority. Moreover, the statement of policy in Section 60506(a) is exactly that: a statement of policy. Courts have long held that sections using words like “should”[64] are “precatory.”[65] While this helps to illuminate the goal of the provision at issue, it does not actually expand the remit of FCC authority. The goal of the statute is clear: to make sure the Commission takes steps to promote broadband buildout. It empowers the Commission (and the Office of the U.S. Attorney General) to ensure that federal policies promote equal access by prohibiting such deployment discrimination.[66]
There is little evidence that IIJA’s drafters intended the law to be read so broadly. The legislative record on Section 60506 is exceedingly sparse, containing almost no discussion of the provision beyond assurances that “broadband ought to be available to all Americans,”[67] and also that the provision was not to be used as a basis for the “regulation of internet rates.”[68] Given that sparse textual basis, reading Section 60506 as granting the Commission expansive powers to serve as a broadband civil-rights czar could also run afoul of the “major questions” doctrine.[69] That doctrine requires Congress “to speak clearly if it wishes to assign to an agency decisions of vast ‘economic and political significance.’”[70] To allow the Commission to exercise the type of broad authority to ameliorate disparate impact, as suggested by some commenters, would be to find the proverbial “elephants in mouseholes”[71] in this statute that the Supreme Court has not allowed.
More specifically, it does not appear that Section 60506 can be reasonably construed as authorizing disparate-impact analysis. While the Supreme Court continues to uphold disparate-impact analysis in the context of civil-rights law, it has recently imposed some important limitations. For example, in Texas Department of Housing & Community Affairs v. The Inclusive Communities Project Inc., the Court upheld the disparate-impact doctrine, but noted that disparate-impact claims arise under statutes explicitly directed “to the consequences of an action rather than the actor’s intent.”[72] For example, in the Fair Housing Act, Congress made it unlawful:
To refuse to sell or rent after the making of a bona fide offer, or to refuse to negotiate for the sale or rental of, or otherwise make unavailable or deny, a dwelling to any person because of race, color, religion, sex, familial status, or national origin.[73] [Emphasis added.]
The Court noted that the presence of language like “otherwise make unavailable” is critical to construing a statute as demanding an effects-based analysis.[74] Such phrases, the Court found, “refer[] to the consequences of an action rather than the actor’s intent.”[75] Further, the structure of a statute’s language matters:
The relevant statutory phrases… play an identical role in the structure common to all three statutes: Located at the end of lengthy sentences that begin with prohibitions on disparate treatment, they serve as catchall phrases looking to consequences, not intent. And all [of these] statutes use the word “otherwise” to introduce the results-oriented phrase. “Otherwise” means “in a different way or manner,” thus signaling a shift in emphasis from an actor’s intent to the consequences of his actions.[76]
Previous Court opinions help to parse the distinction between statutes limited to intentional-discrimination claims and those that allow for disparate-impact claims. Particularly relevant here, in Alexander v. Sandoval, the Court emphasized that it was “beyond dispute—and no party disagrees—that § 601 prohibits only intentional discrimination.”[77] The relevant statutory language stated that “No person in the United States shall, on the ground of race, color, or national origin, be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any program or activity receiving Federal financial assistance.”[78]
Thus, when Public Knowledge argues that “assertion that the phrase ‘based on’ limits the Commission to disparate intent is based on the dissent not the majority opinion of Inclusive Communities. The majority’s opinion states the exact opposite… The phrase at issue in Inclusive Communities was ‘because of,’ which is equivalent to ‘based on’ contained in section 1754…”[79], it gets both Inclusive Communities and previous precedents wrong. First, Inclusive Communities primarily based its opinion on the “otherwise make unavailable” language and not on the “because of” language on its own. Second, the closest analogy for “based on” is the “grounded on” language of Title VI, which does not include the “otherwise” language found to be so important in Inclusive Communities. If the Court has found “grounded on” means only intentional discrimination, then it is hard to see how “based on” wouldn’t lead to the same conclusion.
Further, even where disparate-impact analysis is appropriate, the Court held in Inclusive Communities that it is significantly constrained by the need to ensure that the free-enterprise system continues to function:
[Supreme Court precedent] also teach[es] that disparate-impact liability must be limited so… regulated entities are able to make the practical business choices and profit-related decisions that sustain a vibrant and dynamic free-enterprise system. And before rejecting a business justification…a court must determine that a plaintiff has shown that there is “an available alternative … practice that has less disparate impact and serves the [entity’s] legitimate needs.”[80] [Emphasis added.]
In practice, this means that lower courts are free to probe a disparate-impact claim rigorously in order to avoid such claims becoming a club to wield against regulated entities.[81] It also suggests that, in a context such as Section 60506’s proscriptions against digital discrimination, they may not be so broad as to render it impossible for broadband providers to make effective decisions about which deployment projects are economically feasible.
More to the point, as Section 60506 was drafted without “results-oriented language”[82] and instead frames the prohibition against digital discrimination as “based on income level, race, ethnicity, color, religion, or national origin,”[83] this would put the rule squarely within the realm of prohibitions on intentional discrimination.[84] That is, to be discriminatory, the decision to deploy or not to deploy must have been intentionally made based on or grounded on the protected characteristic. Mere statistical correlation between deployment and protected characteristics is insufficient.
In enacting the IIJA, Congress was undoubtedly aware of the Court’s history with disparate-impact analysis. Had it chosen to do so, it could have made the requirements of Section 60506 align with the requirements of that precedent. But it chose not to do so, thereby reinforcing that it intended the FCC to have some discretion, but to err on the side of caution when declaring certain practices an impermissible form of discrimination.
This is not to say that Section 60506 has no effect. As mentioned above, it can be reasonably read to encompass intentional discrimination, given appropriate evidence. Further, the means available to the FCC to remedy undesirable patterns of deployment are manifold. The only options rendered off the table would be requirements that are technologically or economically infeasible, such as an unfunded mandate that providers deploy at maximum speeds to all households simultaneously.
Moreover, as NCTA noted in its comments, the “intentional discrimination” standard provides ample room for the Commission to act upon instances of impermissible discrimination:
[I]t is NCTA’s position that discriminatory intent need not be proven with a “smoking gun,” such as documentary evidence overtly acknowledging or demonstrating discrimination, but can instead be sufficiently pled and shown with evidence including a combination of impact elements and facts such as: statistics demonstrating a pattern of discriminatory intent, the sequence of events leading to the decision, departures from normal procedures, and a consistent pattern of actions imposing much greater harm on the protected class that is unexplainable on grounds other than discriminatory ones.[85]
Indeed, in Vill. of Arlington Heights v. Metro. Hous. Dev. Corp.,[86] the Supreme Court established a legal test for determining intentional discrimination. The test requires a plaintiff to demonstrate that a discriminatory intent was a motivating factor behind the challenged action or decision.[87] To prove intentional discrimination, the Court identified several factors that can serve as evidence. Under this test, “[d]etermining whether invidious discriminatory purpose was a motivating factor demands a sensitive inquiry into such circumstantial and direct evidence of intent as may be available.”[88] Such an analysis can include circumstantial evidence of:
As the DOJ observes, while statistical evidence of patterns of discrimination cannot themselves be used as proof of discriminatory intent, they can be used as supporting evidence in such claims.[94] Critically, as noted in the section above, when dealing with claims of income-based discrimination, this means that challenges to deployment decisions must be made on the basis of bias regarding consumers at a particular income level, and cannot be divined through statistical inferences in the myriad factors that are merely correlated with income (such as education, computer ownership, adoption levels, and willingness to pay).
In sum, Section 60506 is an intentional-discrimination statute and the Commission’s rules should reflect that fact. To create a disparate impact regime would be to invite a drawn-out legal battle that would likely result in the rules being struck down.
The Commission asks whether it should adopt safe harbors, rely on case-by-case inquiry into “technical or economic” feasibility issues, or both.[95] We believe that the FCC needs to establish clear and robust safe harbors and affirmative defenses to discrimination complaints. Without such safe harbors, the administration of Section 60506 would become unwieldy, as the Commission wades through what is likely to be many false positives. There are a few situations that provide prima facie evidence that a broadband provider is not impermissibly discriminating against low-income consumers, or consumers in an otherwise protected class.[96]
For instance, in areas where a provider deploys service that is adhering to obligations under federal or state subsidy programs, a provider is obviously trying to reach underserved communities. Any shortcomings in deployment in such an area are almost certainly going to be the result of technical or economic realities. Similarly, where a provider is constrained by federal or state laws regarding permitting or access to rights of way, it would be fruitless to investigate; only once a provider is actually able to deploy legally should it be subject to scrutiny under Section 60506.
Similarly, there are constrains implicit in particular technologies that would make it difficult to accurately assess discrimination in some cases.[97] For example, when examining deployment of wireless providers, spectrum availability is a major issue that can constrain a provider’s ability to deploy in certain areas. Relatedly, the nature of a particular geographic area may limit how signals propagate. Even if a wireless provider fully deploys in such areas, building density or, inversely, sparsely populated areas might appear to be underperforming. In such cases, the Commission should adopt a technological safe harbor that assumes best efforts in certain cases imply good-faith compliance with Section 60506.
Thus, not only do all providers need some form of safe harbor, given the limitations of technology, but the Commission should also employ tailored safe harbors that incorporate the unique features of both wireless and wired providers.
Moreover, safe harbors do more than merely safeguard against an unfair or inefficient process, but may become a virtual necessity if the Commission attempts to rely on a “disparate impact” standard. As USTelecom noted in its comments, related civil-rights laws invariably include safe harbors in the context of fact-dependent, complicated proceedings.[98] These well-established legal proceedings create a formal burden-shifting framework that attempts to capture the economic and business realities underlying challenged practices.[99]
The Commission has also asked whether it would be appropriate to rely on its informal consumer-complaint process as part of its enforcement of Section 60506.[100] An informal complaint process that invites input from individuals directly affected by deployment decisions can make sense in some cases, while in others, a more formal complaint process will be necessary. Even if the Commission can appropriately delineate these cases, certain procedural protections should be in place to ensure the process is not abused.
First, there should be some form of standing requirement, such that a complainant actually is in a position to obtain broadband service, but is unable to do so (or do so at “comparable speeds, capacities, latency, and other quality of service metrics in a given area, for comparable terms and conditions”[101]). Given how large the national deployment footprint is, without an injury-in-fact requirement, opening the process to third parties who lack direct interest would be unmanageable. It would burden both the Commission and providers, who we otherwise want to spend their scarce resources on further deployment. Moreover, private parties with adequate standing who believe they have valid complaints can file through an informal process that could theoretically be handled much more quickly and efficiently.
The Commission also asks whether it should adopt a private right of action or permit state and local government enforcement against broadband providers.[102] Both options are likely to prove unworkable for a number of reasons. First, states and localities are often in a position of both granting access to necessary facilities as well as granting permission for providers to deploy. A right of action for states and localities—or even a process by which states and localities can source complaints in their jurisdiction and try those complaints—would create an imbalance in the bargaining process between providers and state authorities. Those authorities could use the complaint process as a leverage tool to extract inappropriate concessions from providers as they negotiate franchising agreements and other permissions necessary for deployment in particular jurisdictions.[103] Giving them a dual role in this respect—as both a complainant that can use legal process to intervene in providers’ deployment decisions as well as a party seeking to conduct an arm’s length negotiation with providers—threatens to seriously distort deployment incentives.
Moreover, providers are responsible for managing deployment decisions in a way that inherently crosses jurisdictional barriers, particularly for large providers that cross state lines. A given locality could be in a position to complain about a provider’s deployment decision, even if that decision makes technical and economic sense across jurisdictional boundaries. A state or locality is not well-positioned to adjudicate this problem, while the FCC is extremely well-positioned to do so.
Ostensibly in the interests of completeness, the NPRM asks whether it has authority to retroactively pursue claims for digital discrimination.[104] We believe it should go without saying that this procedure should be forward looking. Nothing in Section 60506 suggests that Congress intended to give the FCC authority to pursue providers for previous deployment decisions.
It is evident that, while the Commission possesses considerable authority to remedy intentional discrimination under Section 60506, its discretion is not without boundaries. Moreover, it should create safeguards to ensure that the complaint process does not excessively burden Commission staff or erect administrative barriers to providers’ efforts to deploy broadband.
Although “income level” is included as a protected category under Section 60506, income can be correlated with such a wide array of variables, which themselves better explain deployment and adoption, that the Commission needs to take care. Trying to construe discrimination on the basis of “income” too broadly will surely generate a large number of false positives, and will lead the Commission astray.
Moreover, Section 60506 employs language directly related to case law centered on “intentional discrimination” and further includes crucial provisions directing the Commission to consider technical and economic feasibility. This legislative framework exists against the backdrop of the Supreme Court’s expanding “major questions” doctrine. With the law and the economics taken together, it is clear that the Commission should not adopt a “disparate impact” test under Section 60506. Moreover, it is crucial to remember that “income” remains a slippery metric to judge, and attempts to use correlational proxies in a discrimination analysis are fraught. As such, claims based on income discrimination should be rooted in bias regarding particular income levels, all else equal. It is critical that Section 60506 not be used as a cudgel against providers as they attempt to balance the opportunity costs of competing deployment opportunities.
The FCC rules should also articulate a presumption of nondiscrimination in which allegations of digital discrimination must be demonstrated, rather than a presumption of discrimination that must be rebutted for each deployment decision. This presumption should furthermore be coupled with adequate safe harbors that allow that Commission to consider defenses based on “technical and economic” feasibility in an expedited manner. Otherwise, given the economic realities discussed above, there is an unacceptably high chance that every one of a provider’s decisions will be subject to challenge, wasting the resources of both the Commission and the providers.
The largest takeaway is that adoption matters quite a bit. Indeed, one of the biggest issues affecting economic feasibility is consumers’ ability and willingness to pay. Moreover, Congress has recognized this reality in its recent legislation. The IIJA’s Broadband Equity and Access program provides more than $42 billion in grants to state programs to help them support providers and give assistance directly to users.[105] The Affordable Connectivity Program provided another $14 billion in funding to help users pay for devices and broadband connections.[106] In our estimation, the Commission stands to do the most good by championing and shepherding programs like these.
If the Commission has good evidence of intentional discrimination in the deployment of broadband, it has a role to play in preventing it. But without strong, compelling evidence of intentional discrimination, the FCC will waste scarce resources chasing bogeymen.
[1] Notice of Proposed Rulemaking, Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (Dec. 22, 2022) [hereinafter “NPRM”].
[2] Id. at ¶ 12.
[3] Comments of NCTA, GN Docket No. 22-69 (Feb. 21, 2023), at 4 [hereinafter “NCTA”].
[4] Id. at 6.
[5] Apply for Internet Essentials or Internet Essentials Plus From Comcast, Comcast, https://www.xfinity.com/support/articles/comcast-broadband-opportunity-program (last visited Apr. 19, 2023).
[6] Affordable Connectivity Program, AT&T, https://www.att.com/help/affordable-connectivity-program (last visited Apr. 19, 2023).
[7] Spectrum Internet for Low Income Households, Spectrum, https://www.spectrum.com/internet/spectrum-internet-assist (last visited Apr. 19, 2023).
