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Spending on Infrastructure toward Equity (SITE) Tool User Guide

Why We Created This Tool

Ideally, infrastructure—transit, roads, plumbing, wires, and even homes—links all people to the resources they need to live a full life. It connects people to education and jobs, ensures access to quality dwellings, carries clean water, and provides parks to promote community health. The US federal government has recently expanded investment in infrastructure through the 2021 Infrastructure Investment and Jobs Act (IIJA) and has maintained funding for the Department of Housing and Urban Development (HUD). These investments are intended to make transportation safer and more effective, increase access to broadband internet, ameliorate water quality, and reduce housing costs, while ensuring benefits go to communities where they are needed most.
Historically, however, infrastructure development has produced immense benefits for some communities while causing destructive harm to others, including many low-income communities of color. Post-WWII highway projects in cities throughout the United States, for example, razed entire communities, intensified racial and economic segregation, and now expose communities of color to higher levels of air pollution. Similarly, contaminated water in aging lead pipes of older homes harms children of color at higher rates than white children. Such inequitable conditions result in disparities in health, poverty, and overall life outcomes. Today, the choices public agencies make about investments in infrastructure have the potential to reinforce—or reverse—these inequities.
The distribution of dollars through new investments will have equity implications that are critical to understand in order to prevent worsening disparities. Through the SITE tool, we aim to explore the equity implications of federal infrastructure investments by evaluating the funding distribution of programs originating from IIJA and HUD. Our work responds directly to the Biden administration’s pledge to “allocat[e] federal resources to advance fairness and opportunity.”
To our knowledge, this is the first project to attach equity metrics to the national distribution of infrastructure funding. Readers may also be interested to explore the data and analysis available at the following sites:

How to Use This Tool

Elected officials, policymakers, and advocates at the federal, state, and local levels can use this tool to understand the ways in which federal funds are distributed. Here are some potential ways to use the tool:
  • Congressmembers and Congressional staff can explore the distribution of program funding through the formulas they write, such as for the Department of Transportation’s National Highway Performance Program. They can explore, for example, the degree to which current rules result in states with a higher share of people of color getting a fair share of funding.
  • Federal departmental officials can identify whether the programs they administer through competitive grants, such as the Department of Housing and Urban Development’s Continuum of Care Program, are expanding support for communities with high levels of homelessness.
  • Elected officials and staff from state, local, and tribal governments can evaluate the degree to which their state or community is receiving funding on par with the rest of the nation. They can look up data for Colorado, for example, or Cook County, Illinois.
  • Advocates can collect information about what federal infrastructure programs are available and how funding is distributed to help them understand how best to maximize the value of federal investments.

How This Tool Is Organized

To use this tool, start with the search bar on the landing page and look up a state, county, or infrastructure program. If you don’t know specific program names, you can search for an infrastructure category to navigate to a list of related programs.
On the state and county pages, we include five data visualizations: a table of programs and their funding amounts; a map and a beeswarm comparing the amount of program funding nationally (for states) and state-wide (for counties); an equity score comparing a program’s per capita funding with indicators of need in that geography; and a barbell chart showing differences in program funding between the selected geography and the median of similar geographies. These pages intend to show how much funding an area has received compared with its need for infrastructure investment relative to other areas across the country.
On the program pages, we include a brief description of the program as well as four data visualizations: a map and a beeswarm comparing the amount of program funding nationally; a table showing three different equity scores that indicate how equitably funds are distributed; and a bar chart comparing program funding across different community characteristics. These pages intend to show how much funding has been made available through a program and how well that funding is addressing the infrastructure deficits in the communities most in need of investment.
To learn more about the data behind each of these visualizations, see the About the Data section below.

