BTOP’s Fiber Investment, Social Value & the Special Access Market

During the past few days I’ve been: 1) reviewing the BTOP program evaluation study’s final report prepared in 2014 by ASR Analytics and; 2) doing some homework aimed at better understanding issues related to the FCC’s pending special access study and proceeding. The former relates to a pending Quello Center research project, while the latter was prompted by release of a paper written by Mark Cooper, Director of Research at the Consumer Federation of America (CFA). Cooper presented the paper, entitled “The Special Problem of Special Access: Consumer Overcharges and Telephone Company Excess Profits,” at an April 5 event sponsored by the New America Foundation.

In his paper, Cooper made a theoretical and empirical case that “large incumbent telephone companies have engaged in abusive pricing practices” for special access services that have resulted in economic harm exceeding $150 billion over the past five years:

Today, special access is a $40 billion per year business, which works out to about $300 per household, which is almost equal to what they spend on landline telephone service…

This paper shows that about half of the total bill paid to the large incumbent local phone companies for special access service, who control between five-sixths and nine-tenths of the special access market, is the result of the abuse of market power – i.e. setting prices far above costs to earn excess profits…

Because of the importance of special access as an intermediate good, the $20 billion in annual overcharges suppresses a significant amount of economic activity, reducing economic output by at least another $20 billion. The magnitude of the harm has been growing steadily, so that the cumulative value of economic losses over the past five years is in excess of $150 billion.

While there’s much to consider and debate in Cooper’s analysis and, more broadly, related to the FCC’s pending special access proceeding (something that may be done in the future by me and/or MSU colleagues on this blog), for now I’m only going to use Cooper’s general argument as a jumping off point to consider a few metrics that struck me in ASR’s BTOP evaluation study.

As explained in the introduction to its final report, published in September 2014, ASR Analytics summarized the scope of and general methodologies used in its study:

The scope of work includes an assessment of the benefits that BTOP grants are having on broadband availability and adoption, and in achieving social and economic benefits in areas served by the grantees…

ASR developed its conclusions based on a mixed- methods approach that includes comparative case studies of BTOP-funded projects, input-output analysis of the short-term economic impacts of all BTOP budgetary spending, and a matched-pairs analysis of the counties served by infrastructure grants in the evaluation study sample.

The ASR study had lots of ground to cover and, in my view, did an admirable job of using mixed methods to leverage available qualitative and quantitative data to evaluate a large number of projects spanning three major categories: Comprehensive Community Infrastructure (CCI), sometimes referred to as “Middle Mile Fiber” projects, Public Computer Centers (PCCs) and Sustainable Broadband Adoption (SBA) projects. And, importantly, as ASR noted in the introduction to its final report, it was “required to provide NTIA with all data that created a foundation for the [report’s] analysis and conclusions, as well as all data that could be utilized by future researchers.”

In this blog post I’m going to focus on a few elements of ASR’s analysis of the impacts of CCI projects, whose purpose and nature are, in my view, closely tied to the issues surrounding the special access market. This is because most if not all CCI projects involved construction of fiber networks providing high-capacity, high-reliability connectivity to “community anchor institutions” (CAIs), including schools, libraries and government and healthcare facilities, as well as providing non-discriminatory open-access backbone connections to wholesale and last mile service providers.

As I see it, the BTOP CCI projects represent a significant wave of new players entering the special access space, the bulk of whose construction costs (up to 80%) were covered by federal grants, and whose terms of service are required to meet certain nondiscriminatory “open access” requirements. And, conveniently and importantly, thanks to NTIA and ASR, these projects have been the subject of careful study from their inception.

Though there’s plenty we can learn from the ASR study of CCIs, I’m going to focus here on some high-level numbers that the study gathered, estimated and extrapolated.

According to Table 7 on pg. 15 of ASR’s final report, the total amount (including both federal grants and matching funds) budgeted for 109 CCI projects was $3.9 billion. The table also indicates that, at the time the study was done, these projects had connected 21,240 CAIs, at a budgeted cost of $184,141 per CAI. Assuming federal grants paid for 80% of this total cost, the average federal grant amount per CAI would be in the neighborhood of $147,300.