[8] NPRM, supra note 1 at ¶ 12
[9] See, e.g., Comments of Public Knowledge, Benton Institute for Broadband and Society, and Electronic Privacy Information Center, GN Docket No. 22-69 (Feb. 21, 2023), at 52 (“Congress has again centered the focus of the Commission’s actions on getting all people access, regardless of any discriminatory treatment or intent of the provider.”) [hereinafter “Public Knowledge”]; Letter from David Brody, Lawyers’ Committee for Civil Rights Under Law, to Marlene H. Dortch, Implementing the Infrastructure and Jobs Act: Prevention and Elimination of Digital Discrimination, WC Docket No. 22-69 (Dec. 12, 2022) [hereinafter “Brody”].
[10] See, e.g., Tex. Dep’t of Hous. & Cmty. Affs. v. Inclusive Cmtys. Project Inc., 576 U.S. 519 (2015) [hereinafter “Inclusive Communities”].
[11] See, e.g., Alexander v. Sandoval, 532 U. S. 275, 280 (2001) (“[I]t is… beyond dispute—and no party disagrees—that § 601 prohibits only intentional discrimination.”).
[12] See, e.g., Inclusive Communities, supra note 10 at 533- 34 (“[A]ntidiscrimination laws must be construed to encompass disparate-impact claims when their text refers to the consequences of actions and not just to the mindset of actors, and where that interpretation is consistent with statutory purpose.”); Board of Ed. of City School Dist. of New York v. Harris, 444 U. S. 130 –141 (1979) (considering the context of a statute’s text, history, purpose, and structure in determining whether a statute encompasses disparate impact analysis).
[13] See Section 60506(a)(1), (a)(3).
[14] See, Emergency Coal. to Def. Educ. Travel v. U.S. Dep’t of Treasury, 498 F. Supp. 2d 150, 165 (D.D.C. 2007) (“Courts have repeatedly held that such ‘sense of Congress’ language is merely precatory and non-binding.”), aff’d, 545 F.3d 4 (D.C. Cir. 2008).
[15] Compare 42 U.S. Code § 2000d (“No person in the United States shall, on the ground of race, color, or national origin, be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any program or activity receiving Federal financial assistance.”) with Section 60506(b)(1) (empowering the Commission to create rules taking into account “preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin”) (emphasis added).
[16] See Section 60506(c) (“The Commission and the Attorney General shall ensure that Federal policies promote equal access to robust broadband internet access service by prohibiting deployment discrimination…”).
[17] West Virginia v. EPA, 142 S. Ct. 2587, 2607–2608 (2022); Util. Air Regul. Grp. (UARG) v. EPA, 573 U.S. 302, 324 (2014).
[18] Whitman v. Am. Trucking Ass’ns, 531 U.S. 457, 468 (2001).
[19] Broadband Equity, Access, and Deployment Program, BroadbandUSA, https://broadbandusa.ntia.doc.gov/resources/grant-programs/broadband-equity-access-and-deployment-bead-program (last visited Oct. 23, 2022).
[20] Affordable Connectivity Program, Federal Communications Commission, https://www.fcc.gov/acp (last visited Oct. 23, 2022).
[21] NPRM, supra note 1 at ¶24.
[22] NOI Reply Comments of AT&T, GN Docket No. 22-69 (Jun. 30, 2022), (“In particular, like all companies operating in a competitive marketplace, broadband providers must and do take expected demand into account, and the ‘economic feasibility’ qualifier protects their right to do so.”)
[23] Telecommunications: Broadband Deployment Is Extensive Throughout the United States, but It Is Difficult to Assess the Extent of Deployment Gaps in Rural Areas, U.S. Gov’t Accountability Off., GAO-06-426 (May 2006), https://www.gao.gov/assets/gao-06-426.pdf. [hereinafter “GAO-06-426”].
[24] Brian Whitacre & Roberto Gallardo, State Broadband Policy: Impacts on Availability, 44 Telecomm. Pol’y. 102025 (2020).
[25] Tonny J. Oyana, Exploring Geographic Disparities in Broadband Access and Use in Rural Southern Illinois: Who’s Being Left Behind?, 28 Gov’t. Info. Q. 252 (2011).
[26] GAO-06-426, supra note 23.
[27] Id.
[28] Whitacre & Gallardo, supra note 24.
[29] Juan Rendon Schneir & Yupeng Xiong, A Cost Study of Fixed Broadband Access Networks for Rural Areas, 40 Telecomm. Pol’y. 755 (2016).
[30] GAO-06-426, supra note 23.
[31] Brian Whitacre, Sharon Strover, & Roberto Gallardo, How Much Does Broadband Infrastructure Matter? Decomposing the Metro–Non-Metro Adoption Gap with the Help of the National Broadband Map, 32 Gov’t Info. Q. 261 (2015).
[32] Broadband: National Strategy Needed to Guide Federal Efforts to Reduce Digital Divide, U.S. Gov’t Accountability Off., GAO-22-104611 (May 31, 2022) [hereinafter “GAO-22-104611”].
[33] Id. See also, How Do Speed, Infrastructure, Access, and Adoption Inform Broadband Policy?, Pew Research Center (Jul. 7, 2022), https://www.pewtrusts.org/en/research-and-analysis/fact-sheets/2022/07/how-do-speed-infrastructure-access-and-adoption-inform-broadband-policy (“nearly 1 in 4 Americans do not subscribe to a home broadband connection, even where one is available”).
[34] Michelle Cao & Rafi Goldberg, New Analysis Shows Offline Households Are Willing to Pay $10-a-Month on Average for Home Internet Service, Though Three in Four Say Any Cost is Too Much, National Telecommunications and Information Administration (Oct. 6, 2022), https://www.ntia.doc.gov/blog/2022/new-analysis-shows-offline-households-are-willing-pay-10-month-average-home-internet.
[35] Kenneth Flamm & Anindya Chaudhuri, An Analysis of the Determinants of Broadband Access, 31 Telecomm. Pol’y. 312 (2007).
[36] Id.
[37] Victor Glass & Stela K. Stefanova, An Empirical Study of Broadband Diffusion in Rural America, 38 J. Reg. Econ. 70 (Jun. 2010).
[38] Christopher G. Reddick, Roger Enriquez, Richard J. Harris, & Bonita Sharma, Determinants of Broadband Access and Affordability: An Analysis of a Community Survey on the Digital Divide, 106 Cities 102904 (2020).
[39] Glass & Stefanova, supra note 37 at 70.
[40] GAO-22-104611, supra note 32.
[41] Alison Powell, Amelia Bryne, & Dharma Dailey, The Essential Internet: Digital Exclusion in Low-Income American Communities, 2 Pol’y & Internet 161 (2010).
[42] Oyana, supra note 25.
[43] GAO-06-426, supra note 23.
[44] GAO-22-104611, supra note 32.
[45] NPRM, supra note 1 at ¶ 66.
[46] See, e.g., Notice of Inquiry, Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (2022) (“If underlying cost or geographic hurdles exist in conjunction with demand in an area that makes it unprofitable, how should the Commission address such a situation?”).
[47] Public Knowledge, supra note 9 at 45 (“In many cases, a provider has the choice to build out and provide service in one area, or another. It will likely choose to build out in the more profitable area, even if it could break even or turn a profit serving the other, as well.”)
[48] See, e.g., N. Gregory Mankiw, Principles of Microeconomics, 9th ed. (2021) (“The opportunity cost of an item is what you give up to get that item. When making any decision, decision makers should take into account the opportunity costs of each possible action.”).
[49] Public Knowledge, supra note 9 at 45 (“determinations of economic feasibility also cannot take into account opportunity costs”).
[50] NPRM, supra note 1 at ¶ 66.
[51] Id.
[52] Eric Fruits & Kristian Stout, The Income Conundrum: Intent and Effects Analysis of Digital Discrimination, Int’l Ctr. for L. & Econ. (Nov. 14, 2022), available at https://laweconcenter.org/wp-content/uploads/2022/11/The-Income-Conundrum-Intent-and-Effects-Analysis-of-Digital-Discrimination.pdf.
[53] Declaration for Glenn Woroch, NOI Reply Comments of AT&T, supra note 22.
[54] T. Randolph Beard & George S. Ford, Digital Discrimination: Fiber Availability and Speeds, by Race and Income, Phoenix Ctr. for Advanced Legal & Econ. Pol’y Stud., Phoenix Ctr. Pol’y Paper No. 58 (Sep. 2022), https://phoenix-center.org/pcpp/PCPP58Final.pdf.
[55] Garson O’Toole, If You Torture the Data Long Enough, It Will Confess, Quote Investigator (Jan. 18, 2021), https://quoteinvestigator.com/2021/01/18/confess.
[56] Comments of CEI, GN Docket No. 22-69 (Feb. 21, 2023), at 8.
[57] NPRM, supra note 1 at ¶ 12.
[58] Public Knowledge, supra note 9 at 52 (“Congress has again centered the focus of the Commission’s actions on getting all people access, regardless of any discriminatory treatment or intent of the provider.”); see also, Brody, supra note 9.
[59] Ricci v. DeStefano, 557 U.S. 557, 577 (2009) [hereinafter “Ricci”].
[60] Id. (Intentional discrimination cases “present the most easily understood type of discrimination…[that] occur[s] where [a party[ has treated [a] particular person less favorably than others because of a protected trait.”).
[61] Inclusive Communities, supra note 10 at 528–29.
[62] See Public Knowledge, supra note 9 at 50-53.
[63] Id. at 5-40.
[64] See Section 60506(a)(1), (a)(3).
[65] See, Emergency Coal. to Def. Educ. Travel v. U.S. Dep’t of Treasury, 498 F. Supp. 2d 150, 165 (D.D.C. 2007) (“Courts have repeatedly held that such ‘sense of Congress’ language is merely precatory and non-binding.”), aff’d, 545 F.3d 4 (D.C. Cir. 2008).
[66] See Section 60506(c) (“The Commission and the Attorney General shall ensure that Federal policies promote equal access to robust broadband internet access service by prohibiting deployment discrimination…”).
[67] 167 Cong. Rec. 6046 (2021).
[68] 167 Cong. Rec. 6053 (2021).
[69] See, e.g., West Virginia v. EPA, 142 S. Ct. 2587 (2022); Util. Air Regul. Grp. (UARG) v. EPA, 573 U.S. 302 (2014).
[70] West Virginia v. EPA, 142 S. Ct. at 2607–2608; UARG, 573 U.S. at 324.
[71] Whitman v. Am. Trucking Ass’ns, 531 U.S. 457, 468 (2001).
[72] Inclusive Communities, supra note 10 at 534.
[73] 42 U.S.C. § 3604(a) (emphasis added).
[74] Inclusive Communities, supra note 10 at 534.
[75] Id.
[76] Id. at 534-35.
[77] Alexander v. Sandoval, 532 U.S. 275, 280 (2001).
[78] 42 U.S.C. §2000d (emphasis added).
[79] Public Knowledge, supra note 9 at 54.
[80] Inclusive Communities, supra note 10 at 533 (emphasis added).
[81] Id. at 521–22 (“Courts should avoid interpreting disparate-impact liability to be so expansive as to inject racial considerations into every housing decision. These limitations are also necessary to protect defendants against abusive disparate-impact claims.”).
[82] Id.
[83] Section 60506 (emphasis added).
[84] Ricci, supra note 59 at 557.
[85] NCTA, supra note 3 at 21.
[86] 429 U.S. 252, 266-67 (1977).
[87] Id. at 265 (“Proof of racially discriminatory intent or purpose is required to show a violation of the Equal Protection Clause.”).
[88] Id. at 266.
[89] Id. at 266-67.
[90] Id. at 267.
[91] Id. at 268.
[92] See, Texas Dep’t of Cmty. Affs. v. Burdine, 450 U.S. 248, 258–59 (1981). Note that the last two factors listed in this and the subsequent footnote are part of the McDonnell Douglas framework, McDonnell Douglas Corp. v. Green, 411 U.S. 792, 798, 93 S. Ct. 1817, 1822, 36 L. Ed. 2d 668 (1973). Technically, the Arlington factors are generally used when analyzing group discrimination and the McDonnell Douglas factors are used when analyzing discrimination against individuals. Section 60506 might, however, be plausibly read as permitting either approach to intentional discrimination in deployment decisions.
[93] See, Reeves v. Sanderson Plumbing Prod. Inc., 530 U.S. 133, 143–44 (2000).
[94] US Dep. of Justice, Title VI Legal Manual: Proving Discrimination – Intentional Discrimination, https://www.justice.gov/crt/fcs/T6Manual6 (“While statistical evidence is not required to demonstrate intentional discrimination, plaintiffs often successfully use statistics to support, along with other types of evidence, a claim of intentional discrimination.”).
[95] NPRM, supra note 1 at ¶ 35-36.
[96] Indeed, as NCTA notes in its comments, a safe harbor of this kind would give effect to Congress’ requirement that the FCC acknowledge constraints on deployment relating to “technical or economic feasibility.” NCTA, supra note 3 at 25-30.
[97] See, e.g., Comments of T-Mobile, GN Docket No. 22-69 (Feb. 21, 2023), at 30-31.
[98] Comments of USTelecom, GN Docket No. 22-69, (Feb. 21, 2023), at 33-34.
[99] Id.
[100] NPRM, supra note 1 at ¶ 52.
[101] Section 60506(a)(2).
[102] NPRM, supra note 1 at ¶ 76.
[103] These possibilities open the door for what public-choice economists call “rent extraction,” whereby public officials use the ability to control entry into a market for their own benefit. See Fred McChesney, Money for Nothing: Politicians, Rent Extraction, and Political Extortion (1997). See also, ICLE Ex Parte on Sec. 621, MB Docket No. 05-311 (Jul. 18, 2019), available at https://laweconcenter.org/wp-content/uploads/2019/07/ICLE-Comments-on-Implementation-of-Section-621a1-of-the-Cable-Communications-Policy-Act-of-1984.pdf (arguing that local and state franchising authorities often abuse their authority to get in-kind contributions from cable providers far beyond the 5% cost limit).
[104] NPRM, supra note 1 at ¶ 92.
[105] Broadband Equity, Access, and Deployment Program, BroadbandUSA, https://broadbandusa.ntia.doc.gov/resources/grant-programs/broadband-equity-access-and-deployment-bead-program (last visited Oct. 23, 2022).
[106] Affordable Connectivity Program, Federal Communications Commission, https://www.fcc.gov/acp (last visited Oct. 23, 2022).
ICLE Issue Brief If it looks like a duck, walks like a duck and quacks like a duck, then it just may be a duck. —Walter Reuther Executive . . .
If it looks like a duck, walks like a duck and quacks like a duck, then it just may be a duck. —Walter Reuther
Rate regulation can take many forms. Rates may be regulated through overt price controls, such as price ceilings or price floors; through less-overt rules governing the pace of price changes; or through quality mandates or restrictions. Some rate regulations can provide short-run benefits to certain groups of consumers or producers, but often result in shortages or surpluses that diminish overall welfare. In the long run, rate regulation often distorts investment incentives, leading to a misallocation of investment (e.g., to under- or over-investment).
