Analyzing Persistent Poverty Areas Using Federal Data
Recommended Citation:
Farrigan, T. and Crowe, J. (2023). Analyzing Persistent Poverty Areas Using Federal Data.
FCSM Equitable Data Toolkit: A Toolkit for Strengthening Federal Data to Analyze Historically Underserved Populations. Washington, DC: Federal Committee on Statistical Methodology.
Federal agencies are building on a legacy of past efforts as they strive to better understand and address issues of equitable access. Persistent poverty indicators have been relied upon to target, implement, and monitor federal grants and programs designed to support educational and employment opportunities, health care services and healthy food access, transit service and community facilities improvements, housing assistance and land development loans, fiscal health and administrative capacity of local governments, energy savings and climate change resilience, and aid to underserved groups (see Appendix Tables 1 and 2 for links to related legislation and federal agency examples).
Goals of this section of the FCSM Equitable Data Toolkit
Poverty is a long-standing and fundamental measure of economic well-being and inequality in the United States. Its measurement occurs initially at the levels of families and individuals. The emergence of spatial poverty measures, which characterize the extent and nature of poverty for geographic areas, reflects the recognition that the geographic concentration of poverty has its own socioeconomic dynamic (see for example Understanding Neighborhood Effects of Concentrated Poverty). The concept of "persistent poverty" introduces a temporal dimension. It reflects the recognition that the persistent concentration of poverty in a geographic area over multiple decades also has its own socioeconomic dynamic, which differs from that associated with concentrated poverty that is intermittent or that exists for just a short time.
Though well established in federal program design, persistent poverty area measurement in the federal government is not uniform in its methodology or application. The purpose of this section of the FCSM Equitable Data Toolkit is to provide federal agencies with information on existing persistent poverty area indicators and on the underlying constructs of persistent poverty area measurement. With this information, federal agencies will know of their options when seeking a persistent poverty area measure that can meet their research or programmatic needs. For consistency with other agencies, an agency may elect to adopt an existing measure.
Discussion of tools to measure persistent poverty areas consists of three main sections:
- A conceptual and methodological history of persistent poverty's emergence in federal policy.
- Guidance on navigating the existing landscape of federal persistent poverty area indicators, their methodologies and uses, and alternative concepts and measures.
- Discussion and guidance to help users make decisions about and locate resources for generating their own persistent poverty area indicator and related demographic, social, and economic statistics.
What is persistent poverty?
In most countries around the world, the term persistent poverty refers to a form of chronic poverty that is defined by a person or household with relatively low income (e.g., below 60 percent of median area disposable income) for several consecutive years (see for example, Persistent Poverty in the UK and EU). Given that it is a relative measure, this definition of persistent poverty doesn’t imply abject despair or even a necessarily low standard of living, but rather is understood as a measure of being at risk of poverty. Persistent poverty typically has a very different definition and meaning when used in reference to economic well-being in the United States.
The term persistent poverty in the United States generally refers to a spatial concept of poverty defined by long-standing geographic concentrations of the poor. It is commonly defined by a high rate of poverty (usually 20 percent or more) in a given geographic area over a number of consecutive decades (most often three or four, as indicated in the data years and sources column in Appendix Table 1 and in details available from links in Appendix Table 2). As an indicator of spatial well-being, such a measure effectively captures the interwovenness of localized private sector disinvestment, deficiency of community resources, and limited economic opportunities.25 The long-term entrenchment of these conditions is often characterized by a lack of multiple baseline necessities for area residents, such as access to health care facilities, grocery stores that offer affordable and nutritious food, an adequate housing market, a sufficient educational system, jobs that pay a living wage, and essential public services. Likewise, relative material deprivation (the inability to consume goods and activities that are the norm in society) may be prevalent given lack of access to things like public transportation, parks and recreation, and civic services.
The geographic concentration of poverty can exacerbate the income poverty of individual residents by limiting the availability of services and employment prospects.26 In conjunction, persistent poverty areas (PPAs) tend to have disproportionate numbers of people with characteristics that make them prone to disadvantage, such as low educational attainment and chronic health issues.27 They also tend to have higher than average proportions of underserved racial and ethnic populations and other groups that historically have had trouble gaining access to economic opportunities. However, while PPAs often share similar challenges and characteristics, they are not socially, culturally, economically, and environmentally homogeneous. PPAs represent a complex form of poverty that manifests across unique contexts.
Meeting earlier demand for poverty area measurement
Persistent poverty area measurement is rooted in federal research and policy initiatives dating back to the early 1960s, namely the Johnson Administration’s Great Society programs, which sought to address issues such as inequities in education and access to medical care, as well as racial discrimination and poverty. With respect to the latter, the President famously declared a War on Poverty (WOP) in 1964.28 While poverty was the focus, there was no universal concept or measure of poverty to serve as a target or by which to determine success. Federal researchers and other social scientists "were enlisted to help define and measure poverty, to plan programs, and later to evaluate them and measure the progress achieved."29
Poverty definition and measurement subsequently followed two distinct paths. The better-known path is the development of the official poverty measure for families and individuals. In 1965, the Office of Economic Opportunity (OEO)30 developed a working definition of poverty constructed from a basic income needs approach for determining the poverty status of families and for counting the poor among them.31 Four years later the Office of Management and Budget (OMB) issued a memorandum establishing an ‘official’ poverty measure (OPM) and assigned the Census Bureau the task of collecting and reporting poverty statistics. Widespread use of the OPM did not come about until nearly a decade later when OMB issued a statistical policy directive (#14, May 1978) specifying the OPM as the definition of poverty to be used by all executive departments and establishments for statistical purposes.32
The lesser-known path is that of poverty area measurement, which was a growing field of study for federal researchers and rural development analysts during the years leading up to the WOP (see for example, ERS Legacy of Poverty Area Measurement). Federal spatial initiatives focusing on regional development as a means of poverty area alleviation grew extensively following the late 1950s with an awareness that poverty remained high for certain places and subpopulations while the nation as a whole prospered. This concern fueled many of President Johnson’s Great Society initiatives and subsequent need for spatial information on poverty conditions, which led to the commissioning of poverty area research. As part of the focus on urban renewal, the OEO charged the Census Bureau with the study of urban poverty areas. The study of rural poverty areas was tasked to the USDA Economic Research Service (ERS) as part of the work of the President’s National Advisory Commission on Rural Poverty (Rural Commission).
There was no single established method to identify poverty areas in the mid-1960s. However, earlier in the decade, ERS researchers developed poverty area methodologies for identifying the extent and persistence of poverty in rural areas.33 They consisted of relative composite indices, which aggregate multiple variables into a single number that can be used to determine an area's position from the lowest to highest levels of economic well-being in society. For instance, if an area was positioned in the lowest quartile of index scores then it was categorized as a poor area. Such indices serve as a means to capture the complexity and persistence of poverty by highlighting additional deprivations experienced by area residents. They may include measures of income, population age structure, housing conditions, employment status, and educational attainment. ERS built upon this work with its contributions to the seminal Rural Commission report 'The People Left Behind' (1967) and research volume "Rural Poverty in the United States" (1968). In those publications, rural poverty areas were defined at the county-level.34 ERS researchers continued to use an index approach for county-level poverty area measurement up until the early 1980s.