Key Terms and Operative Language

1. Infrastructure: Infrastructure is an umbrella term used to describe elements of the built environment, though there is no single definition or use of the term. IIJA (see below) largely uses it to describe transportation, energy, water, and broadband projects. For this project, we chose to expand that definition to housing, which is a key element of the built environment.
2. Equity: Equity means “the state, quality, or ideal of being just, impartial, and fair,” as defined by Race Forward. For this project, we focus on distributional equity across states and counties according to race, ethnicity, and economic class, meaning we look at which programs and policies result in a fair distribution of benefits and burdens across all segments of a community, prioritizing those with the highest needs. These distributions are, in part, the product of funding choices made by public officials, but it is worth emphasizing that achieving equitable outcomes depends on whether investments improve communities or degrade them. We do not measure these outcomes as a part of this project.
3. Infrastructure Investment and Jobs Act (IIJA): In November 2021, Congress passed this law, which will distribute $1.2 trillion through various funding programs between fiscal years 2022 and 2026 to rebuild American infrastructure and “invest in communities that have too often been left behind,” according to the White House. Throughout this project, we refer to the infrastructure law as IIJA; some officials refer to it as the Bipartisan Infrastructure Law, or BIL.
4. Formula grant: Formula grants are awarded to eligible entities based on funding formulas established by Congress or federal agencies, often based on population and other local characteristics. In some cases, these formulas were established by prior laws, and Congress has maintained funding levels to state and local jurisdictions based on those formulas without updating them to account for present conditions. Most formula grants are distributed to states, but some (such as Community Development Block Grants) are distributed to localities and others (such as Housing Choice Vouchers) are distributed to public agencies.
5. Competitive grant: Competitive, or discretionary, grants are awarded by federal departments after a request for proposals that invites applicants to submit ideas that meet federal priorities. Through competitive grant programs, governmental bodies, public agencies, and occasionally nonprofit and for-profit entities can apply for federal funding for specific programs or project ideas. Once received, applications are evaluated based on merit by a team of reviewers from the awarding agency.
6. Capacity: Capacity represents the extent to which municipal governments have the time, staff, and money to apply for and receive grants by developing compelling proposals. In the context of this project, we define capacity as the number of per-capita staff members working in county and local government offices. We calculate this figure for staff working in transportation, housing and community development, and the environment, depending on the program.
7. Externalities: An externality is an outcome, effect, or consequence of some project or investment. Positive externalities are the planned or unplanned beneficial outcomes of some effort. Negative externalities are outcomes that cause harm (often referred to as “costs”). In the context of infrastructure work, negative externalities are often undesired byproducts of construction and facility use, such as the air pollution and traffic noise associated with highways. Each project funded by IIJA programs is likely to generate some amount of negative externalities that affect communities in the immediate vicinity of the project and in the surrounding regions. We describe a large number of these externalities for different project types in the appendix of Is Federal Infrastructure Investment Advancing Equity Goals?.
8. Need: We use the term “need” in two ways for this project. First, we use it in the context of community demographics, when referring to communities with high shares of people with low incomes and people of color, because we are interested in racial and economic equity considerations. Many of these communities have either historically received less investment or experienced more negative externalities from inequitable investment than whiter or more affluent communities. As such, these communities may have a greater need for investment today. Second, we use the term “need” in the context of programmatic indicators to describe jurisdictions that have a higher need related to a specific program; for example, jurisdictions with higher housing cost burdens might have a higher need for housing assistance.
9. Indicator(s): Indicators are data points that align with programmatic need. As in the example above, one indicator for the “need” for housing investment is housing cost burden.
10. Per-capita measurements: Per-capita measurements calculate specific data per person. In this project, per-capita calculations typically represent data values per 1000 people; we note if otherwise. Per-capita measurements allow us to compare funding amounts across counties and states with different populations; for example, a county with 1,000,000 residents is likely to receive more funding overall than a county with 100,000 residents, but per-capita funding can more easily be compared between jurisdictions.