For these reasons, since the late 1970s, direct rate regulation generally has fallen out of favor across most sectors of the economy, although there are some—such as insurance and utilities—where it remains commonplace. Nevertheless, elected officials and other policymakers frequently come under pressure from constituents and stakeholders to “do something” about the price of goods and services in the ostensibly “deregulated” sectors of the economy, such as when consumers characterize short-term price disruptions as “price gouging.” In some cases, firms may seek regulations to “stabilize” prices, while in others, rate regulation may be seen as a means to “increase access” to crucial goods and services.
Because the costs of overt rate regulations are so well-known, price controls are often buried under layers of bureaucracy or wrapped in with other policies and programs, such that policymakers can plausibly claim that their proposals do not directly regulate rates. While not explicit price controls, these programs amount to de facto rate regulation. It’s a regulatory version of the Duck Test.
Rate regulation—in any form and whatever the imagined benefits—is not a costless endeavor. Costs and risk do not disappear under rate regulation. Instead, they are shifted in one direction or another—typically with costs borne by consumers through some mix of suppressed or misdirected investment, sluggish improvements in quality, and reduced innovation.
This issue brief gives an overview, with a particular focus on the telecommunications sector, of the consequences of different types of overt rate regulation—price ceilings and prices floors—as well as how quality regulations can amount to rate regulation. Price controls, such as price ceilings and price floors, are government interventions in the market that aim to regulate the prices of goods and services. While they may have some short-term benefits, they can also lead to long-term consequences that are not always positive. We examine, in particular, four telecommunications programs in which de facto rate regulation is a key component.
In each of these examples, policymakers have gone to extraordinary lengths to avoid characterizing the programs’ pricing provisions as direct rate regulation. No matter how the policies are characterized, however, the consequences remain. When regulation is used to set prices on one side of the multi-sided broadband market at below-market rates, there will be upward pricing pressure on another side of the market. Ultimately, consumers who are not subject to the regulated rates will face higher prices, in turn putting pressure on policymakers to impose yet another layer of imprecise and complex regulation and even deeper constraints on investment.
Government policy may well be able to help accelerate broadband deployment to the unserved portions of the country where it is most needed. This issue brief concludes that the way to achieve that goal is not by imposing price controls on broadband providers. Instead, broadband access can best be expanded by removing costly, government-erected barriers to buildout and/or by subsidizing and educating consumers, where needed.
Since the deregulation of railroads, airlines, and trucking in the late 1970s, direct rate regulation has generally, except in a few outlier examples like insurance and utilities, fallen out of favor with elected officials and policymakers. To be sure, there are times when experts and activists have called for price controls in response to short-term price disruptions they characterize as “price gouging.” Because of a widespread skepticism of explicit price controls, rate-regulation efforts are instead often described as efforts to “stabilize” prices or “increase access” to goods and services. In many cases, the price controls are buried under layers of bureaucracy or bundled with other policies and programs, such that policymakers can plausibly claim that their proposals do not amount to regulating rates.
For example, the Wall Street Journal recently reported that 50 members of Congress sent a letter to President Joe Biden urging his administration “to pursue all possible strategies to end corporate price gouging in the real estate sector and ensure that renters and people experiencing homelessness across this country are stably housed this winter.”[1] Proposals include directing the Federal Housing Finance Agency (FHFA) to establish “anti-price gouging protections” and “just cause eviction standards” in rental properties with government-backed mortgages. Another proposal would have the Federal Trade Commission (FTC) issue new regulations defining “excessive” rent increases as an unfair trade practice. A third proposal would condition grants from the U.S. Department of Housing and Urban Development (HUD) on localities mitigating housing cost burdens and “adopting anti-rent-gouging measures.” None of these proposals amount to direct rent controls, but they would, in tandem, establish de facto rent regulation.
Efforts by policymakers to control prices, while distancing themselves from explicit rate regulation, have targeted myriad industries, including telecommunications services. For example, under former Chair Tom Wheeler, the Federal Communications Commission (FCC) voted to enact the 2015 Open Internet Order (OIO), which categorized internet service providers (ISPs) as “common carriers” under Title II of the Communications Act of 1934, thereby subjecting them to, among other things, net-neutrality principles. While rate regulation is among the defining features of most Title II services,[2] Wheeler nonetheless promised at the time to forebear from applying such regulations, stating flatly that “we are not trying to regulate rates.”[3]
But this assurance proved a small consolation. While the agency decided to waive “the vast majority of rules adopted under Title II,” it also made clear that the commission would “retain adequate authority to” rescind such forbearance in the future.[4] In his dissent from the OIO, Commissioner Ajit Pai noted the forbearance merely meant that “the FCC will not impose rules ‘for now.’”[5] Thus, while stopping short of imposing explicit rate regulation immediately, the OIO dangled the threat of rate regulation in the future.
Such threats amount to de facto rate regulation, in which agencies hold out the potential use of onerous rules in the future to shape providers’ pricing policies today. Tim Wu—credited with coining the term “net neutrality” and a recently departed senior advisor to President Joe Biden—has explicitly endorsed the use of threats by regulatory agencies as a means to obtain favored policy outcomes:
The use of threats instead of law can be a useful choice—not simply a procedural end run. My argument is that the merits of any regulative modality cannot be determined without reference to the state of the industry being regulated. Threat regimes, I suggest, are important and are best justified when the industry is undergoing rapid change—under conditions of “high uncertainty.” Highly informal regimes are most useful, that is, when the agency faces a problem in an environment in which facts are highly unclear and evolving. Examples include periods surrounding a newly invented technology or business model, or a practice about which little is known. Conversely, in mature, settled industries, use of informal procedures is much harder to justify.[6]
In 2017, under then-Chairman Pai, the FCC reclassified broadband under Title I of the Communications Act. In a 2018 article referencing the repeal of the 2015 rules, Gigi Sohn lamented that removing ISPs from Title II’s purview meant losing the “power to constrain ‘unjust and unreasonable’ prices, terms, and practices by [broadband] providers.”[7] More recently, standing as a nominee to the FCC, Sohn was asked during a 2021 confirmation hearing before the U.S. Senate Commerce Committee if she would support the agency’s regulation of broadband rates.[8] She responded: “No. That was an easy one.” Around the same time, FCC Chair Jessica Rosenworcel said in written comments that she did not plan to regulate broadband rates directly or indirectly.[9] Her comments indicated that the agency’s 2015 net-neutrality rules “expressly eschew future use of prescriptive, industry-wide rate regulation” and that she “supported this approach in the past and would do so again in the future.”
Nonetheless, policymakers’ interest in imposing controls on broadband rates continues unabated. In 2021, for example, President Biden’s American Jobs Plan called on Congress to reduce broadband prices:
President Biden believes that building out broadband infrastructure isn’t enough. We also must ensure that every American who wants to can afford high-quality and reliable broadband internet. While the President recognizes that individual subsidies to cover internet costs may be needed in the short term, he believes continually providing subsidies to cover the cost of overpriced internet service is not the right long-term solution for consumers or taxpayers. Americans pay too much for the internet—much more than people in many other countries—and the President is committed to working with Congress to find a solution to reduce internet prices for all Americans.[10]
But even in those cases in which rate regulation is imposed, proponents are careful to avoid calling it rate regulation. In defending the State of New York’s 2021 Affordable Broadband Act, for example, the state claimed that the law’s pricing provisions did not amount to rate regulation because they specified a price ceiling, rather than a specific price.[11]
This brief first provides an overview of the problems inherent in rate regulation, de facto or otherwise. It then identifies several instances of rate regulation being covertly introduced into broadband policy, and the dangers this poses to deployment.
In a competitive market, prices allow for the successful coordination of supply and demand, and the market price reflects both consumer demand and the costs of production. Of course, for those on the demand side of the equation, the price of a good or service is a cost to them, and they would prefer falling prices to rising prices. For suppliers, the price represents the revenue from selling the good or service and they would prefer rising prices to falling prices.
Because of this inherent tension, there is a natural inclination on the part of both consumers and producers to seek the government’s intervention in the competitive process to halt or slow price changes. The most obvious way the government can intervene is through rate regulation, such as price controls. Price controls can be divided into two categories: price ceilings that set a maximum price that sellers can charge and price floors that set the minimum price that consumers can pay. It is well-known and widely accepted that price controls can make both consumers and sellers worse off.[12] Consequently, policymakers may pitch policies that control prices under another name (e.g., “second generation rent relief”) or introduce policies that are not explicit price controls, but have substantially the same effects as price controls (e.g., quality-of-service mandates).
The most well-known example of a price ceiling is rent control—so well-known, in fact, that just about every introductory microeconomics textbook discusses the topic. Consider the market for apartment rentals shown in Figure I, which is based on an example from Gregory Mankiw’s widely used economics textbook.[13] In a competitive market, the price of apartments would be $1,500 and 2,500 apartments would be rented out.
Figure I: Rent Control in the Short Run and in the Long Run
SOURCE: Mankiw
At the market price, however, tenant advocates would complain of a housing “affordability crisis”—that apartment rents are too high. They argue that if prices were lower, more people could afford apartments. As a result, the government imposes a price ceiling, mandating that apartment rents cannot be any higher than $1,200. But at this price, in the short run, Panel (a) shows the number of apartments demanded (2,500) exceeds the quantity supplied (2,000). Because of this excess demand of 500 apartments, some people who want to rent an apartment would be unable to do so. In other words, there is a shortage of apartments.
In this example, the price ceiling makes the housing “crisis” worse, because fewer people are able to rent apartments than before the rent control was imposed. Some renters are better off because they are paying lower rents, but others are worse off because they cannot rent an apartment—even if they are willing to pay the market price.
Rent-control advocates might argue that there would be no shortage of apartments because apartments don’t just disappear. But they do, just not in the most obvious ways. In the short run, property owners may be more selective regarding to whom they will rent apartments. In the medium term, property owners might convert their apartments to short-term rentals (e.g., listing them on a service like Airbnb). In the somewhat longer term, property owner will reduce their maintenance investments or might convert their apartment buildings to condominiums or sell their rental house to an owner-occupier. Ultimately, developers may decide to invest in an area that is not subject to rent control, thereby reducing the construction of new rental housing. Thus, as shown in Panel (b), in the long run, rent control shifts the supply curve, further reducing the supply of housing and increasing the shortage to 1,000 apartments.
This is not just a theory. There are plenty of real-world examples of this phenomenon playing out. Some nonetheless advocate for a modified version of rent control, sometimes called “second generation” rent control.[14] Rather than regulating the price of apartments, the newer iterations of rent control cap the rate at which prices can rise (e.g., rents can rise no higher than the rate of inflation, plus 3%). Second-generation rent control still results in shortages and all the other consequences, but draws out these effects over a longer time period.
The most well-known form of price-floor regulation is the minimum wage, but there are many industries that are also subject to regulated price floors in the United States. Some states impose floors on the price of milk and alcoholic beverages. For decades, many U.S. agricultural products have been subject to price floors. Until the late 1970s and early 1980s, airline fares and stock-broker charges were subject to price-floor regulation.
Consider the market for wheat shown in Figure II, also adapted from Mankiw’s textbook.[15] In a competitive market, the price of wheat would be $3 and 100 bushels of wheat would be sold. At the market price, however, farmers would complain that the price is “too low.” They argue that, without assistance, their family farms would go under.
Figure II: Rent Market with a Price Floor
As a result, the government imposes a price floor, mandating that wheat cannot be bought for less than $4 per bushel. But at this price, the amount of wheat grown (120) exceeds the quantity demanded (80). Because of this excess supply of 40 bushels, there is a surplus of wheat and some farmers who want to sell wheat at the regulated price would be unable to do so. This introduces another problem for policymakers: price floors do not help suppliers who cannot sell their products at the regulated price.
To solve this problem, policymakers often turn to another set of policies. In some cases, the government promises to purchase any surplus. In one notable example, there is a cave in Missouri that contains 1.4 billion pounds of cheese purchased under such a program.[16] In other cases, the government replaces the price-floor regulation with a subsidy that promises to pay the difference between the market price and a “target price.”[17]
While a price ceiling can lead to “under” investment, a price floor can encourage “over” investment. For example, if a wheat farmer knows the minimum price that a bushel of wheat will fetch and that all the wheat grown will be purchased by someone, then the farmer has incentive to invest in wheat production rather than some other alternative.
Firms often respond to price floors in nonobvious ways. Baby boomers and their parents can tell stories of the luxurious accommodations enjoyed by those who flew coach in the 1960s and 1970s. Planes had spacious seating and some larger planes had a piano lounge onboard—features that were due, in a large part, to rate regulation that set a price floor on airline tickets. Because airlines faced no price competition, they competed for customers by offering superior service. In other words, they responded to price-floor regulations by “over” investing in service and amenities.[18]
In jurisdictions with high minimum wages, firms respond by using less labor. For example, restaurants may switch from table service to counter service, or they may replace some counter service with self-service electronic kiosks. Restaurants that maintain table service may assign more tables to each server. As the perceived level of service declines, consumers may substitute dining at-home for dining out.
Because the effects of explicit rate regulation are so well-known and so obvious, policymakers who seek to regulate prices often attempt to do so in less-obvious ways. One already-discussed way is the regulation of price changes, rather than the prices themselves. For example, many rent-control price ceiling programs limit the rate at which rents can increase from year-to-year, a policy described as “rent stabilization.”[19] Many jurisdictions with minimum wage price-floor programs mandate an increase in the minimum wage in-line with the inflation rate.[20]
Another way in which officials can effectively—but not explicitly—regulate rates is through quality mandates. For example, some agricultural products are subject to “marketing orders,” which are legal cartels than can dictate the price and quality of produce.[21] Consider an apple market subject to a marketing order that specifies fresh apples must be of a certain shape and size, such that only large, round apples can be sold as fresh produce.
Presumably, consumers prefer large apples to small apples and prefer round apples to misshapen apples. Thus, as shown in Figure III, the order that only large, round apples can be sold as fresh has the effect of increasing/shifting the demand curve. Consumers would be willing to pay more for the seemingly better fruit, and they’d be willing to buy more. But the order also increases the cost to apple growers. They have to find a way to dispose of their smaller or misshapen apples, perhaps by making apple sauce or juicing the fruit. They also incur higher costs of managing their crop to produce more of the higher-quality fruit. This has the effect of decreasing/shifting the supply curve for fresh fruit. Growers will supply less fruit at a higher cost.
Figure III: Market with a Quality Mandate
Combining the effects from both the shift in supply and the shift in demand shows that the marketing order unambiguously results in a higher price for apples. What is not known, however, is whether more or fewer apples are sold. That will depend on the elasticities of demand and supply. Because the order results in a higher price, however, it has created a de facto price floor without explicitly setting one. Consumers are not aware that they are paying a higher price because they do not know what type of fruit would be available, and at what price, absent the quality restrictions.
The FCC obviously has a long history of explicit rate regulation since its inception in 1934.[22] Among its founding mandates, the commission was charged with ensuring that rates were fair, that service was reliable and efficient, and that access to telecommunications services was available to all Americans.[23] During this time, the FCC governed telephone-service rates through a system of rate-of-return regulation, in which rates were set based on the cost of providing service and the company’s desired return on investment.[24] In the latter half of the 20th century, and especially since Congress passed a major overhaul of the Communications Act in 1996, a more deregulatory approach to telecommunications has prevailed.