The Census Bureau published a technical report 'Characteristics of Families Residing in Poverty Areas' (1966). It outlined an index approach similar to that used by ERS, but with variable selection based on relevancy to the urban context. The spatial scale for this work was census tracts within metropolitan areas. A series of more in-depth reports on metropolitan areas followed 1967-1972.35 Over that period, the Census Bureau transitioned from the use of a relative composite index to an approach based on a single variable - an area was defined as poor if it had an OPM poverty rate of 20 percent or more. The poverty rate cut-off was selected after Census Bureau research showed that on average previously designated metro poverty areas had an OPM poverty rate of 20 percent or more while the average for their non-poor counterparts was below 20 percent. Since then, the Census Bureau has consistently published poverty area reports for the entire country using the same approach,36 which is often referred to as an absolute measure. That is, an area’s poverty status is not determined by its economic position relative to society as with the former index approach, but rather it is solely based on a pre-defined level of disadvantage as measured by an absolute poverty rate cutoff.
Evolution of definitions of persistent poverty areas
USDA rural poverty area researchers at ERS and within the Rural Development mission area have historically focused on measuring poverty at the regional or county level and have emphasized the duration of high poverty as an important indicator of spatial distress. The Census Bureau and other federal entities with an interest in urban issues have leaned toward measures based on other geographical units while often considering current rather than an extended period of time. A number of factors have influenced these differences in measures across federal agencies, such as the geography of economic regions, spatial location of administrative and other governmental bodies, and issues of special interest to a particular agency or program. However, the timing of the publication of nationwide poverty estimates and the spatial scale at which rural and urban data were produced were driving forces behind poverty area measurement decisions up until at least 1990.37 Spatial poverty measures for rural areas, such as ERS’s seminal persistent poverty classification discussed below, were developed at a time when the county was the lowest geographic unit for nationwide coverage. In 1985, ERS published the first formal classification of persistent poverty areas ever released by a federal agency, based on the characteristics of current (1979) OMB designated nonmetropolitan counties.38 Persistent poverty counties were defined as those in the lowest quintile of per capita income among all U.S. counties in each of the years 1950, 1960, 1970, and 1980.39 Per capita income was chosen as a comparable measure of economic well-being in absence of an official poverty measure. Considering the policy context over the same timeframe and the characteristics of persistent poverty counties compared to others, ERS researchers noted that:
Persistent poverty counties are among those affected disproportionally by various federal and state programs directed against poverty. However, such programs over the past three decades have not been enough to move people in these counties into the mainstream of economic activities.40
In 1994, ERS published an expanded and revised version of the 1979 county classification (commonly the ERS Typology).41 The effort reflected the need to be consistent with observed changes in the economy and society as well as federal statistical reporting practices. This included a shift in the persistent poverty methodology to an absolute measure based on an OPM poverty rate cutoff (similar to the earlier shift made by the Census Bureau). Sensitivity analysis was conducted to determine a useful cutoff for nonmetro counties. Persistent poverty status became defined by a county poverty rate of 20 percent or higher in each of the Decennial Census years 1960, 1970, 1980, and 1990. ERS has continued to use the 1994 methodology, updating the years to cover a sliding three-decade span (baseline plus three evaluation periods).42
- Resource: ERS County Typology Codes
Analysis of the 1994 persistent poverty counties found that the distinct regions of persistent poverty of decades prior (Central Appalachia, the Black Belt, the Mississippi Delta, the Southwest borderlands, and Native American lands), and their racial and ethnic disparities, remained prominent. This would be true of subsequent updates to ERS’s persistent poverty county list - the number of counties declined somewhat over time, but the geography and demography changed little. 43
These findings are interpretable. Economic growth in the 1950s and 1960s and the series of federal efforts from the Great Society programs changed the landscape of poverty dramatically.44 Poverty rates fell nationwide during the 1960s and early 1970s then leveled out through the 1980s. By 1990, poverty rates had improved almost everywhere, and the national poverty rate had fallen well below the 1960 rate of 22 percent to 13 percent. The most dramatic reductions in poverty took place between 1960 and 1970 with an average county poverty rate decrease of nearly forty percent nationwide. Counties with poverty rates above 20 percent in 1960 experienced the largest decennial poverty rate decreases, yet more than one-third remained above the 20 percent cutoff in 1970. 45
Illustration: High poverty counties over time interactive and static maps
Since 1970, aside from minor changes coinciding with macroeconomic conditions, poverty rates have remained stable for the majority of counties. There have been exceptions where, for some counties, poverty rates have continued to drop significantly since 1970. However, the opposite trend of rising poverty rates has also occurred. For example, in many counties with high concentrations of Native Americans, poverty rates have gone from a level that is considered high (20 percent or more) to one that is generally considered to be extreme (40 percent or more).46
Illustration: Spatial concentration of Native American and Alaska Native poverty using a racial and ethnic typology of high poverty counties
25 This and the following statements in this section are supported by an extensive body of scholarly literature on concentrated poverty and neighborhood effects. See for example: Kuhn, (2005); Jargowsky, (2013) Meade, (2014).
26 This phenomenon is often referred to as 'double poverty exposure' and the outcome 'poverty amplification' or 'compound deprivation.' The research on the impacts of double exposure to poverty are mixed. It is difficult to tease out cause and effect given the circularity and complexity of locational poverty and individual poverty. Yet there are ample correlates to support that the impacts can be significant, particularly for children that have been exposed for the duration of their developmental years (for a seminal summary of this work see Brooks-Gunn et. al, (1997)). However, double exposure effects aren't limited to children; for an example of this research for the adult population see Ludwig, et. al, (2012).
27 USDA Economic Research Service, 1995. Understanding Rural America, Agricultural Information Bulletin #710.
28 For a full discussion of the War on Poverty history, policies, and impacts see: Haveman et al., 2015. The War on Poverty: measurement, trends, and policy. Journal of Policy Analysis and Management, 1 (46).
29 Sawhill, I., (1988). Poverty in the U.S.: Why is it so persistent? Journal of Economic Literature, 26(3): 1073-1119.
30 The Office of Economic Opportunity (OEO) was established in 1964 as an independent agency and was responsible for administering most of the War on Poverty programs.
31 For more information, see The development of the Orshansky poverty thresholds and their subsequent history as the U.S. Official Poverty Measure.
32 For information on how this directive was implemented see the related Census Bureau page.
33 ERS developed similar indices for low-income and low levels of living agricultural and rural areas. This work is referenced in many early 1960s reports, including: USDA Economic Research Service, Agricultural Information Bulletin #234 by Inman, 1960 and Agricultural Economic Reports: #63 by Bird, 1964 and #79 by Cowhig, 1965.
