How to assess consolidation in broadcasting.

Last week, Vincent (Vinnie) Curren, Principal at Breakthrough Public Media Consulting, Inc., gave an insightful Quello Center presentation about the technological and market potential of ATSC 3.0, an IP-based standard created by the Advanced Television Systems Committee (ATSC).[1] As CNET put it, this standard was created with the idea that most devices would be Internet-connected, enabling a hybrid system whereby the main content (audio and video) would be sent over the air, but other content (advertisements) would be sent over broadband and integrated into the program. This creates some very interesting opportunities for individualized marketing, though as ATSC touts in a somewhat cutesy promotional video, ATSC 3.0 is capable of a lot more.

Vincent Curren

The conversation with Vinnie took an interesting turn (to me anyhow), when he contrasted the state of public broadcasting in Michigan with that in Arkansas. According to Vinnie, public broadcast station management in Michigan is highly balkanized, whereas in Arkansas, it is largely centralized. This implied far fewer individual station engineers and managers in Arkansas, where budget savings from having a smaller bureaucracy are instead applied toward better local news coverage. Effectively, Vinnie was touting the benefits of merger to (state level) monopoly.

This statement immediately set off my antitrust alarm (which sounds like this). After all, even if a merger between two firms that preserves both firms’ products (e.g., broadcast stations) can reduce costs, monopolistic ownership could still raise prices above that in a duopoly by internalizing competition between the firms. More specifically, when one firm in a duopoly raises its price, some of its customers will switch to its competitor’s product and vice versa. This competitive threat puts downward pressure on prices relative to what happens under a monopoly. When a monopolist sells both products, a rise in the price of one positively impacts demand for the other, inducing the monopolist to set higher prices unless a merger to monopoly lowers costs sufficiently to offset this anti-competitive effect. The fact that antitrust practitioners seldom consent to a merger to monopoly suggests that the anti-competitive effect usually dominates.

However, the broadcasting market is different! Broadcasters operate in a multi-sided market that is likely to become even more complicated by the spread of ATSC 3.0. First, consumers of content do not pay broadcasters to watch television. Instead, broadcasters subsidize consumers, but charge advertisers for airing commercials (though in the case of public broadcasting, this is largely supplemented by contributions from viewers like you). Broadcasters may also charge retransmission fees to cable operators who carry broadcasting content and do charge consumers for content generally. Moreover, with ATS 3.0, Internet service providers will have to be involved in this market if advertisements are to be integrated via broadband. This means that the effect of merger operates through a mechanism that is far more complex than the “internalization of competition.”

After Vinnie’s presentation I considered whether economists have attempted to tackle the issue of merger in a multi-sided market. The issue is relatively understudied, but two papers stood out in my literature search:[2]

Chandra, A., & Collard‐Wexler, A. (2009). Mergers in Two‐Sided Markets: An Application to the Canadian Newspaper Industry. Journal of Economics & Management Strategy, 18(4), 1045-1070.
Tremblay, M. J. (2017). Market Power and Mergers in Multi-Sided Markets. Available at https://ssrn.com/abstract=2972701.

Chandra and Collard‐Wexler (2009) theoretically explore a two-sided merger from duopoly to monopoly and then use difference-in-differences approaches to empirically investigate mergers by newspaper publishers. As in many other two-sided markets, newspaper publishers offer one side (consumers) a subsidy by charging below cost. This is because newspapers not only value readers’ circulation revenue, but also the value that advertisers place on consumers. In the model of Chandra and Collard‐Wexler (2009), the key factor that determines how newspaper mergers affect prices is how newspapers value the marginal consumer who is indifferent between two competing newspapers.

If the revenue that this consumer indirectly brings in through advertisement consumption is lower than the loss to the newspaper of subsidizing the consumer’s newspaper purchase, then competing duopolists will set higher circulation prices in equilibrium than a monopoly owner of the two papers (even absent any cost reduction by the monopolist). This result is driven in large part by the authors’ assumption that consumers who are indifferent between the two papers will turn out to be less valuable to advertisers, and hence will bring in advertising revenues that are lower than the subsidy they enjoy on the paper. The assumption is well motivated in the paper, but may not necessarily apply in broadcasting. Moreover, if the reader provides a positive value to the newspaper, then mergers can still increase prices (unless cost reduction is sufficient to counteract market power).[3]

Tremblay (2017) sets up a relatively general multi-sided platform model that he uses to measure platform market power and to assess the effect of platform mergers. In this model, multiple platforms that facilitate interactions between distinct groups (e.g., broadcasters might serve consumers of content and advertisers) compete by pricing for each interaction facilitated by the platform.