This made sense in the 1990s, and has only made more sense over time, as different communications modalities have been developed, and competition has flourished throughout the market. The reality of the competitive market is acknowledged by regulators across the political spectrum, as we noted above. Both potential and current FCC commissioners note that rate regulation of the broadband industry is undesirable.[25]
At the same time, however, current and potential FCC commissioners—along with other regulators at adjacent agencies—have shaped federal policy in ways that effectively amount to de facto rate regulation. Rate regulation by design and rate regulation in effect arrive at the same damaging economic consequences for consumers and the economy as a whole, however. As such, it is worth reviewing some of the recent efforts to enact de facto rate regulation.
The National Telecommunications and Information Administration’s (NTIA) notice of funding opportunity under the Broadband Equity, Access, and Deployment (BEAD) program requires each participating U.S. state or territory to include a “middle-class affordability plan to ensure that all consumers have access to affordable high-speed internet” (emphasis in original).[26] The notice provides several examples of how this could be achieved, including:
Despite the Infrastructure Investment and Jobs Act’s (IIJA) explicit prohibition of price regulation, the NTIA’s approval process appears to envision exactly this. The first example provided above is clear rate regulation. It specifies a price (“low-cost”); a quantity (“all middle-class households”); and imposes a quality mandate (“high-speed”). Toward these ends, the notice provides an example of a “low-cost” plan that would be acceptable to NTIA:
The notice states that the focus of this portion of the program is to foster broadband access, rather than broadband adoption. But broadband access alone may not be sufficient to drive greater rates of broadband adoption. A report by the U.S. Government Accountability Office concluded that “even where broadband service is available … an adoption gap may persist due to the affordability of broadband and lack of digital skills.”[28] The GAO report notes that nearly one-third of those with access to broadband do not subscribe to it.[29] Brian Whitacre and his co-authors found that, while the reduced levels of broadband access in rural areas explained 38% of the rural-urban broadband-adoption gap in 2011, differences in other general characteristics—such as income and education—explain “roughly half of the gap.”[30]
A policy bulletin published by the Phoenix Center for Advanced Legal & Economic Public Policy Studies notes that the NTIA did not conclude that broadband was unaffordable for middle-class households.[31] George Ford, the bulletin’s author, collected data on broadband adoption by income level. The data indicate that, in general, internet-adoption rates increase with higher income levels. Higher-income households have higher adoptions rates (97.3%) than middle-income households (92.9%) which in turn have higher adoption rates than lower-income households (78.1%). For each of the 50 states and the District of Columbia, the Phoenix bulletin finds that middle-income internet-adoption rates are, to a statistically significant degree, higher than lower-income adoption rates.
The Phoenix bulletin concludes that broadband currently is “affordable” to middle-class households and that “no direct intervention is required” to ensure affordability to the middle class. These observations, however, invite questions regarding how NTIA intends to administer the BEAD program.
As John Mayo, Greg Rosston, & Scott Wallsten note:
A substantial portion of the unserved and underserved areas of the country that are the likely targets of the BEAD program, however, are rural, low-population density areas where deployment costs will be high. These high deployment costs may seem to indicate that even “cost-based” rates—normally seen as an attractive competitive benchmark—may be high, violating the IIJA’s “affordability” standard.[32]
The only effective way to reduce broadband price, increase access, and improve quality simultaneously is to increase supply. That would call for prioritizing subsidies to broadband providers before consumers. Although consumer subsidies would increase the demand for broadband, which would have a knock-on effect of potentially attracting long-term investment from providers, it could also increase the price for households who do not receive the subsidy. Direct provider subsidies targeted at hard-to-connect areas could avoid many of the problems that price controls and direct user subsidies can create.[33] Ultimately, however, price controls—even de facto or “backdoor” price controls—would likely slow broadband deployment.
In 2018, Congress provided the secretary of U.S. Department of Agriculture authority to establish a pilot project intended to expand broadband deployment in rural areas, known as the ReConnect Loan and Grant Program. According to the Congressional Research Service, as of December 2022, USDA had awarded more than $3 billion of ReConnect funds through three funding rounds.[34]
With its third round of funding in 2021, USDA announced that, for the first time, applicants would receive a preference, in the form of “points,” for agreeing to abide by so-called “net neutrality” rules similar to those that the FCC had eliminated in 2018’s Restoring Internet Freedom Order. The department simultaneously added affordability—providing a “low-cost option”—as a point criteria. In addition, the third round required that projects must provide broadband access at speeds of at least 100/100 Mbps (i.e., 100 Mbps symmetrical speed). Round 4, announced in August 2022, includes the same criteria.
USDA’s third- and fourth-round requirements under the ReConnect program could be characterized as “back-door” rate regulation. They specify pricing as a point criteria (“low-cost option”) and impose a quality mandate (100/100 Mbps). While it does not mandate a low-cost option, the point weighting indicates that pricing is a priority in awarding funds under the program.
This sort of second-generation price control, while it does not create a centrally directed rate schedule, amounts to the same dynamic. These preferences, while potentially more diffuse in the short term, ultimately create the same medium- and long-term dynamics that drive up prices, and reduce quality and availability.
In 2021, the State of New York passed the Affordable Broadband Act (ABA).[35] The act requires ISPs to offer all qualifying low-income households at least two internet-access plans: (1) download speeds of at least 25 megabits-per-second for no more than $15-a-month, or (2) download speeds of at least 200 megabits-per-second for no more than $20-a-month. Providers with fewer than 20,000 subscribers may be eligible for exemption from the law. More than one-third of households in the state would be eligible to participate in the program.
Before it went into effect, a group of ISPs obtained an injunction in federal court to block the law.[36] The plaintiffs claimed that the ABA amounted to common-carrier rate regulation, which is preempted by federal law. ISPs are regulated as an “information service” under Title I of the Federal Communications Act of 1934, rather than as Title II common-carrier “telecommunications services.” As such, the plaintiffs claim neither the FCC nor the states can regulate ISPs as common carriers.
New York attempted to dance around this complication by asserting that the ABA merely set a price ceiling.[37] Because ISPs were permitted to charge any price below the ceiling, “the ABA does not ‘rate regulate’ broadband services,” the state argued.[38] The court shut down that line of reasoning, citing several earlier decisions that conclude “‘[p]rice ceilings’ regulate rates.”[39] The matter is currently on appeal before the 2nd U.S. Circuit Court of Appeals, where oral arguments were heard in January 2023.[40]
The FCC’s 2015 Open Internet Order (“OIO”),[41] although explicitly forbearing from rate regulation,[42] was a regulatory scheme that imposed many of the same effects. Further, with prohibitions on practices like “zero rating,” the regulation walks right up to the line of explicit rate regulation, if not over it.
At an abstract level, the OIO was predicated on the idea that it was possible to impose some common-carriage obligations on broadband providers but to leave out rate regulation. Fundamentally, the OIO failed to take account of the economics that drive ISP investment and pricing, for both edge providers and consumers. In short, in a condition of scarcity—such as limited bandwidth and limited infrastructure to increase bandwidth—there will always be some form of rationing; it will be accomplished either through prices or through regulatory intervention. Even if a regulator disavows explicit rate regulation, intervention into providers’ business models and technical decisions will inevitably shape pricing in much the same way as explicit price regulation does, through the “hydraulic effect” of regulation.[43]
Generally speaking, the OIO imposed a form of “negative” rate regulation that short circuited the normal course of rationing among broadband providers and their customers. It prohibited providers from applying anything other than a zero price to edge providers.[44] It outright prohibited “paid prioritization”—that is, seeking payments for network utilization from edge providers like Google, Facebook, and Netflix—while casting suspicion on other pricing schemes under the Internet Conduct Standard.[45] Thus, on one hand, the OIO did explicitly regulate rates by imposing a zero price, and, on the other, implemented a de facto rate-regulation scheme by subjecting providers to regulatory scrutiny if they sought novel business relationships with partners.
The best example of this latter situation was the commission’s attack on “zero rating.” Zero rating is the practice of a broadband provider not counting data from certain sources against a customer’s data allowance within a given period.[46] In truth, this is a business model very familiar to any casual internet user: edge providers like gaming companies, email hosts, and social-media platforms frequently offer free or low-cost versions of their service in order to attract a critical mass of users.[47]
Zero-rated broadband service works identically. A content provider like Netflix or YouTube will partner with an ISP like T-Mobile or Comcast in order to provide broadband customers with access to the provider’s content without that use counting against their data plan. Zero rating does not mean that other services are blocked; just that those other services will count against a periodic data allowance.[48] Generally speaking, this sort of business arrangement is a boon to consumers, particularly low-income consumers who can only afford the most restrictive data plans.[49]
With the OIO, however, the FCC introduced the vague Internet Conduct Standard, which gave it broad latitude to ban practices like zero rating.[50] The standard prohibited providers from “unreasonably interfer[ing] with or unreasonably disadvantage[ing]” consumers’ access to lawful content, applications, or services, as well as edge providers’ ability to distribute lawful content, applications, or services.[51] In 2016, the FCC sent letters to AT&T and Verizon, suggesting that the two companies’ use of zero rating were likely violations of the OIO.[52]
Even this implicit threat of regulatory proceedings to examine the propriety of zero rating likely had a chilling effect. Indeed, in an analogous context, the U.S. Circuit Court of Appeals for the D.C. Circuit struck down earlier net-neutrality regulations from the FCC on the grounds that they amounted to the application of de facto common-carriage obligations, even though that commission had refrained from applying Title II.[53]
Regulatory presumptions against zero rating and other forms of paid prioritization similarly amount to de facto rate regulation.[54] As multi-sided platforms, broadband providers seek to balance service and pricing across users and edge providers. As regulation restricts broadband providers’ ability to seek agreements with other large service providers, investment and consumers prices will be forced to shift in order to accommodate. In the long run, this will result in price increases, shortages, declines in quality or, most likely, some mix of the three.
Both economics and history demonstrate that rate regulations that cap the price of a product below the market price lead to shortages by increasing the quantity demanded without increasing the quantity supplied. Over time, such price caps can reduce the overall supply, as providers curtail or slow output-improving investments.
Broadband rate regulation—whether in the forms of direct and explicit price controls or back-door de facto policies—will result in slowed broadband investment and deployment. Broadband providers have a wide range of investment opportunities, with expected returns as a key consideration in evaluating these opportunities. Policies like price ceilings, which reduce the returns on deployment investments, will in turn reduce the likelihood that such investments will be made, thereby slowing broadband deployment.
As we noted in an earlier issue brief, broadband providers—like all firms—have limited resources with which to make their investments.[55] While profitability is a necessary precondition for investment, not all profitable investments can be undertaken. Among the universe of potentially profitable projects, firms are likely to give priority to those that promise greater returns on investment relative to those with lower ROI. Thus, any evaluation of broadband deployment and access must examine not only whether a given deployment is likely to be profitable, but also how its expected returns compare to other investment opportunities.
In broadband, returns on investment depend on several factors. Population density, terrain, regulations, and taxes are all important cost factors. The consumer population’s willingness to adopt and pay for broadband are key demand-related factors. In addition to these cost and demand factors, timing factors concerning both investment and adoption affect the ROI of any deployment investment. Generally speaking, the longer it takes for a given deployment to recoup its investment and generate a return, the lower the ROI and, in turn, the lower the likelihood that the investment will be made. Similarly, binding rate regulation—whether explicit or de facto—will reduce the ROI of deployments subject to that regulation.
Not only would existing broadband providers make fewer and less-intensive investments to maintain their networks, but they would also invest less in improving quality:
When it faces a binding price ceiling, a regulated monopolist is unable to capture the full incremental surplus generated by an increase in service quality. Consequently, when the firm bears the full cost of the increased quality, it will deliver less than the surplus-maximizing level of quality. As Spence (1975, p. 420, note 5) observes, “where price is fixed … the firm always sets quality too low.”[56]
Quality suffers under price regulation not just because firms can’t capture the full value of their investments, but also because it is often difficult to account for quality improvements in regulatory-pricing schemes:
The design and enforcement of service quality regulations is challenging for at least three reasons. First, it can be difficult to assess the benefits and the costs of improving service quality. Absent accurate knowledge of the value that consumers place on elevated levels of service quality and the associated costs, it is difficult to identify appropriate service quality standards. It can be particularly challenging to assess the benefits and costs of improved service quality in settings where new products and services are introduced frequently. Second, the level of service quality that is actually delivered sometimes can be difficult to measure. For example, consumers may value courteous service representatives, and yet the courtesy provided by any particular representative may be difficult to measure precisely. When relevant performance dimensions are difficult to monitor, enforcing desired levels of service quality can be problematic. Third, it can be difficult to identify the party or parties that bear primary responsibility for realized service quality problems. To illustrate, a customer may lose telephone service because an underground cable is accidentally sliced. This loss of service could be the fault of the telephone company if the company fails to bury the cable at an appropriate depth in the ground or fails to notify appropriate entities of the location of the cable. Alternatively, the loss of service might reflect a lack of due diligence by field workers from other companies who slice a telephone cable that is buried at an appropriate depth and whose location has been clearly identified.[57]
The design and enforcement of service quality regulations is challenging for at least three reasons. First, it can be difficult to assess the benefits and the costs of improving service quality. Absent accurate knowledge of the value that consumers place on elevated levels of service quality and the associated costs, it is difficult to identify appropriate service quality standards. It can be particularly challenging to assess the benefits and costs of improved service quality in settings where new products and services are introduced frequently.
Second, the level of service quality that is actually delivered sometimes can be difficult to measure. For example, consumers may value courteous service representatives, and yet the courtesy provided by any particular representative may be difficult to measure precisely. When relevant performance dimensions are difficult to monitor, enforcing desired levels of service quality can be problematic.
Third, it can be difficult to identify the party or parties that bear primary responsibility for realized service quality problems. To illustrate, a customer may lose telephone service because an underground cable is accidentally sliced. This loss of service could be the fault of the telephone company if the company fails to bury the cable at an appropriate depth in the ground or fails to notify appropriate entities of the location of the cable. Alternatively, the loss of service might reflect a lack of due diligence by field workers from other companies who slice a telephone cable that is buried at an appropriate depth and whose location has been clearly identified.[57]
None of these concerns dissipate where regulators use indirect, de facto means to cap prices. Broadband is a classic multi-sided market.[58] If the price on one side of the market is set at below-market rates through rate regulation, then there will be upward pricing pressure on the other side of the market. Ultimately, consumers who are not subject to the regulated rates will face higher prices, which puts pressure on policymakers to impose yet another layer of imprecise and complex regulation and even deeper constraints on investment.
It’s important to understand that rate regulation—in any form and whatever the imagined benefits—is not a costless endeavor. Costs and risk do not disappear under rate regulation. Instead, they are shifted in one direction or another—typically with costs borne by consumers through some mix of suppressed investment, sluggish improvements in quality, and reduced innovation.
Government policy may well be able to help accelerate broadband deployment to the unserved portions of the country where it is most needed. But the way to get there is not by imposing price controls on broadband providers. Instead, broadband access can best be expanded by removing costly, government-erected barriers to buildout and/or by subsidizing and educating consumers where necessary.