34 At that time, anything outside of a Census defined urban area was considered rural. Rural census tract geography did not exist (urban census tracts were defined for select metropolitan areas in combination with urban area geography). Therefore, county-level geography was chosen and 'rural' was defined as the balance of the county population and land area that was not urban.
35 See for example Trends in social and economic conditions in metropolitan areas (1969). And Trends in social and economic conditions in metropolitan and nonmetropolitan areas (1970).
36 See for example: Changes in poverty rates and poverty areas over time: 2005 to 2019, which compares county poverty rates spanning three consecutive time-periods covering fifteen years and Census tracts defined as poverty areas based on a 20 percent cutoff.
37 The architecture of Census geography that we have today was in its infancy in the 1960s. The Census Bureau delineated urbanized areas 'to provide a better separation of urban and rural population in the vicinity of larger cities.' Basically, rural consisted of anything that was not urban. For highlights on the various measures of rurality, see the Rural Definitions and Measures Tools section of the Equitable Data Toolkit. For a full description of current Census geography see Guidance for geography users. For further explanation of urban and rural population designations in the 1960s see 1960 Census supplementary report on the population of urbanized areas (1961).
38 For discussion of the original ERS persistent poverty county type, see the USDA Economic Research Service, Rural Development Research Report, RDRR #49, The Diverse Social and Economic Structure of Nonmetropolitan America, 1985. Reports contributing to the 1985 persistent poverty county definition included: USDA Economic Statistical Cooperative Service, Rural Development Research Report, RDRR #12, Persistent Low-income Counties in Nonmetro America, 1979 and USDA Economic Research Service, unpublished staff report, A Decade of Change in Persistent Low-income Counties, 1981.
39 This reflected Decennial Census income years (1949, 1959, 1969, and 1979) with the earlier years pre-dating the OPM.
40 Bender, L.D, Green, B.L., Hady, T.F., Kuehn, J.A., Nelson, M.K., Perkinson, L.B., and Ross, P.J. (1985). The Diverse Social and Economic Structure of Nonmetropolitan America. USDA Economic Research Service Rural Development Research Report, 49:15.
41 For more information see the USDA Economic Research Service, rural development research report, RDRR-89, The revised county typology: an overview, 1994.
42 ERS updates the 1994 persistent poverty list every decade, maintaining the methodology that spans three decades by using four decennial years. In 2005, the Census Bureau changed the income and poverty data collection from the Decennial Census to the American Community Survey (ACS). Since then, nationwide OPM poverty statistics have been reported on a rolling 5-year basis (see Section 3). The 5-year ACS period that most corresponded to what would be the next decennial census income year (2009) was 2007-2011. The subsequent ERS persistent poverty county update included 1980, 1990, and 2000 decennial census data and 2007-2011 ACS 5-year estimates. The next update will take place following the release of the 2017-2021 ACS 5-year estimates.
43 For a discussion of the correlation between persistently high regional poverty and race and ethnicity, see Beale, 2004, Anatomy of nonmetro high poverty areas: common in plight, distinctive in nature, Amber Waves, USDA Economic Research Service.
45 This is demonstrated by a 2017 update to the 1967 ERS poverty area map as it appears in the Rural Commission report. Research by T. Farrigan, B. Weber, and A. Glasmeier presented at the Rural Poverty Research Institute conference: Rural poverty, 50 years after the People Left Behind - a research conference, looking backward and forward, March 2018.
46 Research suggests that Native Americans residing on tribal lands, such as residents of the nine reservations in South Dakota, have not had the same success as others in accessing federal resources. For example, according to ERS analysis (Farrigan 2022) the poverty rate for Jackson County, SD, which contains part of the Pine Ridge Reservation, increased by more than 70 percent between 1960 (decennial Census poverty rate 26.4%) and 2019 (2015-2019 5-year ACS poverty rate 45.5%). The Department of Housing and Urban Development notes that about one-third of reservation homes lack electricity, adequate plumbing, and running water. In their Fiscal Year 2017 Congressional Justifications report it is emphasized that 'lack of housing and infrastructure in Indian country is severe and widespread.'
Persistent poverty area indicators are embedded in recent federal policy
Since the 1990’s, other federal agencies have widely adopted ERS’s measure of persistent poverty, or some variation of it. A measure akin to ERS’s appeared in federal legislation in the American Recovery and Reinvestment Act of 2009 (ARRA, P.L. 111-5). The ARRA addressed how USDA was to allocate appropriated funds to three rural development programs. The legislation required USDA to allocate at least 10 percent of funds to persistent poverty counties, which the ARRA identified using a poverty rate of 20 percent or more for each Decennial Census year from 1980 to 2000; the definition in ARRA used one time period fewer than ERS’s definition but referred to the time period as a span of 30 years. The ARRA provision became known as the 10-20-30 provision. Since ARRA, the 10-20-30 provision has been applied to other federal programs outside of rural development and updated to include more current data.
The Consolidated Appropriations Act of 2021 (CAA-2021, P.L. 116-260) updated and redefined the 10-20-30 provision definition of persistent poverty counties. The CAA-2021 also expanded the focus on poverty areas to include high poverty Census tracts, identified by a poverty rate of 20 percent or more for a single time period.47 Altogether, CAA-2021 includes multiple definitions of persistent poverty in conjunction with the Act’s provisions to various federal agencies and initiatives (see Appendix table 2 for links to specific policies).
A feature of these definitions is that they combine geographic levels of counties and census tracts. The poverty concept used for census tracts in CAA-2021 is high poverty measured by a 5-year average (from the American Community Survey) in contrast to the multiple decades that are used for defining persistent poverty at the county level. There is growing demand for persistent poverty measurement at the census tract level. In 1990, the Census Bureau first assigned census tract geography to the entire nation and collected tract-level income and poverty data for all tracts (for more information see ). With the additional years of nationwide tract-level data now available, persistent poverty measures for census tracts can be constructed and have begun to be adopted by federal agencies.48 A challenge with defining the census tract rather than the county as the geographical unit is that the tract level can involve greater methodological complexity, as discussed in Section III below.
Diversity of persistent poverty area indicator uses by federal agencies
Persistently poor areas are generally defined by a high proportion of residents with incomes below the federal poverty level over multiple decades (see for example, ERS Poverty Area Measures definitions and others in Appendix tables 1 and 2). By this definition, persistent poverty for an area is both systemic and enduring. Persistent poverty reaches beyond economic well-being to also encompass social, demographic, political, cultural, and environmental outcomes of interest. As such, persistent poverty indicators produced by ERS or others are relied upon to target, implement, and monitor federal initiatives aimed at addressing a wide range of issues. They are used by grants and programs designed to assist with educational and employment opportunities, health care services and healthy food access, transit service and community facilities improvements, housing assistance and land development loans, fiscal health and administrative capacity of local governments, energy savings and climate change resilience, and aid to underserved groups.