Table 13 on pg. 34 of the report shows the changes in subscription speeds and pricing experienced by the 86 CAI locations providing this information to ASR. The table shows very large increases in speed and, depending on the category of CAI, dramatic 94-96% average reductions in per-Mbps pricing. Table 14 on pg. 36 uses these reported changes in speed and price to extrapolate CAI cost savings from switching to CCI-provided fiber connections. Averaged across all CAI categories, the per-CAI annual savings amounted to $236,151.

So, in a single year, the average CAI saved well more ($236,151) in operating costs than the total capital cost ($184,141) required to connect it to a CCI fiber network.

These direct cost savings to CAIs were only part of the impacts considered by ASR. It also used previously developed models to estimate other economic benefits, as explained on pg. 33 of its final report:

Increased economic output: The largest long-term social or economic impact due to BTOP infrastructure spending is the yearly increase in GDP in the areas served by the new broadband infrastructure. ASR used two studies, Czernich et al. (2011) and LECG Ltd. (2009), to extrapolate the increase in economic output that could be expected in counties receiving BTOP- funded infrastructure. For the base case of a 2.0 percent increase in broadband availability, BTOP infrastructure spending could be expected to yield $5.7 to $21.0 billion in increased output annually using results from Czernich et al. (2011) and LECG Ltd. (2009) as the bases for extrapolation, respectively.

Long-term increased levels of employment: Kolko (2010) and Gillett et al. (2006) provide a basis for estimating the long-term increase in employment due to BTOP-funded infrastructure spending. Based on Kolko’s estimates, the additional broadband infrastructure provided by BTOP could be expected to create more than 22,000 long-term jobs and generate $1.1 billion in additional household income each year. Results from Gillett et al. (2006) suggest at least 6,900 long-term jobs could be created in the year following the construction of BTOP infrastructure, and potentially each year for at least the next four years due to increasing employment growth in areas with new broadband availability. These employment increases would result in a $328 million increase in household income for each year employment increases by the estimated amount in newly served areas.

Value to new subscribers: The Allen Consulting Group (2010) finds the value of broadband Internet access to the average American household is about 3.4 percent of average household income. Using the base case to determine the number of households adopting broadband, this translates into an estimated value of broadband to new subscribers of $2.6 billion per year.

Given all of the above, the CCI component of NTIA’s BTOP program strikes me as a very good investment of public funds in that it: 1) delivers substantial direct and indirect net social value, as suggested by the ASR study and; 2) helps correct the substantial excess-profit market failure suggested by both the CFA analysis and the dramatic cost savings reported by CAIs after connecting to BTOP-funded CCI fiber networks. And given these strong indicators of net social value, I’d suggest that the federal government consider expanding its CCI investment in geographic areas that the FCC’s special access data collection project indicates still face a lack of competitive options and an abundance of excess-profit-extracting prices in the special access market.

I’ll have more to say about this perspective in future posts.

Primary takeaways

Digital inequality shows larger impacts on youth academic performance as compared to time spent on screens.
Digital skills play a significant role in mediating unstructured online engagement (social media use, playing video games, browsing the web) and youth academic, social, and psychosocial development.
Unstructured online engagement and face-to-face social interaction are complementary and continuously interact to create and enhance youth capital outcomes.

A familiar story: concerns of screen time

Today’s discussions of adolescent well-being have coalesced around a clear narrative: teenagers spend too much time online, and their academic performance, mental health, and social lives are deteriorating as a result. A steady stream of academic papers, books, and op-eds, alongside a growing number of policy proposals––school phone bans, age-gated social media use, restrictive screen-time limits––rest on the same underlying claim, aligning with a contemporary, digitized version of the displacement hypothesis:

Screen time, particularly the unstructured, free-time spent on social media, gaming, watching video content, or browsing the web, is said to displace the productive face-to-face activities that build adolescents into capable adults.

The implied and often practiced solution is restriction. In response, this dissertation tested this claim directly, and placed it within the broader context of adolescence.