[1] The Editorial Board, Nationwide Rent Control?, Wall St. J. (Jan. 22, 2023), https://www.wsj.com/articles/nationwide-rent-control-congress-democrats-progressives-housing-president-biden-11674233540.
[2] Lawrence J. Spiwak, USTelecom and Its Aftermath, 71 Fed. Comm. L. J. 39 (2018), available at http://www.fclj.org/wp-content/uploads/2018/12/71.1-%E2%80%93-Lawrence-J.-Spiwak.pdf.
[3] FCC Reauthorization: Oversight of the Commission, Hearing Before the Subcommittee on Communications and Technology, Committee on Energy and Commerce, House of Representatives, 114 Cong. 27 (Mar. 19, 2015) (Statement of Tom Wheeler).
[4] Protecting and Promoting the Open Internet, 80 FR 19737 (Apr. 13, 2015) (codified at 47 CFR 1, 47 CFR 8, and 47 CFR 20), https://www.federalregister.gov/documents/2015/04/13/2015-07841/protecting-and-promoting-the-open-internet, (“2015 OIO”) at ¶¶ 51 & 538
[5] Id., Dissenting Statement of Ajit Pai, https://docs.fcc.gov/public/attachments/FCC-15-24A5.pdf.
[6] Tim Wu, Agency Threats, 60 Duke L.J. 1841, 1842 (2011).
[7] Gigi B. Sohn, A Policy Framework for an Open Internet Ecosystem, 2 Geo. L. Tech. Rev. 335 (2018) at 345.
[8] David Shepardson, FCC Nominee Does Not Support U.S. Internet Rate Regulation, Reuters (Dec. 1, 2021), https://www.reuters.com/world/us/fcc-nominee-does-not-support-us-internet-rate-regulation-2021-12-01.
[9] Id.
[10] The White House, Fact Sheet: The American Jobs Plan (Mar. 31, 2021), https://www.whitehouse.gov/briefing-room/statements-releases/2021/03/31/fact-sheet-the-american-jobs-plan (emphasis added).
[11] NY State Telecom. Assoc. v. James, 2:21-cv-2389 (DRH) (AKT), Memorandum and Order, Document 25 (E.D. N.Y. June 11, 2021), https://ecf.nyed.uscourts.gov/doc1/123117827301 (“Memorandum and Order”).
[12] See, for example, N. Gregory Mankiw, PRINCIPLES OF MICROECONOMICS, 4th ed., Thomson South-Western (2007); Paul Krugman & Robin Wells, Economics, 6th ed., MacMillan (2021); Steven A. Greenlaw & David Shapiro, Principles of Microeconomics 2nd ed., OpenStax (2017).
[13] Id., Mankiw.
[14] See, e.g., David L. Mengle, The Effect of Second Generation Rent Control on the Quality of Rental Housing, Fed. Res. Bank of Rich., Working Paper 85-5 (Nov. 1985), https://www.richmondfed.org/-/media/RichmondFedOrg/publications/research/working_papers/1985/pdf/wp85-5.pdf.
[15] Mankiw, supra note 12.
[16] Gitanjali Poonia, Why Does the U.S. Government Have 1.4 Billion Pounds of Cheese Stored in a Cave Underneath Springfield, Missouri?, Deseret News (Feb. 14, 2022), https://www.deseret.com/2022/2/14/22933326/1-4-billion-pounds-of-cheese-stored-in-a-cave-underneath-springfield-missouri-jimmy-carter-reagan.
[17] For example, the U.S. Department of Agriculture’s Price-Loss Coverage program issues payments when the effective price of a covered commodity is less than the respective reference price for that commodity. See, Agriculture Risk Coverage (ARC) & Price Loss Coverage (PLC), USDA (Oct. 2022), https://www.fsa.usda.gov/Assets/USDA-FSA-Public/usdafiles/FactSheets/2022/fsa_arc_plc_factsheet_101922.pdf.
[18] See, Richard H. K. Vietor, Contrived Competition: Regulation and Deregulation in America (1996) at 45 (“Since capacity could no longer serve as a means of differentiation, the trunk carriers had to devise new means of service competition. ‘Capacity wars’ gave way to ‘lounge wars.’”).
[19] See, e.g., Rent Stabilization, Oregon Dept. of Admin. Serv. (n.d.), https://www.oregon.gov/das/OEA/pages/rent-stabilization.aspx.
[20] Dave Kamper & Sebastian Martinez Hickey, Tying Minimum-Wage Increases to Inflation, as 13 States Do, Will Lift Up Low-Wage Workers and Their Families across the Country, Econ. Pol’y Inst. (Sep. 6, 2022), https://www.epi.org/blog/tying-minimum-wage-increases-to-inflation-as-12-states-do-will-lift-up-low-wage-workers-and-their-families-across-the-country.
[21] See, Darren Filson, Edward Keen, Eric Fruits & Thomas Borcherding, Market Power and Cartel Formation: Theory and an Empirical Test, 44 J. L. & Econ. 465 (2001).
[22] Vietor, supra note 17 at ch. 4.
[23] Id.
[24] Id.
[25] Supra notes 13-15
[26] Notice of Funding Opportunity, Broadband Equity, Access, and Deployment Program, NTIA-BEAD-2022, NTIA (May 2022), available at https://broadbandusa.ntia.doc.gov/sites/default/files/2022-05/BEAD%20NOFO.pdf (note that the IIJA itself did not include this requirement, and this is an addition by NTIA as part of the NOFO process; thus, it is unclear the extent to which this represents a valid requirement by NTIA under the BEAD program).
[28] Broadband: National Strategy Needed to Guide Federal Efforts to Reduce Digital Divide, GAO-22-104611, U.S. Gov’t Accountability Off. (May 31, 2022), https://www.gao.gov/assets/gao-22-104611.pdf, [hereinafter “GAO-22-104611”].
[29] Id. (“According to FCC data, about 31 percent of people nationwide who have access to broadband at speeds of 25/3 Mbps have not subscribed to it ….); see also, How Do Speed, Infrastructure, Access, and Adoption Inform Broadband Policy?, Pew Research Center (Jul. 7, 2022), https://www.pewtrusts.org/en/research-and-analysis/fact-sheets/2022/07/how-do-speed-infrastructure-access-and-adoptioninform-broadband-policy (“nearly 1 in 4 Americans do not subscribe to a home broadband connection, even where one is available”).
[30] Brian Whitacre, Sharon Strover, & Roberto Gallardo, How Much Does Broadband Infrastructure Matter? Decomposing the Metro–Non-Metro Adoption Gap with the Help of the National Broadband Map, 32 Gov’t Info. Q. 261 (2015).
[31] George S. Ford, Middle-Class Affordability of Broadband: An Empirical Look at the Threshold Question, Phoenix Ctr. for Adv. Leg. & Econ. Pub. Pol’y Stud., Pol’y Bull. No. 61 (Oct. 2022), https://phoenix-center.org/PolicyBulletin/PCPB61Final.pdf.
[32] John W. Mayo, Gregory L. Rosston & Scott J. Wallsten, From a Silk Purse to a Sow’s Ear? Implementing the Broadband, Equity, Access and Deployment Act, Geo. U. McDonough Sch. of Bus. Ctr. for Bus. & Pub. Pol’y (Aug. 2022), https://georgetown.app.box.com/s/yonks8t7eclccb0fybxdpy3eqmw1l2da?mc_cid=95d011c7c1&mc_eid=dc30181b39.
[33] Even as a second-best option, user subsidies remain far preferable to price controls, as they at least directionally work within a market framework and encourage providers to deploy where there is genuine need and demand.
[34] Lisa S. Benson, USDA’s ReConnect Program: Expanding Rural Broadband, Cong. Res. Serv., R47017 (Dec. 14, 2022), https://crsreports.congress.gov/product/pdf/R/R47017.
[35] Memorandum and Order, supra note 11.
[37] Id. (“In Defendant’s words, the ABA concerns ‘Plaintiffs’ pricing practices’ by creating a ‘price regime’ that ‘set[s] a price ceiling,’ which flatly contradicts her simultaneous assertion that ‘the ABA does not “rate regulate” broadband services.’”)
[38] Id.
[39] Id.
[40] Randolph J. May & Seth L. Cooper, Second Circuit Hears Preemption Challenge to New York’s Broadband Rate Regulation Law, FedSoc Blog (Feb. 7, 2023), https://fedsoc.org/commentary/fedsoc-blog/second-circuit-hears-preemption-challenge-to-new-york-s-broadband-rate-regulation-law.
[41] 2015 OIO, supra note 4.
[42] As noted above, however, the FCC still retained the power to impose rate regulation at a future date. This obviously muddies the discussion, as a looming threat of potential rate regulation would likely exert some influence over broadband providers’ decisions.
[43] See Geoffrey A. Manne, The Hydraulic Theory of Disclosure Regulation and Other Costs of Disclosure, 58 Ala. L. Rev. 473 (2007).
[44] The OIO banned paid prioritization outright, but regulated nonlinear pricing mechanisms like sponsored data under the Internet Conduct Standard. See 2015 OIO, supra note 4 at ¶ 151-53. But the order also rejected the “commercially reasonable” standard of the 2010 OIO and replaced it with a more amorphous, and more restrictive, “unreasonable interference or unreasonable disadvantages” standard. Following the commission’s letters expressing its hostility to AT&T’s and Verizon’s zero-rating programs (supra note 52, and accompanying text), it is safe to assume that such pricing schemes stood on extremely thin ice under the 2015 OIO.
[45] See 2015 OIO, supra note 4 at ¶ 151-53.
[46] See 2015 OIO, supra note 4 at ¶ 151; Jeffrey A. Eisenach, The Economics of Zero Rating, NERA (Mar. 2015), available at https://www.nera.com/content/dam/nera/publications/2015/EconomicsofZeroRating.pdf.
[47] See, e.g., Geoffrey A. Manne & Kristian Stout, In the Matter Of: Telecom Regulatory Authority of India’s 9/12/15 Consultation Paper On Differential Pricing For Data Services at 4 and accompanying citations, Int’l Ctr. for L & Econ. (Jan. 4, 2015), available at https://laweconcenter.org/wp-content/uploads/2017/08/icle-india_diff_pricing_comments_2016.pdf.
[48] Id. at 9.
[49] See, Understanding and Appreciating Zero-Rating: The Use and Impact of Free Data in the Mobile Broadband Sector, Multicultural Media, Telecom and Internet Council (May 9, 2016), available at http://mmtconline.org/WhitePapers/MMTC_Zero_Rating_Impact_on_Consumers_May2016.pdf.
[50] 2015 OIO, supra note 4 at ¶ 136.
[52] See Jeff Dunn, The FCC Thinks AT&T’s Policies ‘Harm Consumers’ – And It’s Warning Verizon, Too, Business Insider (Dec. 2, 2016), http://www.businessinsider.com/fcc-verizon-att-zero-rating-net-neutrality-letter-directv-now-2016-12.
[53] Verizon, 740 F.3d at 657 (“The Commission has provided no basis for concluding that in permitting ‘reasonable’ network management, and in prohibiting merely ‘unreasonable’ discrimination, the Order’s standard of ‘reasonableness’ might be more permissive than the quintessential common carrier standard.”).
[54] See, e.g., Kristian Stout, Geoffrey A. Manne, & Allen Gibby, Policy Comments of the International Center for Law & Economics, Restoring Internet Freedom NPRM, WC Docket No. 17-108 at 36 and associated citations, Int’l Ctr. for L. & Econ. (Jul. 17, 2017), available at https://laweconcenter.org/wp-content/uploads/2017/09/icle-comments_policy_rif_nprm-final.pdf; see also Daniel A. Lyons, Usage-Based Pricing, Zero-Rating, and the Future of Broadband Innovation, 11 Free State Foundation Perspectives 1 (2016), http://works.bepress.com/daniel_lyons/80.
[55] Eric Fruits & Kristian Stout, The Income Conundrum: Intent and Effects Analysis of Digital Discrimination, Int’l Ctr. for L & Econ., Issue Brief 2022-11-14 (Nov. 2022), https://laweconcenter.org/wp-content/uploads/2022/11/The-Income-Conundrum-Intent-and-Effects-Analysis-of-Digital-Discrimination.pdf.
[56] David E. M. Sappington & Dennis L. Weisman, Price Cap Regulation: What Have We Learned from Twenty-Five Years of Experience in the Telecommunications Industry?, 38 J. Regul. Econ. 227 (Sep. 2010), http://bear.warrington.ufl.edu/centers/purc/docs/papers/1012_Sappington_Price_Cap_Regulation.pdf, at 9.
[57] Id. at 10.
[58] Issue Spotlight: Two-Sided Markets, Int’l Ctr. for L & Econ. (Nov. 8, 2022), https://laweconcenter.org/resources/policy-comments-international-center-law-economics-restoring-internet-freedom-nprm.
Presentations & Interviews ICLE Director of Innovation Policy Kristian Stout was interviewed by RFD-TV for a story item about the challenges involved in connecting rural areas . . .
ICLE Director of Innovation Policy Kristian Stout was interviewed by RFD-TV for a story item about the challenges involved in connecting rural areas to broadband internet.
One of the threats that could affect the efficacy of this program could be different state authorities not necessarily focusing on people who have traditionally been very difficult to connect to the internet but looking at lower hanging fruit that it’s easier to connect, like people who might have slower than extremely fast but are faster than what we consider nonexistent broadband service. There are a number of hurdles that have just traditionally existed everywhere in the United States for broadband deployment. These include things like municipal permitting, getting rights of way, and then one of the largest drivers cost is access to utility poles across the United States. There are some more complicated problems that go into accessing these poles around whether they’re privately-owned or whether they’re owned by municipalities and co-ops, which can easily explode costs for a particular deployment and make it so that the money that the federal government is directing to reach these remote areas is not being fully-used to reach these people but is instead being wasted.
One of the threats that could affect the efficacy of this program could be different state authorities not necessarily focusing on people who have traditionally been very difficult to connect to the internet but looking at lower hanging fruit that it’s easier to connect, like people who
might have slower than extremely fast but are faster than what we consider nonexistent broadband service. There are a number of hurdles that have just traditionally existed everywhere in the United States for broadband deployment. These include things like municipal permitting, getting rights of way, and then one of the largest drivers cost is access to utility poles across the United States. There are some more complicated problems that go into accessing these poles around whether they’re privately-owned or whether they’re owned by municipalities and co-ops, which can easily explode costs for a particular deployment and make it so that the money that the federal government is directing to reach these remote areas is not being fully-used to reach these people but is instead being wasted.
TOTM Large portions of the country are expected to face a growing threat of widespread electricity blackouts in the coming years. For example, the Western Electricity . . .
Large portions of the country are expected to face a growing threat of widespread electricity blackouts in the coming years. For example, the Western Electricity Coordinating Council—the regional entity charged with overseeing the Western Interconnection grid that covers most of the Western United States and Canada—estimates that the subregion consisting of Colorado, Utah, Nevada, and portions of southern Wyoming, Idaho, and Oregon will, by 2032, see 650 hours (more than 27 days in total) over the course of the year when available enough resources may not be sufficient to accommodate peak demand.