Appendix table 2 provides a summary of federal agencies that use persistent poverty area indicators in their programs and granting initiatives and, where available, links to their definitions and data resources. The summary is not exhaustive but illustrative of the diverse programs across the federal government. As application of persistent poverty indicators has become more common across the federal government, it has been accompanied by the development of tools that can assist stakeholders with determining their persistent poverty status and with obtaining corresponding socioeconomic and demographic information.
- Resource: ERS Poverty Area Measures data product
Alternative concepts and indicators
There are a number of other spatial indicators of economic well-being used in federal program implementation and research. In some cases, federal programs establish multiple eligibility criteria using several single-dimension indicators such as income, poverty, health, education, or housing quality.49 They may also include geographic and demographic metrics to reflect known disparities, such as rural/urban designations and race/ethnicity. Others aim to capture multiple dimensions of areawide economic hardship and material deprivation in a single indicator, such as an index (see for example, the Appalachian Regional Commission’s index-based system for classifying economic distress in Appalachian counties).
- Resource: Link to Rural Definitions and Measures Tools
- Resource: Link to Race and Ethnicity Tools
These indicators are typically used as relative measures similar to early persistent poverty indicators as previously described, while contemporary persistent poverty indicators use a poverty rate cutoff constructed from the official poverty measure, which is an absolute measure. They are conceptually different in that the former is based on the comparative economic status or standard of living in society as a whole, whereas the latter is based on a threshold meant to reflect a minimum acceptable level of economic well-being.
The relative multidimensional approaches used in the federal government today closely resemble those used in the past. Most of these originated in the 1960s, stemming in large part from the Public Works and Economic Development Act of 1965 (PWED) and have since changed little if at all. The PWED states that to be eligible for assistance a project must be located in an area that meets one or more of the following criteria:
- Low per capita income - the area has a per capita income of 80 percent or less of the national average.
- Unemployment rate above national average - the area has an unemployment rate that is, for the most recent 24-month period for which data are available, at least 1 percent greater than the national average unemployment rate.
- Unemployment or economic adjustment problems - the area is in an area that has experienced or is about to experience a special need arising from actual or threatened severe unemployment or economic adjustment problems resulting from severe short-term or long-term changes in economic conditions.
The PWED is directly referenced by multiple federal programs while other programs use a similar design though not directly referential. Examples are listed in Appendix table 3.
47 This is akin to many of Census Bureau’s post 1970 publications on poverty areas. For example, Census Bureau reports published in 1995, 2005, 2011, 2014, and 2020 analyzed high and concentrated poverty census tracts.
48 The National Institute of Health, National Cancer Institute recently developed and implemented a census tract measure of persistent poverty (using an updated version of ERS’s county methodology) for grants and program use. See Cancer control research in persistent poverty areas.
49 For an example of variable selection from the American Community Survey see A multidimensional poverty measure using the American Community Survey.
Developing a measure of persistent poverty or understanding an existing measure better for programmatic or research purposes involves several key considerations. They can be summarized in a conceptual framework that is introduced here using four D’s: Data, Duration, Depth, and Decisions. With a focus on the Official Poverty Measure, which is prominent in current federal methodologies, the discussion of the 4-D Framework for Persistent Poverty Measurement examines each factor in turn. The issue of spatial scale, which is embedded in each of the four D’s, is discussed as well.
Data – available sources
Ultimately, any methodological considerations depend on the nature, strengths, and limitations of the data that are available. Federal data resources that can help meet the need for multiple years of spatial poverty statistics include Decennial Census data, the American Community Survey 1- and 5-year estimates (ACS), and the Small Area Income and Poverty Estimates (SAIPE).
Decennial Census. The Decennial Census is a national survey that dates back to 1790, but its content has changed over time. Between 1970 and 2000 the Decennial Census collected certain demographic and housing information from the entire population using what was called the short form. A subset of the population – about one in six households – answered a second questionnaire, called the long form, that collected more detailed information including data on income that were used for measurement and analysis of poverty.50 The long form was eliminated following the 2000 Census with the advent of the American Community Survey, which posed those questions and others on an ongoing basis instead of once each decade.
A benefit of the Decennial Census is that it has an extensive selection of geographies and the availability of corresponding demographic, socioeconomic, and housing characteristics. However, it meant that county level poverty estimates based on the Decennial Census were only available every ten years from 1960 (poverty measures were added post Census) through 2000. Similar data at the census tract level are also available for the entire country for 1990 and 2000.
- Resource: Decennial Census Geographies
- Resource: Decennial Census Data sets
- Resource: Historical County Level Poverty Estimates Tool
American Community Survey (ACS). In 2005, the American Community Survey replaced the Decennial Census long form. The ACS is an annual, nationwide survey with a sample size of about 3.5 million addresses across the 50 states and Puerto Rico. One of the main purposes of ACS is to help Congress determine funding and policies for a wide variety of federal programs. To do so, the ACS includes a diverse set of social characteristics (e.g., disability, educational attainment, language spoken, and veteran status), economic characteristics (e.g., employment status, health insurance, income, and earnings), housing characteristics (e.g., computer and internet use, monthly owner costs, rent, year structure was built), and demographic characteristics (e.g., age, sex, race, Hispanic origin, and relationship to householder). It also includes a rich set of geographies: nation, states, congressional districts, counties, places, census tracts, and other localities.
ACS is used to obtain one-year estimates for select geographies (that are sufficiently large to support statistical estimates based on a single year of data) and five-year estimates (which pool data across 5-years to generate period averages) for all geographic areas down to the census tract and block-group levels. The Census Bureau recommends that a comparison of five-year estimates over time for a given geographical unit be limited to five-year periods that do not overlap (see How should users compare 5-year estimates? at Census.gov); a comparison of overlapping five-year periods would include one or more years of the same data, which would make interpretation of the comparison problematic. The release of the 2015-2019 estimates represented the first time that three consecutive non-overlapping five-year periods were available, thereby offering trend data for most Census geographies for a combined 15-year period. All ACS data products can be found on Census' digital data platform.
- Resource: American Community Survey, Multiyear Accuracy of the Data
- Resource: Census data digital platform
The choice of using ACS or Decennial Census data can influence the measurement of persistent poverty areas. The two data sources use different timeframes for measuring income and the population bases differ somewhat. The Census Bureau offers a summary of these differences and guidance about making comparisons across the two data sources for temporal analysis. Census also provides to ACS users a series of special topic handbooks, which include handbooks targeted for federal agencies and for researchers.
- Resource: Differences between the ACS and Decennial Census
- Resource: Handbooks for ACS Data Users
Small Area Income and Poverty Estimates (SAIPE). The Small Area Income and Poverty Estimates program of the Census Bureau offers annual estimates of income and poverty statistics for all states, counties, and school districts. Its main objective is to provide poverty and income estimates for the administration of federal programs and the allocation of federal funds to local jurisdictions. The estimates are available for 1993 then annually from 1995 to present. The details of SAIPE methodology differ year to year. In general, income and poverty for states and counties are modeled estimates derived from a combination of Census population data and poverty inputs from surveys, specifically the Current Population Survey up until 2004 and ACS onwards, and administrative records. Therefore, they are not direct counts from enumerations or administrative records, nor are they direct estimates from sample surveys.
