The American Rescue Plan Act (ARPA) aimed to aid small communities, but the Treasury’s formula missed the mark dishing out similar funds per capita to less populated areas, regardless of wealth. This left some needy areas shortchanged.
by Kyle Huisman, Kathleen Bolter & Lee Adams
Illustration by Kathleen Bolter; photographs by Library of Congress; and Karolina Grabowska via Pexels.
On March 11, 2021, President Joe Biden signed a $1.9 trillion federal stimulus bill, the American Rescue Plan Act (ARPA). Within that legislation, the Coronavirus State and Local Fiscal Recovery Funds (SLFRF) allocated $350 billion to help state, local, and tribal governments handle the economic and public health impacts of the pandemic. The goal of the legislation was to allow local governments to continue providing public services by replacing lost revenue, and to enable communities to make investments that would promote sustained growth. This funding was intentionally flexible, so as to allow each community to respond to its own particular needs.
While the inclusion of small communities (those with a population below 50,000) to receive funding was laudable, the state-by-state formula-based funding model used by the U.S. Department of the Treasury (Treasury) for nonmetropolitan cities did little to address differences in local need for less populated areas. Because economic conditions in small communities were not considered when allocating SLFRF funds, in many states impoverished small communities received the same funding per capita as wealthier small communities. Additionally, because aid was distributed based on a state’s nonmetro population, communities with similar levels of need received vastly different levels of funding depending on which state they were located in. Some states used their own ARPA money to develop programs to help close these divides, providing examples for how this issue could be addressed, absent federal intervention. This disparity in funding underscores the importance of considering local economic conditions when designing and allocating resources, to ensure that support is effectively targeted where it is needed most.
Aid for Small Communities
One noteworthy aspect of SLFRF is that it included small communities at all. In contrast, the previous CARES Act (Coronavirus Aid, Relief, and Economic Security) provided direct funding only to local governments with populations of over 500,000. And while states were authorized to share their CARES allocations with smaller governments, a survey by the National League of Cities found that 29 percent of cities, towns, and villages—roughly 6,000 communities total—did not receive any funding from the CARES Act. Thus, ensuring that smaller communities had access to funding was an important part of the implementation of ARPA. After all, of the approximately 250 million Americans living in an incorporated town or county subdivision eligible to receive SLFRF funding, 81 percent live in communities with a population of under 500,000 people.
Inequities Caused by Formula Funding by State
The Treasury applied distinct formulas to allocate funds to the various levels of government eligible to receive SLFRF: state governments, county governments, metropolitan local governments, and smaller governments known as nonentitlement units (NEUs). NEUs consist of incorporated places, and in some states, minor civil divisions (such as townships), with a population under 50,000. While the Treasury classified some local governments with populations below 50,000 as metropolitan cities based on criteria from the Housing and Community Development Act of 1974, this represents a small proportion of cities (these small cities make up less than 10 percent of all “metropolitan cities”).
The allocation of SLFRF funds to NEUs followed a formulaic approach. The Treasury calculated distribution state by state, providing each NEU within a state with an equal per capita share relative to its 2019 population, but with the exception that the allocation could not exceed 75 percent of an NEU’s early 2020 budget. (Exceeding 75 percent was relatively uncommon.) This formula led to wealthier NEUs and more impoverished NEUs receiving almost equivalent levels of funding in most states. Additionally, the distribution of funding to nonurban counties was similarly based on population and not local need, meaning impoverished small communities in impoverished counties were deprived of resources at multiple levels.
In 30 states, impoverished NEUs received the same amount of funding per capita as wealthier NEUs. In six states, they received even less than wealthier NEUs. In only 13 states did the highest-poverty small communities receive more per capita funding than the lowest-poverty communities. This variation in per capita funding between NEUs was primarily the result of the 75 percent budget cap. In the absence of this cap and other special circumstances, per capita allocations to NEUs within each state would always be the same—and in most cases, they are.
Additionally, as highlighted by Civilytics, the final legislation directed SLFRF funds based on the entire nonmetropolitan population of each state. This led to significant variations in funding per capita for NEUs, based on how local governments were organized within a state: namely, it favored states with a higher percentage of nonmetropolitan population in unincorporated areas. As a result, small communities with similar levels of need received widely different levels of per capita funding based on which state they were located in. Some might argue that this formula ensures that states with large unincorporated populations are not disadvantaged, but residents of unincorporated places may not always equally benefit from stimulus funds sent to governments in which they do not reside.
Our analysis shows the range in per capita funding between states to be quite wide. For example, because Nevada has a larger unincorporated population relative to its total nonmetropolitan population, impoverished NEUs, on average, received $1,200 per capita in funding from ARPA. Comparatively, an NEU with a similar level of need in Michigan received only $105 per capita in funding, simply because the state of Michigan has a larger population living in incorporated areas and county subdivisions eligible to receive SLFRF.