The Infrastructure Investment and Jobs Act (IIJA) directs the Federal Communications Commission to prevent discrimination in broadband access. In addition to preventing racial, ethnic, or . . .
The Infrastructure Investment and Jobs Act (IIJA) directs the Federal Communications Commission to prevent discrimination in broadband access. In addition to preventing racial, ethnic, or religious discrimination, the law seeks to remedy income discrimination. At the same time, the IIJA orders the FCC to take account of economic and technical feasibility of preventing the proscribed discrimination. These provisions of the IIJA raise complex legal and economic questions. Should the FCC focus on discriminatory intent or disparate impacts? How can the FCC prevent income discrimination while simultaneously accounting for economic feasibility?
This webinar discussion on the topic was recorded Feb. 13, 2023 with Rob McDowell (former commissioner of the FCC), Eric Fruits (ICLE), and Jessica Melugin (CEI), and was moderated by Kristian Stout (ICLE).
Due to technical difficulties with the video feed of this event, only the audio has been preserved.
ICLE Issue Brief Section 60506 of the Infrastructure Investment and Jobs Act (“IIJA”)—signed by President Joe Biden on Nov. 15, 2021—requires the Federal Communications Commission (“FCC”) to adopt final rules facilitating equal access to broadband Internet.
Section 60506 of the Infrastructure Investment and Jobs Act (“IIJA”)—signed by President Joe Biden on Nov. 15, 2021—requires the Federal Communications Commission (“FCC”) to adopt final rules facilitating equal access to broadband Internet. More specifically, the statutory text directs the FCC to prevent discrimination in broadband access based on income level, race, ethnicity, color, religion, or national origin, while also directing the Commission to consider issues of technical and economic feasibility.
Evaluating digital discrimination based on race, ethnicity, color, religion, or national origin should be relatively straightforward. But Section 60506 adds income level as a protected class. This presents what we call the “income conundrum.” It is virtually impossible to disentangle the factors affecting economic feasibility from factors correlated with membership in this particular protected class.
In this issue brief, we focus on the tension between the goals of preventing discrimination based on income level and ensuring that broadband-deployment projects are economically feasible, as well as the relevant distinctions between the application of intent-based or effects-based tests of discrimination. We find that some tests of so-called “digital discrimination” on the basis of income level—particularly in the context of effects-based “disparate impact” tests—can be misleading, and their application could be counterproductive.
First, it is important to note that Section 60506 refers to discrimination in the provision of broadband access and not to levels or rates of broadband adoption. While access is a necessary precondition to adopt broadband services, policymakers should be cautious not to infer that lack of adoption is necessarily caused by lack of access. Research finds that consumer income and the affordability of broadband services are key factors influencing whether those who enjoy broadband access will ultimately adopt broadband service. Other factors broadly correlated with income—such as age, educational attainment, and home-computer ownership and usage—similarly affect broadband-adoption decisions.
Thus, the use of income as a heuristic to determine whether providers’ deployment decisions are discriminatory is inherently fraught. Income level will influence consumer decisions to adopt broadband, which in turn affects providers’ ability to deploy to a given area. Therefore, while correlations between income and broadband adoption certainly can be found, research to date does not find evidence that—all else being equal—broadband providers intentionally discriminate against similarly situated groups on the basis of income, race, or other protected characteristics when it comes to broadband access.
Further, it is broadly agreed that Section 60506’s reference to “economic feasibility” refers to profitability—e.g., to whether broadband providers can earn a competitive return from their investments in deployment. Because broadband providers’ investment decisions are always constrained by their limited resources, they must prioritize deployment projects. As a consequence, they must decide not only whether a given project is likely to be profitable, but also how profitable it is likely to be relative to all other potential projects.
The expected profitability of any given broadband-deployment decision depends on a range of cost and demand factors. On the cost side, providers must consider a given territory’s population density and terrain, as well as such factors as state and local rules and taxes. On the demand side, the propensity of consumers who would be served by the deployment to both adopt and purchase broadband are key factors. Thus, the general willingness within a given territory to adopt broadband factors into deployment decisions. Where there is insufficient willingness to purchase broadband service, deployment may not be profitable.
Population density is generally acknowledged as the most important cost factor driving broadband-deployment decisions. The U.S. Government Accountability Office reports that population density is the cost factor most cited as “a critical determinant of companies’ deployment decisions,” a conclusion supported by academic research. Population density also figures into the demand side of the equation, as the GAO notes that low-density rural areas often struggle to “aggregate sufficient demand” to purchase broadband service. Because population density also can be correlated with demographic factors like income, race, age, educational attainment, and home-computer use, however, there may be a temptation for policymakers to infer digital discrimination in deployment decisions that were, in fact, based on population density or other permitted cost and demand considerations.
Further complicating the evaluation of digital-discrimination claims based on income is that, not only is income a key factor influencing whether a given consumer will adopt broadband, but it is also highly correlated with race, ethnicity, national origin, age, education level, and home-computer ownership and usage. Any rules promulgated under Section 60506 that fail to recognize this “income conundrum” will invite costly and time-consuming litigation based on allegations of digital discrimination either where it does not exist or where it is excused by economic-feasibility considerations. Moreover, this threat of litigation could hinder, rather than foster, further broadband deployment.
The U.S. Supreme Court has established tests governing when it is appropriate to conduct an effects-based “disparate impact” analysis in the context of discrimination law. Applying this rubric to Section 60506, we find that it lacks “results-oriented language.” The prohibition against digital discrimination “based on income level, race, ethnicity, color, religion, or national origin” would therefore apply only in cases of intentional discrimination in deployment decisions. Mere statistical correlation between deployment and protected characteristics is insufficient to support a finding of discrimination.
Finally, to close the so-called “digital divide,” it would be wise to avoid creating inefficient bureaucratic processes through which broadband providers would be forced to defend economically justified deployment decisions. For this reason, FCC rules should articulate a presumption of non-discrimination, in which allegations of digital discrimination must be demonstrated, rather than a presumption of discrimination that must be rebutted for each deployment decision. Direct user support—such as that offered by the Affordable Connectivity Program and programs operated under the Universal Service Fund—is a much more direct and economically efficient way to help close the “adoption gap” component of the digital divide.
As part of 2021’s Infrastructure Investment and Jobs Act (“IIJA”), Congress tasked the Federal Communications Commission (“FCC”) with investigating and remedying “digital discrimination” in broadband deployment.[1] The law directs the Commission to adopt rules that “facilitate equal access to broadband internet access service,” which is defined as “preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin.”[2] To this end, the Commission issued a Notice of Inquiry (“NOI”)[3] as a first step toward an ultimate rulemaking.[4]
The NOI states that “one of the Commission’s foremost goals is to ensure that every person in the United States has equal access to high-quality, affordable broadband internet access service… Every person across our Nation deserves—and must have—equal access to this crucial technology in the increasingly digital world; a person’s zip code should not determine their destiny.”[5]
But Section 60506 of the IIJA[6] creates a tension between the goals of encouraging greater broadband deployment and remedying alleged discrimination; indeed, some efforts to address the latter concern could result in slower investment in buildout. Importantly, the NOI does not focus on extending broadband deployment to the truly unserved—i.e., to those who lack any broadband Internet options at all.[7] In fact, the word “unserved” does not appear in the NOI at all, while the NOI instead declares that its target is the “underserved.”[8] But rather than define “underserved” consumers by reference to their relative inability to access broadband Internet service, the NOI defines the set as those who are members of categories that “have been historically underserved, marginalized, or adversely affected by persistent poverty or inequality” because of their income level, race, color, religion, or national origin.[9] The NOI therefore includes in the ranks of the “underserved” individuals who do have the ability to access broadband service, although potentially at slower speeds than some of their neighbors, or who have otherwise opted not to adopt broadband service.
Getting faster Internet to those who live where broadband service already exists, or assisting them in paying for access to the service that already exists, are fundamentally different problems than that faced by Americans who lack Internet access because they live in geographic areas without broadband infrastructure. Moreover, onerous or poorly implemented requirements that seek to curtail “digital discrimination” may be more likely to generally slow further broadband deployment than to speed it. An overly broad enforcement regime—one that sought to apply effects-based “disparate impact” tests or that operated from a presumption of discrimination—could force providers to constantly justify everything from decisions around actual deployment to decisions regarding whether to bid on particular deployment programs offered by governments.
Indeed, were the Commission to pursue economically ill-considered rules to curtail alleged “digital discrimination,” it could lead to intractable litigation. As we discuss below, the U.S. Supreme Court has in the recent past imposed limits on how “disparate impact” tests may be imposed by legislation.[10] These limits apply even to sectors with a demonstrated history of discriminatory redlining, such as housing.
It is undoubtedly important to examine patterns of deployment to discover how best to connect underserved communities. But if we are to overcome impediments that stand in the way of reaching every potential broadband consumer, it is essential that the FCC carefully consider how and why investment decisions are made in broadband markets.[11]
In short, we generally question the NOI’s framing of broadband-connectivity issues as being primarily or even substantially a matter of “discrimination.” Indeed, the IIJA’s project to eliminate “digital discrimination of access based on income level”[12] may not usefully forward efforts to connect the underserved at all. While there remains much work to be done to achieve the goal of universal connectivity, the FCC is already well-aware of the technical, economic, regulatory, and geographical issues that can impede deployment. The Commission should continue the important work it is already doing to address those issues and should ensure that its implementation of Section 60506 is focused on remedying cases where there is strong evidence of intentional discrimination against consumers based on protected characteristics.
In Part II, we analyze the relevant legal concerns for the Commission, should it seek to undertake a “disparate impact” rulemaking. In Part III, we discuss the theoretical and practical challenges that attend treating “income level” as a protected category. We address the economics of “access vs. adoption” and how, if not treated carefully, the issue would substantially skew any effects-based analysis of broadband-deployment patterns. We also discuss the economics of broadband deployment, including the factors that best explain deployment patterns. Part IV concludes with a brief set of policy recommendations.
Section 60506 requires that:
[T]he Commission shall adopt final rules to facilitate equal access to broadband internet access service, taking into account the issues of technical and economic feasibility presented by that objective, including… preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin; and… identifying necessary steps for the Commissions to take to eliminate discrimination… .[13]
Pursuant to this, the FCC asks in its NOI for:
… comment on how we should understand when digital discrimination is “based on” one of the listed characteristics. Does the term “based on” require discriminatory intent? If so, how would we determine the presence or absence of discriminatory intent? Would such an approach be practicably difficult to enforce? Alternatively or in addition, should we establish a “discriminatory effects” or disparate impact test? [14]
Advocates who support greater FCC authority to pursue alleged digital discrimination argue that the use of impermissible factors has contributed to underinvestment in minority communities and that “digital redlining has left unserved and underserved neighborhoods on the wrong side of the digital divide.”[15] Thus, a number of comments submitted to the record have called for the FCC to employ an effects-based “disparate impact” analysis under Section 60506.[16] As we discuss below, however, both the structure of Section 60506 and the Supreme Court’s established jurisprudence on disparate-impact analysis suggest that it would be much more reasonable for the Commission to construe Section 60506 as directing an analysis of intentional discrimination in deployment.
Statutes that define impermissible discrimination, such as the Civil Rights Act of 1964, can be analyzed legally either as addressed toward explicit discriminatory intent, referred to as “discriminatory treatment,” or toward behavior inferred from discriminatory effects, such as the “disparate impact” that the challenged behavior or policy has on a protected class.[17] A case involving discriminatory treatment is somewhat more straightforward,[18] insofar as it demands evidence demonstrating that decisions adversely affecting some protected class were made because of bias toward members of that class. In this context, where deployment decisions are made on the basis of discriminatory intent, the Commission is on much firmer legal ground to pursue them.
By contrast, were the Commission to adopt a “disparate impact” assessment as part of Section 60506, it would face an uphill legal climb. Among the primary justifications for disparate-impact analysis is to remedy those historical patterns of de jure segregation that left an indelible mark on minority communities.[19] While racial discrimination has not been purged from society, broadband only became prominent in the United States well after all forms of de jure segregation were made illegal, and after Congress and the courts had invested decades in rooting out impermissible de facto discrimination. Any policy intended to tackle disparate impact in broadband deployment needs to take this history into account.
Moreover, there is little evidence that IIJA’s drafters intended the law to be read so broadly. The legislative record on Section 60506 is exceedingly sparse, containing almost no discussion of the provision beyond assurances that “broadband ought to be available to all Americans,”[20] and also that the provision was not to be used as a basis for the “regulation of internet rates.”[21] Given that sparse textual basis, reading Section 60506 as granting the Commission expansive powers to serve as a broadband civil-rights czar could also run afoul of the “major questions” doctrine.[22] That doctrine requires Congress “to speak clearly if it wishes to assign to an agency decisions of vast ‘economic and political significance.’”[23]
More specifically, it does not appear that Section 60506 can be reasonably construed as authorizing disparate-impact analysis. While the Supreme Court continues to uphold disparate-impact analysis in the context of civil-rights law, it has recently imposed some important limitations. For example, in Texas Department of Housing & Community Affairs v. The Inclusive Communities Project, Inc., the Court upheld the disparate-impact doctrine, but noted that disparate-impact claims arise under statutes explicitly directed “to the consequences of an action rather than the actor’s intent.”[24] For example, in the Fair Housing Act, Congress made it unlawful:
To refuse to sell or rent after the making of a bona fide offer, or to refuse to negotiate for the sale or rental of, or otherwise make unavailable or deny, a dwelling to any person because of race, color, religion, sex, familial status, or national origin.[25] [Emphasis added.]
The Court noted that the presence of language like “otherwise make unavailable” is critical to construing a statute as demanding an effects-based analysis.[26] Such phrases, the Court found, “refer[] to the consequences of an action rather than the actor’s intent.”[27] Further, the structure of a statute’s language matters:
The relevant statutory phrases… play an identical role in the structure common to all three statutes: Located at the end of lengthy sentences that begin with prohibitions on disparate treatment, they serve as catchall phrases looking to consequences, not intent. And all [of these] statutes use the word “otherwise” to introduce the results-oriented phrase. “Otherwise” means “in a different way or manner,” thus signaling a shift in emphasis from an actor’s intent to the consequences of his actions.[28]
The Court reached this holding after reviewing a number of its previous decisions developing the distinction between effects-based and intent-based interpretations of a law. Particularly relevant here, in Univ. of Texas Sw. Med. Ctr. v. Nassar, the Court considered statutory language that prohibited discrimination “because of … age” and found that it only prevented intentional discrimination.[29] The Court also noted that, in previous cases, it had construed “because of” to mean “‘based on’ and that ‘based on’ indicates a but-for causal relationship.”[30]
Further, even where disparate analysis is appropriate, the Court held that it is significantly constrained by the need to ensure that the free-enterprise system continues to function:
[Supreme Court precedent] also teach[es] that disparate-impact liability must be limited so… regulated entities are able to make the practical business choices and profit-related decisions that sustain a vibrant and dynamic free-enterprise system. And before rejecting a business justification…a court must determine that a plaintiff has shown that there is “an available alternative … practice that has less disparate impact and serves the [entity’s] legitimate needs.”[31] [Emphasis added.]