Across three years, I followed 653 Michigan adolescents from early through late adolescence: in grades 8 or 9 (survey one, 2019) to grades 11 or 12 (survey two, 2022). Notably, these students, studied over time, were part of a broader pooled sample of 5,825 students across the same eighteen highschools. The study window captured the year before and the year after the peak of the COVID-19 pandemic and related lockdown orders, functioning as an unprecedented stress test for theories of adolescent social, academic, and digital life and, importantly, as a benchmark to compare the effects of pandemic-related change and inequality to those effects from screen time alone.

Across four studies of adolescents, consisting of six cross-sectional and longitudinal analyses, findings are not consistent with the displacement narrative, nor the broader concerns about the time youth spend on screens.

Findings are, however, consistent with something the current public and (most) academic discussions have largely overlooked or ignored: the gaps and inequalities that determine whether adolescents can access and use the internet meaningfully in the first place.

What the displacement hypothesis overlooks

Displacement and related research and policy concerning the time young people spend online assumes a “zero-sum” model of adolescent day-to-day time. An hour online is an hour not spent studying, reading, sleeping, or interacting face-to-face (i.e., time spent on more productive or developmentally “better” activity).

Indeed, this makes sense logically. However, as an empirical claim, this model requires time spent online to behave differently from all other ways adolescents allocate time; it must produce uniquely negative outcomes and be inherently harmful across digital contexts, rather than the typical mix of trade-offs corresponding to, and often overlooked among any other social or developmental context.

Yet, online time does not differ from other youth activity. Instead, I find it has a mix of pros, cons, and even some “uniquely digital” benefits which youth utilize for social and academic gains. When I compared unstructured digital media use against traditional face-to-face interaction and activities, both produced similar patterns: some negative associations with academic outcomes, some null, and some positive.

Trade-offs within traditional face-to-face activity (for example, social time with friends and family, or time spent in after-school extracurriculars) are treated as ordinary developmental experiences that must be experienced for the betterment of development. The identical trade-offs involving digital time tend to be overlooked or ignored, and online engagement is perceived as altogether harmful.

A growing body of evidence, including this dissertation, do not support that distinction. Indeed, the developmental context is routinely misread, leaving out the context of the experiences and time spent on digital, as well as face-to-face activities, interactions, existing inequalities, and changes inherent to development. As such, I proposed a novel framework to understand these contexts:

Digital capital exchange

Rather than treating screen time as a unified harm, this dissertation advances an “exchange”-based framework, grounded in James Coleman’s theories of youth capital and digital inequality scholarship, particularly following Eszter Hargittai, Jan van Dijk, and Alexander van Deursen (see this list of all dissertation references for full works).

The core proposition is that adolescents’ online engagement is not an alternative to developmental activity but another, albiet modern domain through which young people accumulate and mobilize online resources––particularly digital skills––that work alongside existing social networks and experiences to be exchanged for human capital (measured as: academic achievement, aspirations, STEM interest) and social capital (peer networks, community participation, extracurricular involvement).

Online time is not the mechanism; instead, it is digital skills that I find to be the most vital component in youth capital exchange and enhancement. Unstructured online engagement contributes to online skills; those skills, accumulated and mobilized alongside existing peer, family, and community networks, translate into the outcomes researchers and parents care about, i.e., academic achievement, aspirations, and face-to-face interaction and social networks.

This digital capital framework treats online and in-person contexts as complementary rather than antagonistic, and it situates adolescents’ digital lives within the structural conditions––connectivity quality, device reliability, autonomy of use––that determine whether exchange can occur at all.

Methods (in brief)

Paper-and-pencil surveys were administered to students in classrooms at two time-points: spring 2019 (N=2,876) and spring 2022 (N=2,949), across the same eighteen predominantly rural Michigan schools, grades 8–12. Official, nationally-ranked standardized reading, writing, and math test scores (PSAT 8/9, PSAT 10, SAT; College Board) were then anonymously linked to students’ survey responses with the help of participating districts.