- Resource: Small Area Income and Poverty Estimates Program
- Resource: Income and Poverty Interactive Data Tool
The main appeal of SAIPE is that it provides single-year estimates that are updated annually; in contrast, the ACS provides estimates based on five-year period averages (for most substate geographies). New five-year ACS estimates are released by the Census Bureau annually, but four of the five years will be the same as in the previous year’s five-year period average. SAIPE estimates also generally have lower variance than ACS estimates. Census data user guidance notes that for counties and school districts, particularly those with populations below 65,000, SAIPE provides the most accurate subnational single-year estimates of poverty. Typically, SAIPE estimates are most useful when single year poverty estimates for all ages, ages 5-17, or less than age 18 for US counties or for ages 5-17 at the school district level are desired. SAIPE is the only complete source for these estimated domains. The Census Bureau provides guidance for data users that desire poverty estimates for other subgroups characteristics and geographies.
- Resource: Which data source to use for poverty
- Resource: Differences between available surveys/programs for poverty
Limitations of SAIPE include substantially fewer geographic scales than the Decennial Census or ACS and the lack of supplemental variable selection that exists with the other data sources. However, the limitation that may be most impactful when considering whether to use SAIPE is technical. The modeling methodology results in numerous cautions about the use of the estimates, which have implications for persistent poverty area measurement. For instance, correlations amongst the estimates should be taken into account to provide a more accurate test for significant year-to-year changes. Some data years are more concerning than others, for example, when considering transition years from the use of CPS to ACS in the models. SAIPE technical details, cautions, and guidance are available on the Census Bureau website for those with at least moderate statistical expertise.
A summary of data options is provided below to assist with making data year/source selections.
County level- For years 1990 or earlier, Decennial Census.
- From 1995 to 2005, annual SAIPE and 2000 Decennial Census.
- From 2005 to present, annual SAIPE and ACS 5-year period estimates, beginning with 2005-2009 (use of non-overlapping 5-year periods recommended).
- For years 1980 or earlier, tract geography does not exist for the entire nation, but what does exist is available through the Decennial Census. Additional census tract geographies and poverty estimates derived from and available through various data sources are also an option (use with caution). This issue and alternative data sources are discussed below, under the spatial scale heading.
- From 1990 to 2000, Decennial Census.
- From 2005 to present, ACS 5-year period estimates, beginning with 2005-2009 (use of non-overlapping 5-year periods and consideration of margins of error recommended, also discussed later with spatial scale).
Duration – appropriate timeframe
Federal data users often seek definitive answers about the appropriate timeframe for persistent poverty area measurement. Yet, the temporal scale for any poverty area measurement is context specific, depending on the poverty phenomenon of interest and purpose.
Research. ERS’s 1985 persistently low-income county type and subsequent persistent poverty county type (beginning in 1994) differ by the specific indicator of well-being and the use of a relative or absolute approach, but they both use four data points spanning 30 years. The decision for this approach was driven by the availability of data and by the research context. Specifically, ERS researchers sought to examine spatial trends in poverty over as long a period as possible, with a particular interest in examining the distributional impacts of 1950s and 1960s economic prosperity trends, the War on Poverty initiatives, and related issues of interest to ERS such as agrarian technological change and trends in migration. More generally, there was an intention to provide researchers and federal stakeholders with tools to inform and evaluate federal policies and programs. At the time, the sole data source available for long-term analysis with sub-state geography was the Decennial Census.51
The original motivation for the measurement of persistent poverty was to examine the endurance and distribution of high poverty rates over as long a time as possible. From this specific research perspective, it could be argued that the methodology might be to maintain or extend rather than shorten the persistent poverty timeframe used by ERS.
Policy objectives. Poverty area measurement as applied in the federal context has been tailored to specific policy objectives. This is demonstrated by the 10-20-30 provision of the ARRA and the CAA-2021, which were discussed in Section II. The persistent poverty area methodologies defined in those legislative acts are very similar to ERS’s. The main difference is that they use three data points instead of four. A result of using fewer data points is that more areas can meet the persistent poverty criteria because an area would not have to exhibit high poverty for as many consecutive points in time.
Decisions about the number of data points to include in the persistent poverty area definition can be used to expand or contract inclusivity. Broad policy objectives meant to reach a large contingency of places in need might consider fewer data points.
Also similar to ERS’s definition is that the persistent poverty measures of the Acts are described as spanning thirty years. Yet some use a shorter time span, while others use a potentially longer time span. For instance, the rural development definition that appears in the 10-20-30 provision and CAA-2021 (table 1,) uses three data points including 1990, 2000, and 2007-11. They are approximately equally spaced apart, by about 10 years, considering the transition from Decennial Census data to ACS 5-year estimates. The time span between the first and the last data point is 20 years. In comparison, the public works definition of the CAA-2021 (table 1) also uses three data points including 1990 and 2000. The third data point is stated as the most recent Small Area Income and Poverty Estimates. The most recent SAIPE to date is 2021, meaning that the public works definition uses three data points, unequal distances apart, spanning more than thirty years. Given that SAIPE is updated annually, the time span for this definition will increase annually.
A potential result of annual updates is that the persistent poverty status of some areas, particularly those with poverty rates nearest to 20 percent, will fluctuate. Poverty rates can change rapidly from year to year due to cyclical changes in the macroeconomy, causing short-term economic difficulty or improvement. Research has shown that this is especially problematic for rural manufacturing and natural resource-based economies that rely heavily on one relatively unstable industry.
Cyclical economic trends, which last a little more than five years on average, should be taken-into-account when evaluating change in PPA status to ensure that the change captured represents permanence rather than fluctuation.
Program needs. Persistent poverty area indicators are often constructed to reflect the specific needs of federal programs, hence the diversity shown in Table 2. Many adopted persistent poverty area indicators before any definition had appeared in federal legislation, while others developed their own following the 10-20-30 provision of the ARRA, even though their program areas did not fall under rural development. The lack of uniformity of definitions found in CAA-2021 (Table 1) is likely influenced by the need to conform to the definitions already embedded in specific program areas. Since the 10-20-30 provision was first introduced, which targets persistent poverty counties, there has been widespread recognition that counties are not the appropriate unit of geography for all situations. Communities with entrenched concentrations of poverty can fail to meet program eligibility because they exist within counties that do not meet the criteria for persistent poverty status. This led to a search of more nuanced targeting mechanisms that can identify the diverse array of persistently poor communities across the nation. One result has been the adoption of census tract level poverty area measures in place of or in addition to county level persistent poverty area measures.
All of the census tract level poverty area measures that appear in legislation to date are defined by one data period. Very few program agencies have developed and implemented persistent poverty area census tract indicators. The lack of availability of comparable tract level data over the long-run and methodological complexities, as discussed in Section II and elsewhere in this report, can create hindrances. The use of one data period, however, can be problematic if the program goal is to address long-term economic difficulties.