In practice, this means that lower courts are free to probe a disparate-impact claim rigorously in order to avoid such claims becoming a club to wield against regulated entities.[32] It also suggests that, in a context such as Section 60506’s proscriptions against digital discrimination, they may not be so broad as to render it impossible for broadband providers to make effective decisions about which deployment projects are economically feasible.
Thus, as Section 60506 was drafted without “results-oriented language”[33] and instead frames the prohibition against digital discrimination as “based on income level, race, ethnicity, color, religion, or national origin,”[34] this would put the rule squarely within the realm of prohibitions on intentional discrimination.[35] That is, to be discriminatory, the decision to deploy or not to deploy must have been intentionally made because of the protected characteristic. Mere statistical correlation between deployment and protected characteristics is insufficient.
In enacting the IIJA, Congress was undoubtedly aware of the Court’s history with disparate-impact analysis. Had it chosen to do so, it could have made the requirements of Section 60506 align with the requirements of that precedent. But it chose not to do so, thereby reinforcing that it intended the FCC to have some discretion, but to err on the side caution when declaring practices an impermissible form of discrimination.
This is not to say that Section 60506 has no effect. As mentioned above, it can be reasonably read to encompass intentional discrimination, given appropriate evidence. Further, the means available to the FCC to remedy undesirable patterns of deployment are manifold. The only options rendered off the table would be requirements that are technologically or economically infeasible, such as an unfunded mandate that providers deploy at maximum speeds to all households simultaneously. As discussed further below, the FCC also has broad authority over various funding programs that it could use to generate both user subsidies and provider incentives to deployment, which could go a long way toward closing the digital divide.
The expected profitability of any given broadband-deployment decision will hinge on a range of cost and demand factors. On the cost side, providers must consider a given territory’s population density and terrain, as well as such factors as state and local rules and taxes. On the demand side, the propensity of consumers who would be served by the deployment to both adopt and purchase broadband are key factors. Thus, the general willingness within a given territory to adopt broadband weighs heavily in providers’ deployment decisions. Where there is insufficient willingness to purchase broadband service, deployment may not be profitable.
As we explain below, economic feasibility is essentially synonymous with return on investment. While income may be correlated with some factors that drive decisions to deploy, animus against potential customers with protected characteristics is almost certainly not an important factor in deployment decisions. Thus, even if the Commission engages in an intent-based analysis under Section 60506, there are many economic-feasibility factors it needs to take into consideration, which we set forth below.
The text of Section 60506 refers to discrimination in the provision of broadband access and not to levels or rates of broadband adoption. While access is a necessary precondition to adopt broadband services, policymakers should be cautious not to infer that lack of adoption is necessarily caused by lack of access. Research finds that consumer income and the affordability of broadband services are key factors influencing whether those who enjoy broadband access will ultimately adopt broadband service. Other factors that may be broadly correlated with income—such as age, educational attainment, and home-computer ownership and usage—similarly influence broadband-adoption decisions. Thus, comparing relative levels of income in territories that are, or are not, chosen for broadband deployment is a poor heuristic to determine whether providers’ deployment decisions are discriminatory. Local income will influence consumer decisions to adopt broadband, which in turn affects whether it will be economically feasible for providers’ to deploy to a given area.
The Commission therefore should not summarily conclude that deployment patterns correlated with income are a form of impermissible discrimination. As explained above, in order to run afoul of Section 60506, the Commission should insist that challenged deployment decisions are directly attributable to an intentional choice not to serve consumers who are members of a protected category. To apply analysis that ignores intent and instead looks at whether members of such categories are impacted disparately by deployment decisions would threaten to create an unmanageable and open-ended legal standard that ultimately slows deployment overall.
Broadband access alone also may not be sufficient to drive greater rates of broadband adoption. For example, Brian Whitacre and his co-authors found that, while the reduced levels of broadband access in rural areas explained 38% of the rural-urban broadband-adoption gap in 2011, differences in other general characteristics—such as income and education—explain “roughly half of the gap.”[36] A report by the U.S. Government Accountability Office concluded that “even where broadband service is available … an adoption gap may persist due to the affordability of broadband and lack of digital skills.”[37] The GAO report notes that nearly one-third of those with access to broadband do not subscribe to it and that “lower-income households have lower rates of home broadband subscriptions.”[38]
The price of broadband services is another significant factor that affects adoption. A National Telecommunications and Information Administration survey of Internet use identified “affordability as a driving factor around why some households continue to remain offline, confirming that cost of service is an essential part of increasing Internet adoption.”[39] The survey reported that the average price that offline households wanted to pay for Internet access was approximately $10 per month, and about 75% of households gave $0 or “none” as their answer. Kenneth Flamm and Anindya Chaudhuri’s empirical research finds that broadband price is a “statistically significant driver” of broadband demand.[40] They conclude that broadband-price declines in the early 2000s explain “some portion” of increased broadband adoption.[41] Victor Glass and Stela Stefanova’s empirical study indicates that higher prices “depress” demand for broadband.[42]
Price sensitivity is closely tied to income. Christopher Reddick and his co-authors concluded that “[i]ncome is a major factor that is likely to influence broadband adoption especially where technology is available.”[43] Glass and Stefanova find broadband service to be a normal good, which means that increased incomes are associated with increased broadband adoption—a finding consistent with previous research.[44] Similarly, the GAO reports: “A recent nationally representative survey by Consumer Reports reported that nearly a third of respondents who lack a broadband subscription said it was because it costs too much, while about a quarter of respondents who do have broadband said they find it difficult to afford.”[45] Alison Powell and her co-authors report that a significant number of low-income Americans engage in a cycle of broadband adoption and “un-adoption,” in which they adopt broadband and then drop it for financial or other reasons, and then re-adopt when circumstances improve for them.[46]
In addition to price and income guiding a household’s broadband-adoption decisions, other factors are also relevant. Tonny Oyana’s empirical research concludes that income, the share of a population who are senior citizens, and the share with some college education are the “three most important demand-side factors” affecting both access and adoption.[47] The GAO reports that “[o]ther barriers include lack of digital skills,” citing a 2016 Pew Research Center report finding that “about half of American adults were hesitant when it comes to new technologies and building their digital skills.”[48]
It can be argued that the gap between broadband access and adoption may present the real digital divide. That is, large numbers of American who have access to broadband do not adopt it, and some who do may “un-adopt” it. While income is a key factor in a household’s adoption choice, it is only one of several important factors, which also include age, educational attainment, and home-computer ownership and usage—each of which is, in turn, also correlated with income. As discussed below, deployment decisions are based on many factors, including a territory’s projected broadband adoption. If firms do not expect sufficient levels of adoption, then deployment may be unprofitable. It would be a mistake to infer that income discrimination in deployment causes low rates of broadband adoption in low-income communities when low income itself—and other factors correlated with income—may be a primary cause of low rates of broadband adoption.
Section 60506 requires the Commission to take account of “issues of technical and economic feasibility.” There is broad consensus that “economic feasibility” here refers to profitability.[49] More precisely, a project is economically feasible if it provides an adequate return on investment (ROI). Like all firms, broadband providers have limited resources with which to make their investments. While profitability is a necessary precondition for investment, not all profitable investments can be undertaken. Among the universe of potentially profitable projects, firms are likely to give priority to those that promise greater returns on investment relative to those with lower ROI. Thus, any evaluation of potential digital discrimination must examine not only whether a given deployment is likely to be profitable, but also how its expected returns compare to other investment opportunities.
Returns on investment in broadband depend on several factors. As noted earlier, population density, terrain, regulations, and taxes are all important cost factors, while a given consumer population’s willingness to adopt and pay for broadband are key demand-related factors.
In addition to these cost and demand factors, the timing of both investment and adoption affect the ROI of a deployment investment. Consider two hypothetical investments, shown in Table I below. Both Deployment A and Deployment B require the same initial investment of $100 million and both ultimately generate the same income of $44 million a year. However, Deployment B has a slower adoption rate. Not only does Deployment B generate lower income over the hypothetical 20-year life of the investment, but its ROI is less than half that of deployment A. While both deployments are profitable and both eventually generate the same annual income, relative to deployment A, deployment B is unprofitable.
Table 1: How Timing Affects ROI in Hypothetical Deployments A and B
Source: Authors
Because the timing of investment returns is critical in a firm’s deployment decisions, local regulations that slow broadband buildout can have significant effects on a deployment investment’s ROI.
By far, population density is widely acknowledged to be the most important cost factor driving broadband-deployment decisions. For example, the GAO reports that population density is the “most frequently cited cost factor” and “a critical determinant of companies’ deployment decisions.”[50]
Academic research supports the GAO’s conclusions. For example, Brian Whitacre and Roberto Gallardo describe population density as one of “the main determinants of Internet availability.”[51] Similarly, Oyana—citing earlier research—concludes that “[l]imited broadband access is common in rural communities because of geographic remoteness and low population density.”[52] Juan Schneir and Yupeng Xiong identify that firms are more likely to deploy broadband in urban and suburban areas, rather than rural areas, due to both cost and demand factors. They note this is “because of the high density of users willing to pay for high-speed broadband services and the relatively low network rollout costs in urban and suburban areas.”[53] Consistent with Schneir & Xiong’s conclusion, the GAO also finds that population density is an important factor on the demand side of deployment decisions. In particular, the GAO concludes that it is more difficult to “aggregate sufficient demand” to pay for broadband service in low-density rural areas.[54]
Several other factors also affect the profitability of broadband-deployment investments. The GAO identifies terrain as an important factor, concluding that “it is more costly to serve areas with low population density and rugged terrain with terrestrial facilities than it is to serve areas that are densely populated and have flat terrain.”[55] The GAO also reports that the cost of “backhaul” can affect broadband deployment to rural areas. “Backhaul” is the cost of routing Internet traffic from rural areas to larger cities in order to connect to a major Internet backbone provider.[56] Whitacre & Gallardo find that state-level broadband-funding programs are associated with a modest increase (1.2–2.0 percentage points) in broadband availability.[57] On the demand side, the GAO reports that “demand will be greater in areas where potential customers are familiar with computers and broadband.”[58]
Population density is also correlated to varying degrees with such demographic factors as income, race, age, educational attainment, and home-computer use. Thus, one should be cautious about inferring digital discrimination based on such factors from deployment decisions that are likely to be based on population density.
As noted above, the evaluation of digital-discrimination claims based on income level is complicated by the fact that income is a key factor—and perhaps the key factor—affecting broadband adoption. Moreover, it is also correlated with race, ethnicity, national origin, age, education level, and home-computer ownership and usage. Adoption of Section 60506 rules that do not recognize this “income conundrum” will invite costly and time-consuming disparate-impact litigation alleging digital discrimination, both where no such discrimination exists and where it is excused by economic-feasibility considerations. The threat of litigation from injudicious rulemaking also may hinder, rather than foster, further broadband deployment.
Randolph Beard and George Ford report:[59]
Survey evidence and empirical research on broadband adoption show that income has a demonstrable effect on demand. Also, empirical research and survey evidence show that some racial minorities—in particular, Hispanic, Black, and Native Americans—are less likely to adopt fixed-service broadband services in the home. Moreover, income is correlated with many factors that affect demand including, among other things, employment, education levels, and housing stability, which makes the determination of “income discrimination” extremely difficult since it is the discriminatory treatment of low-income households, and not these other correlated factors, that is mentioned in the statute. Minority population shares and income levels are also correlated with population density, which affects the cost of network deployment and upgrades. Quantifying “digital discrimination” is, therefore, an extremely challenging endeavor.
In addition to the factors identified by Beard & Ford, income is correlated with several factors associated with broadband adoption. For example, Pew reports that, among lower-income adults:[60]
Some argue that broadband has become more of a necessity over time,[61] akin to utilities for home heating, cooling, and cooking.[62] According to Ryan Finnigan and Kelsey Meagher, low-income households spend approximately half their monthly income on housing and another 10-20% on utilities.[63] The incidence of utility disconnections can provide an indication of ability or willingness to pay for broadband. If a household is more likely to experience a utility disconnection, the household is likely to have a lower ability to pay for a broadband connection. In this sense, broadband disconnections for non-payment can be seen as an extreme form of “un-adoption,” as described by Powell, et al. Diana Hernández and Jennifer Laird’s empirical research on utility disconnections finds that disconnections are correlated with income, education, and home-ownership status, as well as race:[64]
Disconnections are disproportionately high among households with low incomes, a Black head of household, a head who does not have a high school diploma, mobile homes, older homes, poorly insulated homes, rentals, rural homes, and homes in the Northeast. Among those households with an income less than $20,000, nearly 8% have experienced a disconnection—a rate about 2.5 times as high as those with incomes between $20,000 and $59,999.
If a broadband provider determines a given territory is likely to have a low adoption rate or a high “un-adoption” rate, it is likely to conclude that deployment to that locality is less economically feasible than other territories. Empirical evidence suggests that race and income are among the factors associated with broadband adoption and un-adoption. Other factors like population density, education, age, familiarity with computers, and computer ownership are also known to be correlated with race and income and, indeed, race and income are widely known to be correlated with each other. For example, Beard & Ford show that U.S. Census blocks with higher population densities are associated with a higher share of minority residents and lower average incomes. They also report that blocks with a higher share of minority residents have lower fixed-broadband adoption rates and a higher share of mobile-only broadband use.[65]
Beard & Ford attempt to statistically untangle the income conundrum.[66] Their empirical model includes four demand factors for each Census block: fixed-broadband adoption rate, mobile-broadband adoption rate, the share of persons with a tertiary education, and the share of homes with a computer. The model also includes five cost factors: population density, the share of rural blocks within the Census-block group, and three cost categories from CostQuest. Using this information, they evaluate: (1) fiber deployment by race, (2) fiber deployment by income level, (3) download speeds by race, and (4) download speeds by income level. Beard & Ford conclude from their statistical analysis that there is “no meaningful evidence of digital discrimination in either race or income for fiber deployments or for download speeds.” But Beard & Ford is just a single study looking at the possibility of nationwide discrimination. While their approach is rigorous and provides compelling results, it would be challenging to “scale down” the approach to evaluate digital discrimination by firms or locality.
Consider a hypothetical FCC rule mandating that broadband providers must completely exclude income level, race, ethnicity, color, religion, and national origin from their deployment calculus. Instead, firms must rely on their estimates of deployment costs—including population density, terrain, local regulations, and local taxes—and non-protected demand factors, such as population density, education, age, utility-disconnection rates, and rates of computer ownership and usage. This would be one plausible implementation of an intent-based test of digital discrimination under Section 60506. So long as providers’ deployment decisions are not made “because of” any of the protected characteristics, then they would not be found to be practicing digital discrimination. Whether these other factors—education, age, population density, computer usage—are sufficient on their own to determine the economic feasibility of a deployment project is a separate empirical question beyond the scope of this brief.
But because each of these other factors are correlated with income level—and with other protected characteristics—applying an effects-based statistical analysis is likely to produce a false positive concluding the presence of digital discrimination, even when there was an explicit effort to avoid such discrimination. This is a version of Nobel laureate Ronald Coase’s well-known quote: “If you torture the data long enough, it will confess.”[67]
The economics discussed above underscore that the FCC must be particularly cautious when promulgating rules under Section 60506. In particular, the Commission should adopt an intent-based discriminatory-treatment standard, rather than one that opens the doors to disparate-impact claims. The high risk of false positives under a disparate-impact standard would stifle broadband deployment through additional costs, delays, and risk of litigation. Similarly, FCC rules should articulate a presumption of non-discrimination in which allegations of digital discrimination must be demonstrated, rather than a presumption of discrimination that must be rebutted for each deployment decision. Otherwise, given the economic realities discussed above, there is an unacceptably high chance that every one of a provider’s decisions will be subject to challenge, wasting the resources of both the Commission and the providers.