About the Data

For this tool, we analyzed (1) 58 unique grant programs funded by IIJA that will each distribute a total of at least $1 billion between fiscal years 2022 and 2026 and (2) eight housing programs each distributing at least $1 billion in 2022 through annual HUD appropriations. The data presented in the tool are limited to fiscal year 2022. We collected data from federal departmental announcements and project fact sheets. (For more detail, see the methods appendix in Is Federal Infrastructure Investment Advancing Equity Goals?) Other IIJA programs are not included in the tool either because the funding they will distribute is lower than $1 billion, or their complete award announcement information was not available by spring 2023, when we collected data.
The federal government issued funds to regional, state, local, tribal, and private awardees. We indicate the county and state where funding was injected, but do not indicate the specific awardee. The county or state associated with an overall funding amount is not necessarily the specific awardee of some program funds (we use the county level as the smallest unit of geospatial analysis in this tool because it is nationally comprehensive). For example, we would classify a grant awarded to the Chicago Transit Authority to Cook County and Illinois.
When possible, we visualize indicators and programmatic data at the county level. Project funds occasionally cover multiple counties. In these cases, we assume that funds are spread out evenly across these counties. The federal government distributed some awards directly to state governments for projects whose geographies were not yet defined. In these cases, we include awarded funds in state and program totals, but not at the county level. Many formula funds are distributed to state governments through formula, so we do not break down these data to the county level because we do not have adequate information to know how those funds have been spent.
We collected data for demographic and need-indicators from a wide range of publicly available sources, including the 2016–20 US Census American Community Survey and data produced by other federal agencies. These indicators allowed us to investigate the degree to which program funds were disbursed (1) compared with local demographics and (2) compared with a jurisdiction’s possible investment needs. Demographic indicators include characteristics such as population density, share of residents who are people of color, and median household income. Program-related need indicators include broadband speed, number of public transit stops, share of vacant housing units, and share of bridges in poor condition, among others. To review the complete list of data sources and methods used in this work, see the methods appendix in Is Federal Infrastructure Investment Advancing Equity Goals?

Interpreting the Data and Applying Results

We present measurements that capture several different dimensions for how federal funding may be meeting need and equity goals in this tool. Each measurement should be interpreted within its local context and evaluated with the understanding that infrastructure projects generate both positive and negative externalities.
We provide data on a variety of indicators that may help paint a picture of the level of need for infrastructure in specific communities. But these indicators do not always tell a clear story. We use miles of major roads and highways (per capita per square mile), for example, as one way to evaluate transportation programs. Places that have more roads might need high levels of transportation funding to help maintain those roads, but places with fewer roads might also have a high need for funding to build new roads and connect communities that currently lack transportation options.
How a program distributes funding depends on the processes and people in charge of making funding decisions. These actors may differ depending on whether a program uses the formula funding process or the competitive funding process described above.
  • In the formula process, the primary decisionmakers are (1) Congress or federal agencies, in the creation of the initial formula and allocation of funds, and (2) state government agencies, which decide how to distribute most of these funds. Some local governments, tribal governments, and local agencies also receive formula funds.
  • In the competitive process, the primary decisionmakers are (1) federal agencies, which review proposed projects and make decisions about which to fund, and (2) applicants (e.g., state, county, city, and tribal governments; transit authorities; regional entities), which make decisions about whether to apply for funding, which projects to submit, and how to fill out applications.
Once we collected the program funding data and established the demographic and need-indicator categories, we analyzed each of the 66 programs by comparing the distribution of funds across counties and states with the various indicators. This process allowed us to explore whether infrastructure funds are more likely to support communities with certain characteristics.
First, we calculated an equity metric for each jurisdiction, which calculates the difference between the funding percentile and indicator percentile for each program and relevant indicator combination. A score of 0 indicates that the jurisdiction’s funding is proportional to the indicator. A negative score indicates the jurisdiction is receiving less funding than its indicator value would imply; a positive score indicates the jurisdiction is receiving more funding than its indicator value would imply. For example, if a county was at the 40th percentile for the funding it received from the Bridge Formula Program, but in the 70th percentile of need for its share of bridges that are in disrepair, that county would have an equity metric of –0.3 for that program and indicator combination. This metric might indicate that the Bridge Formula Program is not meeting that county’s needs in terms of bridges in need of repair, at least when placed in the national context.
Next, we produced three equity measures for each program:
  • The concentration measure indicates, for each program, how national funding is concentrated in the highest-need jurisdictions according to a selected indicator. For each indicator, we have compiled the highest-need jurisdictions that comprise approximately 25 percent of the US population. (Depending on which jurisdictions are included, slightly more than 25 percent of the US population may be included.) Scores range from –1 to 3. A score of 0 indicates that jurisdictions accounting for the top 25 percent of the US population, ranked based on a given indicator, receive roughly 25 percent of the funding. A lower score means that these jurisdictions receive less than 25 percent of the funding, and a higher score means that these jurisdictions receive more than 25 percent of the funding. For example, if a program has a county-level concentration score of 1 when measured in terms of share of people of color, that would mean that the program distributes about 50 percent of its funding to the quarter of the population living in counties with the highest shares of people of color.
  • The high-need equity measure shows, on median, how close high-need jurisdictions are to receiving a level of funding that would meet their need, as indicated by a specific indicator (e.g., share of residents of color). High-need jurisdictions are those above the 50th percentile for the given indicator. We calculate this measure for each program and relevant indicator combination. In other words, this measure shows the median equity metric (described above) for the jurisdictions in the top 50th percentile of need. Paired with the concentration measure, this measure indicates whether high-need jurisdictions are receiving progressively more funding than lower-need jurisdictions. Scores range from –1 to 1, with negative values signifying that the median high-need jurisdiction is receiving less funding than its indicator value, and positive values signifying that the median high-need jurisdiction is receiving more funding than its indicator value. The nature of this high-need measure makes it very difficult to achieve a positive score. You can use this measure’s distance from zero to understand how close programs are to progressively meeting need in terms of a particular indicator. If a program has a high-need equity score of –0.2 for median household income, that would mean that the median equity metric for counties in the top 50th percentile for need is –0.2. This number could mean, for example, that the median high-need county is at the 50th percentile for program funding, but at the 70th percentile for median household income.
  • The variability measure indicates the degree to which a program’s per-capita funding aligns with the nation’s overall per-capita funding. A variability score of 0 means that the program’s state-level funding distribution is similar to the national distribution. A higher variability score indicates that the state-level funding distribution for that program is farther from the national distribution, in either direction. Scores for most programs fall between 0 and 10. A program having a score of 8, for example, might mean that the typical state is receiving either much higher or much lower per-capita funding than would be true if funding were spread evenly across the country. This metric is relevant for formula programs only, in which large amounts of funding are distributed to all states.
There is no such thing as a “perfect” measure. All measures show just one dimension of how a program may be meeting equity goals and should be viewed in combination with each other and with local context in mind to get a fuller picture.