The nature of economic difficulty associated with the persistent poverty phenomenon is systemic. There are fundamental structural differences between persistently poor areas and their counterparts. Allocating aid using one data period (single-year or a multi-year average) or multiple data points in the short-run may provide a misleading picture of long-term economic well-being. Research has found that a timeframe of less than five years results in estimates that do not represent well the phenomenon of persistent poverty (as measured using four time periods of data spanning thirty years). This research stems from the concentrated neighborhood poverty and resource economics literature. For instance, the characteristics most associated with persistent poverty are not especially prevalent in chronic or short-term concentrated poverty areas.52
The poverty area indicator chosen to target aid ought to vary depending on the nature of economic difficulty that the program is meant to address. A timeframe equal to or spanning beyond thirty years is feasible and useful when there is interest in areas with historical legacies of poverty-related conditions.
Depth - poverty rate cutoff
As discussed in Section 1, fifty years ago the Census Bureau first used a 20 percent cut-off for the OPM poverty rate to measure depth of area poverty. The decision was based on correlation between such a measure and the metropolitan area poverty status derived from a multi-dimensional index measure of economic well-being. About 20 years later, ERS was considering its own study of poverty rate cutoffs relative to nonmetro counties and decided to use a 20 percent cutoff as well.
More recently, the contemporary relevance of the 20 percent cutoff was tested as part of a ‘50 years later’ exploratory update to the ERS poverty area research that appeared in the seminal 1967 People Left Behind report on rural poverty. Using the 1967 relative index methodology and data from the 2012-2016 American Community Survey five-year estimates, ERS researchers found that the corresponding OPM poverty rate for nonmetro and metro poor counties was about 22 percent and 18 percent, respectively. This finding suggests that when considering the conceptual and methodological groundwork for persistent poverty area measurement, a 20 percent OPM cutoff is appropriate to the combined metro/nonmetro persistent poverty county designation today.
The 20 percent poverty rate cut-off is widely adopted for high and persistent poverty area measurement; it is regarded to be relevant to rural (nonmetro) and urban (metro) areas.
Over the same timeframe (approximately 1970 to 2020) research by some academic researchers also suggest that 20 percent is the critical poverty rate cutoff at which residents begin to experience the impacts of area-wide poverty.53 Those impacts appear to be greater at even higher poverty rates, raising the question of whether a "critical impact" point might exist above 20 percent. These effects tend to plateau or slow significantly beyond a 40 percent poverty rate, which is commonly referred to as the threshold of extreme poverty.
The 40 percent poverty rate cut-off, or extreme poverty area indicator, has been used widely in academic research. It has not received as much attention by federal researchers, nor has it been adopted widely for use with federal programs, but it has been growing in popularity as of late.
It is possible that a poverty rate just above the 20 percent threshold over multiple decades may be more damaging to areawide well-being and thus have greater potential to impact residents than a poverty rate nearing the extreme threshold of 40 percent for just a few years. The long-term erosion of government financial resources in the face of a limited residential tax base is one such scenario. Given these considerations, the 20 percent poverty rate seems a reasonable and defensible threshold for identifying high spatial poverty.
The 20 percent poverty rate cut-off is typically applied in federal policy and research as >= 20.0 percent. Different rounding options are often discussed but to date have failed to impact standard practice.
Spatial scale – counties and census tracts
Historically, persistent poverty areas have been defined at the county level. Even so, persistent poverty can be measured at any spatial scale for which appropriate data are available. Demand for sub-county measures has grown in recent years, bringing increased attention to census tract data (often used as a proxy for neighborhoods). As previously noted, these data have been available for the entire nation since 1990, initially based on the decennial Census followed by the ACS (as five-year estimates).
There are special considerations with tract level data, including how boundaries of census tracts change over time much more than do boundaries of counties. Many statistical areas (like census tracts and block groups) are updated once per decade to reflect the most recent Decennial Census. Census tract geography can change dramatically from one decade to the next making temporal comparisons difficult. In order to maintain the greatest geographic coverage when constructing a persistent poverty area indicator, the geographic normalization of tract level data over time should be considered. There is no set methodology for normalizing data, but tutorials for doing so exist as do options to use open access data or to purchase proprietary normalized census tract datasets from private vendors.
- Resource: Updates to census tract boundaries and how to compare them decade to decade
- Resource: Longitudinal tract database tutorial
- Resource: International Historical Geographic Information System
County geography also changes periodically, sometimes with the addition of new counties or the splitting of old ones or the annexation of counties or county equivalents. While the change in county geography is less problematic than it is with census tracts, attention must be paid to this issue when constructing a persistent poverty area indicator, particularly in the case of Alaska where the county-equivalent geography has changed in every decade since statehood. The Census Bureau provides a list of these geographic changes by decade beginning with 1970, though note that there is no authorized recommendation for comparing county-level updates as is true for census tracts.
Another issue with census tracts, and to a lesser degree with counties, is the error of the estimates, often measured in terms of margin of error (when using survey data). Poverty estimates for smaller geographies have higher margins of error. If there is a desire to subset the population into smaller groups, such as by race, then the magnitude of error increases and the estimates can be highly unstable. Data error estimation and interpretation for Decennial Census sample data (long form) requires some degree of statistical expertise. Conversely, the Census Bureau provides calculated margins of error for all ACS estimates (all geographies) and guidance on how to use them, making it amenable to the beginner. Similarly, the Census Bureau also publishes SAIPE estimate (counties and school districts) confidence intervals.
Measures of uncertainty should be used when available. One common practice is to develop an index of reliability from the MOE’s. The index can be translated into a scale, such as low, moderate, and high reliability. This information can be used to inform decisions about whether poverty estimates for select geographies are reliable enough to report and analyze. There are several different versions of reliability indices used in the federal government, but for spatial analysis the most popular is that developed by ESRI (an international GIS software and applications supplier).
Another common practice is to use the MOE’s to estimate upper and lower bounds of the estimate (lower = estimate - MOE; upper = estimate + MOE). This provides information on the potential range of the estimate, within the margin of error. There is no standard practice on how to use this information, but when developing poverty area measures one option is to use it to determine if the MOE impacts the high poverty status of a given area. For instance, if the lower bound, the estimate, and the upper bound yield different poverty status outcomes (e.g., using a 20.0 percent cutoff) then caution should be considered when using that estimate for poverty area analysis and with interpreting findings. A less common practice is the opposite; to define an area as high poverty if any of the values (lower bound, estimate, upper bound) are 20 percent or higher. This is not recommended. The potential for false positives is high, particularly for census tracts. In general, when possible other measures of well-being, contextual information, and alternative data sources should be used to validate findings.