The largest takeaway is that adoption matters quite a bit. Indeed, one of the biggest issues affecting economic feasibility is consumers’ willingness to pay. Moreover, Congress has recognized this reality in its recent legislation. The IIJA’s Broadband Equity and Access program provides more than $42 billion in grants to state programs to help them support providers and give assistance directly to users.[68] The Affordable Connectivity Program provided another $14 billion in funding to help users pay for devices and broadband connections.[69]
[1] H.R. 3684, 117th Cong. (2021).
[2] 47 U.S.C. § 1754(b).
[3] Notice of Inquiry, In the Matter of Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (Feb. 23, 2022), at para. 1 [hereinafter “NOI”].
[4] This issue brief supplements and extends the comments we submitted to the Commission as part of the NOI: Comments in the Matter of Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69, International Center for Law & Economics (2022), accessed at: https://laweconcenter.org/resource/icle-comments-to-the-fcc-on-prevention-and-elimination-of-digital-discrimination.
[5] NOI, supra note 4, at para. 1.
[6] 47 U.S.C. § 1754 [hereinafter “Section 60506”]
[7] Currently defined by the FCC as 25/3 Mbps for terrestrial fixed broadband and 10/1 for mobile broadband. See Fourteenth Broadband Deployment Report, In the Matter of Inquiry Concerning Deployment of Advanced Telecommunications Capability to All Americans in a Reasonable and Timely Fashion, GN Docket No. 20-269 (Jan. 19, 2021), at para. 12 (defining terrestrial fixed broadband), para. 15 (defining mobile broadband) [hereinafter “Fourteenth Broadband Deployment Report”].
[8] NOI, supra note 4, at para. 2 (quoting 47 U.S.C. § 1754(b)(1)).
[9] Id. at para. 3, n. 5; id. at para. 40 (both quoting Executive Order 13985).
[10] Texas Dept. of Housing & Community Affairs v. The Inclusive Communities Project, 576 U.S. 519, (2015).
[11] See, Geoffrey A. Manne, Kristian Stout, & Ben Sperry, A Dynamic Analysis of Broadband Competition: What Concentration Numbers Fail to Capture, ICLE White Paper (June 2021), available at https://laweconcenter.org/wp-content/uploads/2021/06/A-Dynamic-Analysis-of-Broadband-Competition.pdf [hereinafter “ICLE Broadband Competition Paper”].
[12] NOI, supra note 4, at para. 2.
[13] Section 60506, supra note 6, at (b)(1)-(b)(2).
[14] NOI, supra note 4, at para. 22.
[15] Comments of the Joint Advocates on Digital Discrimination, GN Docket No. 22-69 (May 16, 2022).
[16] See Comments of Public Knowledge, GN Docket No. 22-69 (May 16, 2022), pp 7-10; see also, Comments of the Multicultural Media Telecom and Internet Council, GN Docket No. 22-69 (May 16, 2022); Reply Comments of the National Digital Inclusion Alliance, GN Docket No. 22-69 (June 30, 2022).
[17] Ricci v. DeStefano, 557 U.S. 557, 577, (2009).
[18] See, id. (Intentional discrimination cases “present the most easily understood type of discrimination…[that] occur[s] where [a party[ has treated [a] particular person less favorably than others because of a protected trait.”).
[19] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 528–29.
[20] 167 Cong. Rec. 6046 (2021).
[21] 167 Cong. Rec. 6053 (2021).
[22] See, e.g., West Virginia v. EPA, 142 S. Ct. 420, (2021).
[23] Util. Air Regulatory Group v. EPA, 573 U.S. 302, (2014) quoting FDA v. Brown & Williamson Tobacco Corp., 529 U.S. 120, (1999); see also, West Virginia v. EPA, 142 S. Ct. 420.
[24] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 534.
[25] 42 U.S.C. § 3604(a) (emphasis added).
[26] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 534.
[28] Id. at 534-35.
[29] Univ. of Texas Southwestern Med. Ctr. v. Nassar, 570 U.S. 338, 350, (2013) (citing Gross v. FBL Fin. Servs., Inc., 557 U.S. 167, 176, (2009)).
[30] Id. (citing Safeco Ins. Co. of America v. Burr, 551 U.S. 47, 63–64; n. 14, (2007)).
[31] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 533 (emphasis added).
[32] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 521–22 (“Courts should avoid interpreting disparate-impact liability to be so expansive as to inject racial considerations into every housing decision. These limitations are also necessary to protect defendants against abusive disparate-impact claims.”).
[33] Id.
[34] Section 60506, supra note 6 (emphasis added).
[35] See, e.g., Ricci, 557 U.S. 557.
[36] Brian Whitacre, Sharon Strover & Roberto Gallardo, How Much Does Broadband Infrastructure Matter? Decomposing the Metro–Non-Metro Adoption Gap with the Help of the National Broadband Map, 32 Gov’t Info. Q. 261 (2015).
[37] U.S. Gov’t Accountability Off., GAO-22-104611, Broadband: National Strategy Needed to Guide Federal Efforts to Reduce Digital Divide (May 31, 2022) [hereinafter “GAO-22-104611”].
[38] Id. See also, How Do Speed, Infrastructure, Access, and Adoption Inform Broadband Policy?, Pew Research Center (Jul. 7, 2022), https://www.pewtrusts.org/en/research-and-analysis/fact-sheets/2022/07/how-do-speed-infrastructure-access-and-adoption-inform-broadband-policy (“nearly 1 in 4 Americans do not subscribe to a home broadband connection, even where one is available”).
[39] Michelle Cao & Rafi Goldberg, New Analysis Shows Offline Households Are Willing to Pay $10-a-Month on Average for Home Internet Service, Though Three in Four Say Any Cost is Too Much, National Telecommunications and Information Administration (Oct. 6, 2022), https://www.ntia.doc.gov/blog/2022/new-analysis-shows-offline-households-are-willing-pay-10-month-average-home-internet.
[40] Kenneth Flamm & Anindya Chaudhuri, An Analysis of the Determinants of Broadband Access, 31 Telecomm. Pol’y. 312 (2007).
[41] Id.
[42] Victor Glass & Stela K. Stefanova, An Empirical Study of Broadband Diffusion in Rural America, 38 J. Reg. Econ. 70 (Jun. 2010).
[43] Christopher G. Reddick, Roger Enriquez, Richard J. Harris & Bonita Sharma, Determinants of Broadband Access and Affordability: An Analysis of a Community Survey on the Digital Divide, 106 Cities 102904 (2020).
[44] Victor Glass & Stela K. Stefanova, supra, note 43 at 70.
[45] GAO-22-104611, supra note 37.
[46] Alison Powell, Amelia Bryne & Dharma Dailey, The Essential Internet: Digital Exclusion in Low-Income American Communities, 2 Pol’y & Internet 161 (2010).
[47] Tonny J. Oyana, Exploring Geographic Disparities in Broadband Access and Use in Rural Southern Illinois: Who’s Being Left Behind?, 28 Gov’t. Info. Q. 252 (2011).
[48] GAO-22-104611, supra note 37.
[49] Notice of Inquiry, Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (2022) (“If underlying cost or geographic hurdles exist in conjunction with demand in an area that makes it unprofitable, how should the Commission address such a situation?”).
[50] U.S. Gov’t Accountability Off., GAO-06-426, Telecommunications: Broadband Deployment Is Extensive Throughout the United States, but It Is Difficult to Assess the Extent of Deployment Gaps in Rural Areas (May 2006), https://www.gao.gov/assets/gao-06-426.pdf. [hereinafter “GAO-06-426”].
[51] Brian Whitacre & Roberto Gallardo, State Broadband Policy: Impacts on Availability, 44 Telecomm. Pol’y. 102025 (2020).
[52] Tonny J. Oyana, supra note 47 at 252.
[53] Juan Rendon Schneir & Yupeng Xiong, A Cost Study of Fixed Broadband Access Networks for Rural Areas, 40 Telecomm. Pol’y. 755 (2016).
[54] GAO-06-426, supra note 50.
[55] Id.
[56] Id.
[57] Brian Whitacre & Roberto Gallardo, State Broadband Policy: Impacts on Availability, 44 Telecomm. Pol’y. 102025 (Oct. 2020).
[58] GAO-06-426, supra note 50.
[59] T. Randolph Beard & George S. Ford, Digital Discrimination: Fiber Availability and Speeds, by Race and Income, Phoenix Ctr. for Advanced Legal & Econ. Pol’y Stud., Phoenix Ctr. Pol’y Paper No. 58 (September 2022).
[60] Emily A. Vogels, State Broadband Policy: Impacts on Availability, Pew Research Center (Jun. 22, 2021), https://www.pewresearch.org/fact-tank/2021/06/22/digital-divide-persists-even-as-americans-with-lower-incomes-make-gains-in-tech-adoption.
[61] Victor Glass & Stela K. Stefanova, An Empirical Study of Broadband Diffusion in Rural America, 38 J. Reg. Econ. 70 (2010) (“The low price elasticity found in the 2009 study indicates that broadband access has become more of a necessity than it used to be in 2005.”).
[62] Meredith Whipple & Aden Hizkias, We Already Knew Broadband Should Be a Public Utility. The Pandemic Made It Obvious, Public Knowledge (Mar. 15, 2021), https://publicknowledge.org/we-already-knew-broadband-should-be-a-public-utility-the-pandemic-made-it-obvious.
[63] Ryan Finnigan & Kelsey D. Meagher, Past Due: Combinations of Utility and Housing Hardship in the United States, 62 Sociological Persp. 91 (2018).
[64] Diana Hernández & Jennifer Laird, Surviving a Shut-Off: U.S. Households at Greatest Risk of Utility Disconnections and How They Cope, 66 Am. Behav. Sci. 856 (2022).
[65] T. Randolph Beard & George S. Ford, Digital Discrimination: Fiber Availability and Speeds, by Race and Income, Phoenix Ctr. for Advanced Legal & Econ. Pol’y Stud., Phoenix Ctr. Pol’y Paper No. 58 (2022).
[66] Id.
[67] Garson O’Toole, If You Torture the Data Long Enough, It Will Confess, Quote Investigator (Jan. 18, 2021), https://quoteinvestigator.com/2021/01/18/confess.
[68] Broadband Equity, Access, and Deployment Program, BroadbandUSA, https://broadbandusa.ntia.doc.gov/resources/grant-programs/broadband-equity-access-and-deployment-bead-program (last visited Oct. 23, 2022).
[69] Affordable Connectivity Program, Federal Communications Commission, https://www.fcc.gov/acp (last visited Oct. 23, 2022).
Regulatory Comments We wish to highlight two primary concerns: that decisions by pole owners to delay maintenance and shift costs onto attachers are a significant impediment to deployment, and that there is a pressing need for the Commission to create an expedited process to resolve these disputes.
Thank you for the opportunity to comment on this Further Notice of Proposed Rulemaking (FNPRM) in the Matter of Accelerating Wireline Broadband Deployment by Removing Barriers to Infrastructure Investment. It is a broad aim of the U.S. government to extend broadband connectivity to all Americans.[1] However, a complicating factor in this regard is that Internet service providers (ISPs) need frequent access to utility poles to attach their equipment, which creates a point of friction that adds cost and slows deployment timetables.
These barriers to deployment can take many forms, some arising in areas over which the Commission does not have jurisdiction.[2] But with respect to those matters over which it does have jurisdiction, the Commission asks:
In this Second Further Notice, we seek comment on ways to eliminate or expedite resolution of pole replacement disputes by establishing clear standards for when and how utilities and attachers must share in the costs of a pole replacement that is precipitated by a new attachment request.[3]
Utility-pole attachments represent a critical component of deployment costs. Current estimates suggest that, in rural areas, as much as 25% of the cost of broadband deployment can be attributed to pole-replacement and upgrade issues.[4] We wish to highlight two primary concerns: that decisions by pole owners to delay maintenance and shift costs onto attachers are a significant impediment to deployment, and that there is a pressing need for the Commission to create an expedited process to resolve these disputes. We have attached to these brief comments a paper published by the International Center for Law & Economics and that expands on these and related issues in greater depth.
Read the full comments here.
[1] Infrastructure Investment and Jobs Act, H.R. 3684, 117th Cong. (2021).
[2] The FCC lacks jurisdiction over poles owned by electrical cooperatives or municipal governments, and 28 states have not verified that they have regulatory authority over pole attachments. See Michelle Connolly, The Economic Impact of Section 224 Exemption of Municipal and Cooperative Poles (Jul. 12, 2019), available at https://www.ncta.com/sites/default/files/2019-07/NCTA%20Muni%20and%20Coop%20Poles%20Connolly%20Paper%20Ex%20Parte%20Filing%207-22-19.pdf. While not the subject of this proceeding, it should be noted that excessive attachment fees from these sources impede broadband build-out by slowing growth and raising the expense to consumers of broadband access. For example, pass-through literature finds that 56% to 70% of wholesale price increases are passed on to consumers while 5.0% to 6.4% of increased commodity prices are passed on to consumers. See Cost Pass-Through: Theory, Measurement, and Potential Policy Implications: A Report Prepared for the Office of Fair Trading, RBB Economics, (February 2014), at 156-57, available at https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/320912/Cost_Pass-Through_Report.pdf. We believe the Commission should engage on this issue as an expert adviser to state authorities that may have influence over these deployment barriers.
[3] Accelerating Wireline Broadband Deployment by Removing Barriers to Infrastructure Investment, FCC 22-20 (Mar. 16, 2022).
[4] Petition of NCTA for Expedited Declaratory Ruling, In the Matter of Accelerating Wireline Broadband Deployment by Removing Barriers to Infrastructure Investment, WC Docket No. 17-84 (Jul. 16, 2020), at 5-9, available at https://www.ncta.com/sites/default/files/2020-07/071620_17-84_NCTA_Petition_for_Declaratory_Ruling.pdf.
ICLE Issue Brief President Joe Biden in November 2021 signed the Infrastructure Investment and Jobs Act. Among other provisions, the law allocated $42.45 billion toward last-mile broadband development, . . .
President Joe Biden in November 2021 signed the Infrastructure Investment and Jobs Act. Among other provisions, the law allocated $42.45 billion toward last-mile broadband development, with the National Telecommunications and Information Administration (NTIA) directed to administer those funds through the newly created Broadband Equity, Access & Deployment (BEAD) program. The BEAD program will provide broadband grants to states, who may then subgrant the money to public and private telecommunications providers.
Serious analysis of the proper roles for government and the private sector in reaching the unserved is a necessary prerequisite for successful rollout of broadband-infrastructure spending. Public investment in broadband infrastructure should focus on the cost-effective provision of Internet access to those who don’t have it, rather than subsidizing competition in areas that already do.
Read the full checklist here.