Cross-sectional path analyses modeled pooled and wave-specific samples (pooled N=5,825); two-wave cross-lagged panel models tested reciprocal, longitudinal relationships on the 653 students who completed both surveys. Multi-group analyses of the cross-lagged panel models compared relationships between girls (N=345) and boys (N=308). All longitudinal models included time-invariant socioeconomic covariates as well as time-varying covariates to reduce omitted-variable bias.

Key findings: an overview

To summarize, to the best of my ability, eight chapters across 376 pages, I present two primary findings:

First: digital inequality predicted larger and more consistent declines in human capital than screen time did.

Unreliable home internet and technology maintenance problems––experiencing and/or dealing with broken or outdated devices and software, restrictive school-issued hardware, issues with connecting to or maintaining internet access––decreased youth GPA and standardized test achievement. And, these effect sizes were substantially larger than any negative direct effect from unstructured digital media use.

Across all four empirical studies, digital inequality emerged as the most substantial predictor of academic and developmental decline.

Second: digital skills mediated the relationship between online time and adolescent academic and social outcomes.

Unstructured digital media use, particularly online gaming and web browsing, predicted higher internet and social media skills for adolescents, which in turn predicted stronger academic achievement and self-efficacy (human capital), and social interaction and extracurricular participation (social capital). The positive indirect effect of screen time through skills offset or exceeded any small negative direct effects across several outcomes (supporting our existing peer-reviewed work: Hales & Hampton, 2025, and which you can read more about here).

These exchange processes were amplified when peer and family networks were modeled alongside digital skills, consistent with the premise that online and offline contexts operate together rather than in competition. The effect was not universal: social media skills amplified rather than offset a negative association with consistency of interest, one of the two subscales of grit. The exchange framework describes a contextual and conditional, domain-specific mechanism, not a blanket defense of time spent online.

Implications

If digital inequality, and not screen time, is the primary predictor of adolescent academic and developmental decline, and still warrants concern regarding access quality and experience even with the broader adoption of digital devices across the United States, the current policy emphasis on restriction is pointed at the wrong target. The evidence supports a different set of priorities.

Stable, reliable home (fast) broadband should be treated as an educational prerequisite rather than a consumer amenity. Unreliable connectivity exerted larger downward pressure on human capital than any measure of screen time, and that pressure intensified during the pandemic-era reliance on digital infrastructure. Technology maintenance, device repair, replacement, technical support, and the flexibility to install software and explore the web autonomously, matters as much as initial access, and school-issued devices that restrict autonomous use appear to hinder skill accumulation rather than support it.

Restrictive parental mediation of internet use was negatively associated with grit and self-efficacy at magnitudes comparable to the positive contributions of face-to-face activity. This challenges the assumption that digital restriction functions protectively. Instructive mediation, teaching adolescents to verify information, navigate platforms critically, and mobilize online resources toward meaningful ends, is the posture the data supports.

Finally, the technical skill-building that occurs through gaming, self-directed exploration, and deep web use is skill-building, not wasted time. Closing the persistent gender gap in these domains likely requires legitimizing technical play for girls, rather than restricting it for everyone.

None of the above is an argument that screen time is benign. It is an argument that screen time is the wrong focus, particularly when studied mostly in isolation. Context matters substantially, whether that is time spent on other activities during adolescence, the period of adolescence itself, digital inequality, resources gained from such online use, and how all such factors interact. The factor that predicts whether a given adolescent can convert online engagement into capital outcomes is structural: access, infrastructure, skills, and the autonomy to use them. These factors are distributed unevenly, and its uneven distribution, not hours logged, is what separates adolescents who thrive from those who fall behind.

The full dissertation is available through Michigan State University’s ProQuest archive, or see the embedded full-text PDF below. I’m happy to share papers, preprints, or the underlying framework with anyone interested and working in this area––don’t hesitate to reach out via my contact form. Thanks for reading.

Tags: BTOP competition fiber networks infrastructure NTIA public infrastructure special access

BTOP’s Fiber Investment, Social Value & the Special Access Market