- Resource: Using ACS estimates and MOEs and additional resources
- Resource: ESRI importance of margins of errors and mapping
- Resource: Calculating margins of error the ACS way
- Resource: Suppressing unreliable observations and transparency of reliability
Decisions - putting it all together
There are numerous decision factors when producing a persistent poverty area indicator. The primary factors,55 as just described, should be considered in conjunction with the motivation and purposes of the end user. At first glance, it might seem that a user could select any one of the existing federal persistent poverty area methodologies, which for the most part do not vary substantially. However, even slight variation in methodology can change the make-up of the areas identified as persistently poor. This phenomenon can impact how well the policy or program is identifying its target population. For the counties and communities in need, difference in definitions and measurement can make the difference between the area being eligible or ineligible for federal funding. At the least, attention should be paid to data limitations and to the motivation and conceptualization of a particular measure. The decision- making exercise and ERS example provided below may help with this process.
Decision-making exercise.
A. Questions / answers that may be of help include, but are not limited to:
- Is the purpose of the persistent poverty indicator for research, meeting broad policy objectives, meeting specific program need, or a combination?
- Is the target population the most historically impoverished areas, chronically poor areas, newly or temporarily poor areas, or a combination?
- Is the interest only in persistent poverty, as traditionally measured using a high poverty rate cutoff (20 percent or more) or is persistent extreme poverty (40 percent or more) also of interest?
- Is a ten-year period between data points acceptable or desirable? Is there a need to consider an alternative (shorter, longer, or varying)?
- How important is it to have the most current, annual, single-year poverty rates?
- Is direct access and comparability of other socioeconomic, demographic, and/or housing variables important?
- Is the ability to determine reliability of the estimates a priority? If yes, what degree of difficulty in doing so is acceptable (novice, intermediate, or expert)?
- Is there a need for a census tract measure of high or persistent poverty, in addition to or instead of a county measure of persistence?
B. Once the answers to these and other questions (relevant to motivation, data limitations, concept) are established, as a next step, consider:
Reviewing the existing persistent poverty area definitions and poverty area measures in tables 1, 2, and 3, as well as ERS’s definition, to determine their potential for adoption.
If none of the existing measures are acceptable, keeping your answers in mind, revisit the data, duration, depth, and spatial scale discussions of Section III to be reminded of the various aspects of the decision process and what to consider in making decisions.
C. Also, consider consulting with other federal program agencies about the resultant persistent poverty area definition (adopted from existing definitions or uniquely designed) and their experiences with the same/similar/unique persistent poverty area indicators.
Example decision-making exercise related to ERS’s definition:
A. By answering the exercise questions, it was determined that in order to meet ERS’s primary research and secondary federal agency support needs, there are two fundamental (temporal) issues for determining persistent poverty area status and change in persistent poverty area status.
- Poverty should be measured over the long run to capture structural poverty rather than cyclical poverty, using a timeframe adequate to reflect extent of economic difficulty.
- Economic cycles should be taken into consideration when evaluating change, using a time span adequate for capturing permanent improvement or lack thereof.
B. Upon review of definitional options that might address the two issues, ERS’s decision was to continue to use the county-level methodology that was established in 1994:
Use a timeframe that spans thirty years, with a consistent 10-year time span between poverty indicator data points (baseline plus three evaluation periods) and updates.
Generate a comparable census tract level persistent poverty area indicator, allowing for within county analysis of persistent poverty.
C. Federal stakeholder consultation: Agencies with programs aimed at addressing persistent poverty directly or aimed at addressing various issues associated with long-term economic difficulty (e.g., access to healthcare) have reported that ERS’s approach works well. It captures areas consistent with program concerns and observed conditions. It limits cyclical variation in program eligibility status and provides a sufficient timeframe for program impact evaluation. A change to an update every five years (using non-overlapping 5-year ACS) or every year (using concurrent 5-year ACS or SAIPE) instead of ten would diminish the usefulness of the indicator.
50 The Census also collected sample data similar to the long form in 1940 and 1950, but collection of all information was done through a single form instead of two.
51 The Current Population Survey Annual Social and Economic Supplement (CPS ASEC) was/is another poverty data option. It is one of the oldest, largest, and most recognized surveys in the U.S. and serves as the data source for the Official Poverty Measure and the Supplemental Poverty Measure. However, the geography in the unrestricted public use files is limited. The Census Bureau recommends that it is best used for national and state-level (3-year averages recommended) analysis.
52 Gans, H. (2010). Two American problems: concentrated poverty, a critical analysis. Challenge: 53(3) 82-96.
53 See for example, Galster and Booza (2010) The mechanisms of neighborhood effects: theory, evidence, and policy implications. and Galster et al. (2006) The social costs of concentrated poverty.
54 A broad literature supports that the conditions found in persistent poverty and economically distressed areas make them less attractive to private sector investment, thereby discouraging private revitalization efforts and further decreasing the local government tax base.
55 The factors presented are those that are most critical to resultant persistent poverty area geography and counts. They are also the most representative of ongoing definitional debates and where there are differences in existing legislative language. However, there are additional discrete factors to consider, such as rounding decisions with respect to the poverty rate cutoff. This is less of an issue in terms of the impact on the persistent poverty area count. And as of the writing of this report this factor is uncontested in legislation – the language consistently references a poverty rate cutoff of 20 percent or more, which infers 20.0 percent or higher (not 19.9 percent).
