Recently we launched the Benton Institute’s Affordable Connectivity Program Enrollment Performance Tool, a free resource that helps communities answer the question: “How are ACP sign-ups going?” Using the tool to search 5-digit zip codes delivers two important numbers:  1) how many households have signed up for ACP and 2) the expected number of households enrolled. Comparing expected enrollment to actual enrollment is a measure of performance. In this article, our goal is to help readers better understand the tool’s inner workings and what that means for policymakers.

The ACP Enrollment Performance Tool rests on a statistical model that captures individual and community-wide circumstances to explain ACP enrollment at the 5-digit zip code level. The inclusion of community-wide characteristics adds significantly to the tool’s predictive power and offers a more nuanced view of what influences ACP enrollment levels. If ACP enrollment is cast only as an individual decision, then explaining it is relatively simple. The government determines who is eligible, these households demonstrate that they qualify, and then decide whether to undertake the effort to enroll.

The reality is much more complex. Many potentially eligible households are unaware of the ACP, a significant number encounter frictions in enrolling, and some harbor suspicions about whether the benefit is “too good to be true.” The availability of trusted information and intermediaries can help smooth the enrollment process, and a household’s community can be a conduit for such trusted information. This can happen through anchor institutions such as schools, libraries, community organizations, and even locally-owned businesses. Our model captures some of these community characteristics by including economic variables, a community’s digital assets, and other factors.

The Impact of Income on ACP Enrollment

The model uses two inputs to capture income effects. The first is ACP eligibility. Our definition of eligible households captures more than ACP’s 200% of federal poverty level criteria, including, for example, SNAP enrollment (details on eligibility calculations are here). As expected, the share of eligible households in a zip code is a strong predictor of enrollment.

The model also explores the role of severe poverty, namely the degree to which an area has a high concentration of households whose annual incomes are $15,000 or less. It turns out that living in a very poor neighborhood is an additional factor (beyond eligibility) that is positively correlated with enrollment. This suggests that ACP is breaking through in very low-income neighborhoods. Since poverty is typically a barrier to pursuing opportunity, this is a striking finding.

Adoption of Digital Tools & ACP Enrollment

Our model also includes several metrics of technology adoption: the share of households with wireline broadband subscriptions, the share of households relying on cellular data plans as their only internet subscription, and the share of households without computers. Areas with a high share of households with wireline subscriptions have higher rates of ACP enrollment, as do areas with a high share of households without a working computer. There was a positive association between areas with a high share of “cell only” households and enrollment. Overall, places where there is a high share of people without broadband subscriptions of any type (wired or wireless) have somewhat higher ACP enrollment rates.

Other Factors Impact ACP Enrollment

Estimating ACP enrollment is not all about income and digital tools. The tool’s model shows that the presence of public libraries boosts ACP enrollment, suggesting that digital navigator programs (often hosted in libraries) or libraries’ role as community tech hubs make a difference.

But other factors work against ACP enrollment, such as areas where housing costs (captured by the share of households that are “rent burdened”), share of unoccupied homes, and places with many immigrants (captured by the share of foreign-born residents). Age is also an issue; places with high proportions of older (age 65+) adults have lower ACP enrollment levels.

What These Factors Say About ACP’s Impact

At the national level, the ACP Tool’s model shows that the program is:

• Addressing “subscription vulnerability”: ACP helps lower-income households maintain service, as shown by the strong link between the share of households currently with wireline subscriptions and ACP enrollment. Nearly half (46%) of low-income households with home broadband subscriptions say they have difficulty affording service, so it is little surprise many have taken advantage of ACP’s $30 subsidy.
• Narrowing the digital divide: There is a statistically significant link between places where people do not have any home broadband subscription and ACP enrollment. Additionally, forthcoming survey data (early results shared here) shows that as many as 25% of ACP enrollees use the benefit for a new wireline connection. This additive effect is of smaller magnitude than the “subscription vulnerability” effect.
• Reaching very low-income households: The analysis shows a strong relationship between places with a high share of households whose annual incomes are $15,000 or less and enrollment. This suggests that the pandemic underscored the urgency of connectivity among the lowest incomed among us – so that they have sought out assistance to get online. Yet the pull in the opposite direction is real for some issues, such as those facing high housing costs and older adults who may need very directed help in signing up for ACP.

The ACP Enrollment Performance Tool is offering early evidence that the program is helping to close the digital divide by both supporting new wireline broadband subscribers and helping connected households that are at risk of losing their service stay online.

In our next article, we’ll take a closer look at how state and local policymakers can use the ACP Enrollment Performance Tool in broadband planning efforts.

John B. Horrigan is a Benton Senior Fellow and a national expert on technology adoption, digital inclusion, and evaluating the outcomes and impacts of programs designed to promote communications technology adoption and use.

Brian Whitacre is Professor and Neustadt Chair in the Department of Agricultural Economics at Oklahoma State University, where he studies the role of technology in rural economic development.

Hernan Galperin is Associate Professor at the USC Annenberg School for Communication where he studies Internet policy and social inequality.​

The Benton Institute for Broadband & Society is a non-profit organization dedicated to ensuring that all people in the U.S. have access to competitive, High-Performance Broadband regardless of where they live or who they are. We believe communication policy - rooted in the values of access, equity, and diversity - has the power to deliver new opportunities and strengthen communities.

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