A Need-Based Funding Model
A better model for distributing funding is one that takes local need into consideration. Interestingly, the Treasury did have a method for taking need into account, but applied it only to metropolitan cities and, in some cases, urban counties. Unlike with NEUs, funding to metropolitan cities was not allocated based entirely on population size. Instead, funding for metropolitan cities was based on a modified version of the Housing and Urban Development Department’s Community Development Block Grant (CDBG) formula, which prioritizes higher levels of funding to areas with more need. As a result, metropolitan cities with high levels of poverty received over three times more funding per capita than wealthier metropolitan cities. Additionally, while there were still state-level differences in funding between metro areas of similar poverty levels, the gaps were only half as large as they were for NEUs.
Addressing issues of inequity in funding distribution is important in ensuring that all communities can thrive. Inequitable funding contributes to widening social and economic gaps between communities. When areas with greater need do not receive adequate resources, it makes it harder for such places to make investments in addressing challenges such as poverty, inadequate infrastructure, and limited access to essential services.
States Can Help Close the Gap
While the funding model used by the Treasury did not equitably distribute ARPA money, some states did step in to provide robust technical assistance to less-resourced, smaller local governments to enable them to utilize the funding available for local investment. For example, the Vermont legislature, realizing that a large percentage of ARPA allocations were going to wealthy areas of the state, created the Municipal Technical Assistance Program (MTAP) to help small towns access the $370 million in ARPA funds available to the state, which had to be spent by 2024. Many small towns in Vermont do not even have a city manager or administrator, and these areas have had a difficult time accessing federal stimulus funds. To address this, the MTAP distributed funds to 11 regional planning commissions scattered across the state. Staff at the regional commissions worked with local town officials to identify uses for the funds and assist with administrative work.
Additionally, the state of North Carolina used $50 million in state SLFRF allocations to establish the Rural Transformation Grant Fund. The program distributes grants to communities to support projects aimed at attracting investment, improving amenities, and retaining businesses. Through the program, communities can also receive technical assistance and training provided by the North Carolina Department of Commerce to increase local government capacity. These initiatives underscore the importance of state-level interventions in ensuring that funding reaches communities with the greatest needs.
While ARPA was important because it included funding for small cities, some issues have arisen pertaining to how funding was dispersed. Policymakers should address these issues in future stimulus packages aimed at local governments. The Department of the Treasury’s formula system for NEUs led to high-poverty small communities receiving the same funding as wealthier small communities. This system also resulted in disproportionately high per capita funding for NEUs in certain states where a significant portion of the nonmetropolitan population resides in unincorporated areas ineligible for SLFRF funds.
In future stimulus endeavors, policymakers could chart a more equitable course by addressing issues observed in ARPA’s funding dispersion, ensuring that local need is a central consideration. State governments, recognizing their pivotal role, could intervene to provide essential technical assistance to the areas that need it most, fostering a more inclusive and effective approach to supporting local communities.
Policy Recommendations
• Develop a more nuanced allocation model for future stimulus funds, one that accounts for the specific needs of small communities, beyond just population size. For example, this might entail applying the CDBG formula, or something like it, to NEUs.
• Establish comprehensive technical assistance programs at the state level to aid smaller municipalities with limited administrative capacity.
Analyzing ARPA Data
To analyze the allocation of SLFRF funds, we used quarterly and annual SLFRF project spending data reported by the U.S. Department of the Treasury up to March 2023. The data encompass over 26,000 ARPA fund recipients, ranging from small villages and towns to large cities, counties, and states. While more than 29,000 local subcounty governments are theoretically eligible for SLFRF, only around 23,000 appear in the Spring 2023 annual reporting data. For our per capita expenditure analysis, we focused on the nearly 21,400 town and city governments (including consolidated city-county governments) for which we were able to merge Census Federal Information Processing System codes, thus enabling us to merge population and other demographics to the SLFRF data.
Next, we divided the communities in our sample into categories based on their populations and which Treasury formula they received funding under:
- NEUs
- Metropolitan government or consolidated city-county government with a population of less than 250,000
- Metropolitan government or consolidated city-county government with a population greater than 250,000
For our per capita analysis, we use the same 2019 census city and town population estimates that states used to allocate SLFRF funds to NEUs based on reference files. Additionally, we incorporate demographic data from the 2019 American Community Survey five-year estimates.
To create the poverty quartiles used in the analysis, we relied on a comparison data set of all incorporated places and county subdivisions theoretically eligible to receive SLFRF funding (of which there are over 29,000, compared to a little under 21,400 recipients in our data set). This data set was created using the same 2019 census city and town population files used by the Treasury to estimate local populations of SLFRF-eligible cities and towns. We used local household poverty estimates derived from the 2019 ACS five-year sample to divide the areas into four quantiles containing approximately 25 percent of the total population of the data set each. We then applied these cutoffs to the SLFRF recipient data. Each quantile contains roughly 25 percent of the data set population of both NEUs and metropolitan cities combined.
Authors
Related Work