Table 1. Consolidated Appropriations Act of 2021 poverty area definitions
Policy objective/program area | Geographic scale | Concept | Indicator of well-being | Data years included and sources |
---|---|---|---|---|
1. Rural development | county | persistent poverty | poverty rate of 20 percent or more | 1990 and 2000 Decennial Censuses and the 2007-2011 American Community Survey 5-year estmates |
2. Public works | county | persistent poverty | poverty rate of 20 percent or more | 1990 and 2000 Decennial Censuses and the most recent Small Area Income and Poverty Estimates |
3. Comprehensive environmental response, compensation, and liability | county | persistent poverty | poverty rate of 20 percent or more | 1990 and 2000 Decennial Censuses and the most recent Small Area Income and Povery Estimates |
4. Community develpment financial institutions | a. census tract | high poverty | poverty rate of 20 percent or more | 2011-2015 American Community Survey 5-year estimates |
b. census tract | high poverty | poverty rate of 20 percent or more | 2011-2015 American Community Survey 5-year estimates | |
c. county | persistent poverty | poverty rate of 20 percent or more | 1990 and 2000 Decennial Censuses and the 2011-2015 American COmmunity Survey 5-year estimates | |
d. county | persistent poverty | poverty rate of 20 percent or more | 1990, 2000, and 2010 Island Areas Decennial Census or equivalent data of the Bureau of the Census | |
5. Transportation in infrastructure | a. county | persistent poverty | poverty rate of 20 percent or more | 1990 and 2000 Decennial Censuses and the most recent Small Area Income and Poverty Estimates |
b. census tract | undefined | poverty rate of 20 percent moare | 2014-2018 American Community Survey 5-year estimates | |
6. Covid-19 pandemic reponse and recovery (emergency capital investment program) | a. communities | low- and moderate- income | unspecified | unspecified |
b. communities | underserved | unspecified | unspecified | |
c. counties | persistent poverty | unspecified | unspecified |
Table 2. Summary of federal agencies that use persistent poverty area indicators
Program, policy, or grant name | Administering department/ |
Issue(s) addressed | PPA spatial scale | Website |
---|---|---|---|---|
Areas of Persistent Poverty Program | Department of Transportation, Federal Transit Administration | Support planning, engineering, and financing to improve transit services in areas of long-term economic distress | Counties and census tracts | DOT FTA Areas of Persistent Poverty Program |
Bank Enterprise Award Program | Department of Treasury, Community Development Financial Institutions Fund | Provides formula-based grants to successful applicants for increasing Qualified Activities | Counties | DOT CDFI Bank Enterprise Award Program |
Community Development Financial Institutions Program | Department of Treasury, Community Development Financial Institutions Fund | The CDFI Program offers both Financial Assistance and Technical Assistance awards to CDFIs | Counties | DOT CDFI Community Development Financial Institutions Program |
Native American CDFI Assistance Program | Department of Treasury, Community Development Financial Institutions Fund | Financial Assistance and technical assistance awards are made to Native CDFIs. | Counties | DOT CDFI Native American CDFI Assistance Program |
Distressed Cities and Persistent Poverty Technical Assistance Program | Department of Housing and Urban Development | Improve fiscal health and build administrative capacity of relatively small units of general local government (UGLGs or local governments) and their nonprofit partners in places experiencing persistent poverty and economic distress. | Census tracts | HUD Distressed Cities and Persistent Poverty Technical Assistance Program |
Rural Community Development Grants | Department of Health and Human Services Administration for Children and Families’ Office of Communities Services | RCD grants support training and technical assistance for creating and maintaining safe and affordable water and wastewater systems in the nation’s lowest income rural communities, including tribal areas, many of which have populations at or below 2,500 individuals. | Counties | HHS ACF Rural Community Development Grants |
Expanding Cancer Control in Persistent Poverty Areas | Department of Health and Human Services, National Cancer Institute | Provide resources to support highly collaborative, multi-disciplinary Program Projects (P01s) that focus on the development and conduct of cancer control research in low-income and/or underserved populations living in persistent poverty (PP) areas. | Counties and census tracts | NIH NCI Expanding Cancer Control in Persistent Poverty Areas; includes link to census tract persistent poverty data |
Cancer control grants; Persistent Poverty Initiative; Cancer Control Research in Persistent Poverty Areas | Department of Health and Human Services, National Cancer Institute | Cancer control in designated NCI cancer centers and cancer control research to understand the causes and distribution of cancer in populations, support the development and delivery of effective interventions and monitor and explain cancer trends. | Counties | NIH NCI Cancer Control Research in Persistent Poverty Areas |
Rural Community Facilities Program; Community Facilities Grant | U.S. Department of Agriculture Rural Development | Provides affordable funding to develop essential community facilities in rural areas. | Counties | USDA RD Community Facilities Program |
Rural Business Program Account; Rural Business Development Grants | U.S. Department of Agriculture Rural Development | Provides technical assistance and training for small rural businesses. | Counties | USDA RD Rural Business Development Grants |
Rural Business Program; Rural Economic Development Loans Program | U.S. Department of Agriculture Rural Development | Provides funding for rural projects through local utility organizations. | Counties | USDA RD Rural Economic Development Loan and Grant Program |
Rural Business Program; Rural Cooperative Development Grants | U.S. Department of Agriculture Rural Development | Improves the economic condition of rural areas by helping individuals and businesses start, expand or improve rural cooperatives and other mutually-owned businesses through Cooperative Development Centers. | Counties | USDA RD Cooperative Development Grant Program |
Water and Waste Disposal Program Account; Water and Waste Disposal Loan and Grant Program | U.S. Department of Agriculture Rural Development | Provides funding for clean and reliable drinking water systems, sanitary sewage disposal, sanitary solid waste disposal, and storm water drainage to households and businesses in eligible rural areas. | Counties | USDA RD Water and Waste Disposal Loan and Grant Program |
Rural Electrification and Telecommunications Loans Program | U.S. Department of Agriculture Rural Development | Provides financing for the construction, maintenance, improvement and expansion of telephone service and broadband in rural areas. | Counties | USDA RD Telecommunications Program |
Distance Learning and Telemedicine and Broadband Program | U.S. Department of Agriculture Rural Development | Helps rural communities use the unique capabilities of telecommunications to connect to each other and to the world, overcoming the effects of remoteness and low population density. | Counties | USDA RD Distance Learning and Telemedicine Program |
Distance Learning and Telemedicine and Broadband Program; Delta Health Care Services Grant | U.S. Department of Agriculture Rural Development | Provides financial assistance to address the continued unmet health needs in the Delta Region. | Counties | USDA RD Delta Health Care Services Grant |
Rural Housing Insurance Fund Program; Direct Single Family Housing Loans | U.S. Department of Agriculture Rural Development | Assists low- and very-low-income applicants obtain decent, safe and sanitary housing in eligible rural areas by providing payment assistance to increase an applicant’s repayment ability. | Counties | USDA RD Single Family Housing Direct Home Loans |
Rural Housing Insurance Fund Program; Single Family Housing Repair Loans | U.S. Department of Agriculture Rural Development | Provides loans to very-low-income homeowners to repair, improve or modernize their homes or grants to elderly very-low-income homeowners to remove health and safety hazards. | Counties | USDA RD Single Family Housing Repair Loans |
Rural Housing Insurance Fund Program; Rural Housing Site Loans | U.S. Department of Agriculture Rural Development | Provides loans to acquire and develop sites for low- or moderate-income families, with no restriction as to the method of construction | Counties | USDA RD Rural Housing Site Loans |
Rural Housing Insurance Fund Program; Self-Help Housing Land Development Loans | U.S. Department of Agriculture Rural Development | Provides loans are to acquire and develop sites only for housing to be constructed by the Self-Help method. | Counties | USDA RD Mutual Self Help Housing Grants |
Rural Housing Insurance Fund Program; Mutual Self Help Housing Grants | U.S. Department of Agriculture Rural Development | Provides grants to qualified organizations to help them carry out local self-help housing construction projects. | Counties | USDA RD Mutual Self Help Housing Grants |
Rural Housing Assistance Grants; Rural Housing Preservation | U.S. Department of Agriculture Rural Development | Provides grants to sponsoring organizations for the repair or rehabilitation of housing owned or occupied by low- and very-low-income rural citizens. | Counties | USDA RD Housing Preservation Grants |
Table 3. Federal programs that use poverty area measures similar to the Public Works and Economic Development Act (1965)
Administering department/agency | PPA spatial scale | Website |
---|---|---|
Department of Commerce, Economic Development Administration (EDA) | Region | EDA Economic distress levels |
Department of Transportation, Federal Aviation Administration (FAA) | Community | FAA economically distressed areas special rule |
Appalachian Regional Commission | County and community | ARC distressed counties and areas |