About the Authors

About the PERC Initiative

The Melville Charitable Trust funded this work as a component of the Partnership for Equitable and Resilient Communities (PERC), a new justice venture that aims to build cross-sector collaborative partnerships nationwide, prepared to secure and implement public funds specifically focused on advancing economic development, housing, and civic infrastructure. PERC works with cities to strategically form and activate powerful coalitions that center the voices and expertise of Black, Indigenous and Latino/a/x communities, deliver measurable and results-based outcomes, and ultimately, redefine the decision-making process for investment, implementation and long-term impact of public funds. See the Partnership for Equity website for more information.
The venture launched with Cleveland, Ohio; Durham, North Carolina; St. Paul, Minnesota; and Selma, Alabama as its first sites.
By creating the first database that pairs equity metrics with federal infrastructure funding distribution data, this research project supports the PERC Initiative’s goal of advancing racial equity through conscientious local development by providing insight into how federal dollars are distributed across the country and by helping local leaders better understand the positioning of and opportunities for federally supported infrastructure work in their communities.

About

For this tool, we analyzed 58 grant programs funded by IIJA and eight housing programs that use annual HUD appropriations. The data presented here are limited to fiscal year 2022. We collected program data from federal departmental announcements and project fact sheets. Demographic and need indicator data are sourced from approximately two dozen publicly available sources, including the 2016–20 American Community Survey 5-Year estimates from the US Census Bureau and data produced by other federal agencies.

To learn more about how to use this tool, see our User Guide. To review the complete list of data sources and methods used in this work, see our full report.

Project Credits

This data tool was funded by the Melville Charitable Trust as part of the Partnership for Equitable and Resilient Communities Initiative. We are grateful to them and to all our funders, who make it possible for Urban to advance its mission. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Funders do not determine research findings or the insights and recommendations of our experts. More information on our funding principles is available here. Read our terms of service here.

View the project on Github