The model highlights the complexity of analyzing multi-sided markets by recognizing that demand for any interaction is a function of not only the vector of prices involved in that interaction—as in a “one-sided” market—but also of the vector of all other interaction types! Thus, not only must we consider the demand response to a change in price for that interaction, but also the demand response to the numerous potential externalities that might exist (e.g., a negative network externality can occur on media platforms where greater consumer advertisements diminish consumer usage on the platform).[4]

As such, in addition to consisting of the usual marginal cost and demand elasticity contingent markup, the equilibrium price for a specific interaction is also dictated by what Tremblay refers to as “marginal profit elsewhere,” which consists of the marginal changes that the interaction in question engenders on all other interactions. Moreover, in the case of a multi-platform seller (e.g., broadcaster that owns multiple stations), as might follow post-merger, the equilibrium price is impacted not only by the standard diversion term that gauges the extent to which a merger can internalize competition, but also by “diversion elsewhere,” which results from multi-sidedness. This “diversion elsewhere” means that some platform prices may decrease post-merger, suggesting that even without cost-reduction benefits, a horizontal platform merger may be efficient.

Certain factors complicate matters even further in broadcasting. As Vinnie pointed out, a significant part of a local television station’s advertising revenue comes from national advertisers, especially in the larger markets. In many cases, prices are not set unilaterally, but are determined through negotiations with advertisers. A larger multiple-market footprint gives larger broadcast groups leverage when they negotiate pricing for national clients. The effect of a broadcasting merger surely depends on this countervailing bargaining power as well as on whether content consumers view advertising as a good or a bad.

Additionally, a significant part of local station revenue comes from “retransmission consent fees.”[5] If it opts for retransmission consent, a cable service provider is not required to carry the broadcaster’s channel, but if the cable operator chooses to do so, the broadcaster can demand “retransmission” or rights fees. A large station owner like Sinclair, which operates hundreds of stations, has additional leverage when negotiating retransmission consent fees with a large cable operator like Comcast. Of course, cable companies may pass these fees down in the form of higher prices to consumers. The additional revenue on the broadcaster side may lead to better content, but that will probably come at a higher price for cable service.

ADDENDUM

After reading this post, a former colleague who is very knowledgeable in this area pointed out that there has been some research on the trade-offs of consolidation in two-sided markets and related issues that predates the modern multi-sided market literature.

An early two-sided market analysis by Robert Masson, Ram Mudambi, and Robert Reynolds (1990) shows that competition can sometimes lead to a price increase. Moreover, in the model, competition either makes advertisers better off while making media-consumers worse off or the other way around. An even older related piece by James Rosse (1970) seeks to estimate cost functions in the newspaper industry without cost data. Yet another article concerning the newspaper industry by Roger Blair and Richard Romano (1993), looks at newspaper monopolists, which as the authors point out, nevertheless frequently sold newspapers at below cost. I suspect that the two-sided logic for this to occur is a lot more clear to economists today than it was in 1993.

[1] ATSC is an international, non-profit organization developing voluntary standards for digital television. Member organizations represent the broadcast, broadcast equipment, motion picture, consumer electronics, computer, cable, satellite, and semiconductor industries. See https://www.atsc.org/about-us/about-atsc/.

[2] Other related work includes Filistrucchi et al. (2012) and Song (2013). See Filistrucchi, L., Klein, T. J., & Michielsen, T. O. (2012). Assessing unilateral merger effects in a two-sided market: an application to the Dutch daily newspaper market. Journal of Competition Law and Economics, 8(2), 297-329; Song, M. (2013). Estimating platform market power in two-sided markets with an application to magazine advertising. Available at https://ssrn.com/abstract=1908621.

[3] Note that I have not discussed the impact of merger on the price of advertising. The authors find that the effect on advertising price is indirect: if there is an increase in a newspaper’s circulation price, this will increase the average value to advertisers of that newspaper.

[4] In the words of Tremblay, demand contains an infinite feedback loop because demand for an interaction by platform X is a function of demand for an interaction Y and vice versa.

[5] Commercial stations have a choice between two options with respect to making their programming available to cable and satellite systems. They can exercise “must carry.” If they do this, the cable service provider is required to carry the broadcaster’s primary channel but does not have to pay the broadcaster any rights fees for carrying the channel. Alternatively, cable service providers can exercise “retransmission consent.”

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: ATSC 3.0 broadcasting horizontal merger multi-sided markets two-sided markets

How to assess consolidation in broadcasting.