ERS Charts of Note
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Monday, April 1, 2024
The USDA, Economic Research Service (ERS) has updated its Rural-Urban Continuum Codes (RUCC), which classify all U.S. counties into nine categories from most urban to most rural. The RUCC distinguish U.S. metropolitan (metro) counties by the population size of their metro area and nonmetropolitan (nonmetro) counties by their degree of urbanization and adjacency to a metro area. The RUCC allow researchers and policymakers to add nuance to their county-level analyses by incorporating the population of the Census Bureau’s urban areas with the OMB’s definition of metropolitan counties. The most urban counties belong to metro areas (shown in purple on the map). These are divided into three categories based on the total population of the metro area. Counties that are commonly considered rural are those that do not belong to metro areas (shown in green on the map). The RUCC classify these nonmetro counties into six categories based on the number of people who live in urban areas (small cities or towns) and whether the county is adjacent to a metro area. The most urban of the nonmetro counties are those that had urban area populations of at least 20,000 and are most prevalent in regions such as the Northeast, Great Lakes, and along the coasts. The most rural of the nonmetro counties had urban area populations of fewer than 5,000 and are the most prevalent in the Great Plains and Corn Belt. Counties classified as adjacent to metro areas are considered more urban than their nonadjacent counterparts because their residents have greater access to the diverse employment opportunities, goods, and services available in metro areas. For more information on the RUCC, please see the ERS data product Rural-Urban Continuum Codes.
Thursday, March 7, 2024
Both rural (nonmetro) and urban (metro) populations grew because of increased migration over the last few years; however, the sources of the increased migration are different. In 2020–21 and 2021–22, rural areas experienced an increase in population because more people moved from urban to rural areas than in the opposite direction, a reversal of domestic migration trends from the previous decade. Domestic migration occurs when people move among areas within the United States. Net domestic migration in rural areas jumped from near zero in 2019–20 to more than 0.35 percent in the last two years. Fear of exposure to Coronavirus (COVID-19) in urban areas and the subsequent increase in remote work contributed to this dramatic shift in migration patterns. Conversely, urban areas increased their population through migration from other countries. International migration to urban areas reached a peak of 0.34 percent in 2021–22. The growth in migration rates for both urban and rural areas are somewhat offset by elevated death rates (which are falling from pandemic highs) and lower birth rates. This chart is drawn from the USDA, Economic Research Service report Rural America at a Glance, published in November 2023.
Wednesday, March 6, 2024
Over the last two decades, disease-related (natural-cause) mortality rates have widened between rural and urban areas, especially for the prime working-age population (aged 25–54). Researchers with USDA, Economic Research Service (ERS) compared natural-cause mortality in rural and urban areas between two 3-year periods, 1999–2001 and 2017–2019. They found the gap between rural and urban natural-cause mortality rates widened between the two time periods. Natural-cause mortality rates decreased across all age groups in urban areas. In rural areas, mortality rates decreased for most age groups (although not as much as for the same groups in urban areas) but increased for the prime working-age population. The rural group with the largest increase (19 percent) in natural-cause mortality rates was 30- to 34-year-olds. Increased mortality rates for people who are of prime working age are an indicator of worsening population health, which could have negative implications for rural families, communities, employment, and the economy. This chart appears in the ERS report The Nature of the Rural-Urban Mortality Gap, published in March 2024.
Wednesday, February 21, 2024
The Coronavirus (COVID-19) pandemic affected employment in rural and urban areas differently. Before the pandemic, employment growth was higher and unemployment rates were slightly lower in urban areas. However, these trends reversed during the pandemic. In the second quarter of 2020, urban employment fell to 88 percent of prepandemic (Q1 2019) employment levels, while rural employment fell to 90 percent of prepandemic levels. Unemployment during the pandemic reached a high of 13.3 percent in urban areas and 11.4 percent in rural areas, compared with prepandemic rates of 3.8 and 4.2 percent, respectively. Rural and urban employment grew quickly in the third and fourth quarters of 2020 as many sectors of the economy reopened. Employment growth slowed in 2021, but more in rural areas than in urban. Urban employment recovered to prepandemic levels by the first quarter of 2022, and the urban unemployment rate dropped below the rural rate once again in the second quarter of 2022. Meanwhile, the slow employment growth rate in rural areas in 2022 (0.5 percent) was similar to rates in the years between the Great Recession of 2008 and the COVID-19 pandemic. From 2010 to 2019, the annual average employment growth rate in rural areas was 0.4 percent compared with 1.6 percent in urban areas. Rural employment recovered to prepandemic levels in the third quarter of 2023, more than one year after urban employment did. Rural unemployment rates in 2023 were at their lowest point (3.6 percent) since before 1990. This figure updates data in the USDA, Economic Research Service report Rural America at a Glance, published in November 2023.
Thursday, November 16, 2023
The rural (nonmetro) population growth that began with the Coronavirus (COVID-19) pandemic in 2020 continued into 2022, according to census population estimates. A sharp increase in net migration (the number of people moving in minus the number of people moving out) was the source of the growth. Migration to rural areas was 0.47 percent and 0.45 percent in 2020–21 and 2021–22, respectively, compared with 0.01 percent in the period before the pandemic. Overall, the rural population grew at 0.12 percent from mid-2021 through mid-2022 after accounting for the 0.33-percent decline caused by natural decrease (more deaths than births) in the same period. For rural areas, this recent growth is a reversal of population loss and near-zero migration in 2019–20 and comes after annual rural growth rates declined or were near zero in the previous 10 years. The population in metro areas followed a different trend in 2019–20 and 2020–21, dropping from 0.42 to 0.16 percent growth before returning to 0.42 percent in 2021–22. Roughly 46 million U.S. residents lived in rural areas in July 2022, making up 13.8 percent of the population. This chart is drawn from the ERS report Rural America at a Glance, published in November 2023.
Monday, November 6, 2023
USDA, Economic Research Service (ERS) researchers analyzed the share of each State’s population living in rugged terrain using the Road Ruggedness Scale, a five-category measure created by ERS that classifies census tracts based on elevation changes along roads. They found that in 2010, West Virginia led the Nation with 80.7 percent of its population living in areas classified as either slightly, moderately, or highly rugged. It was followed by Vermont (51.6 percent), Hawaii (43.3 percent), Pennsylvania (39.3 percent), and Washington State (38.0 percent). In 19 States and the District of Columbia, a greater share of residents lived in slightly to highly rugged census tracts than for the Nation as a whole (11.6 percent). For most States near the top of the list, a large share of residents lived in highly rugged census tracts (the highest ruggedness category), notably West Virginia, Hawaii, Oregon, and Montana. However, despite having no highly rugged census tracts, Vermont and Connecticut still have enough residents in slightly and moderately rugged census tracts to be among the top 10 States with the highest population shares in rugged areas. While topographic variation, or “ruggedness,” is visually appealing and may spur economic growth, it can also make it more difficult to navigate land and waterways and limits space for residential and commercial expansion. Residents living in areas with rugged terrain may also require more time to travel to hospitals, schools, social services, grocery stores, and other critical destinations compared with those living in less rugged locations. This chart is drawn from data in the ERS report Characterizing Rugged Terrain in the United States, published in August 2023.
Uphill climb: The share of rural residents living in low-income areas increases with road ruggedness
Wednesday, November 1, 2023
In 2010, a higher share of rural residents lived in low-income census tracts, especially in places characterized by rugged terrain. Researchers with USDA, Economic Research Service (ERS) classified census tracts (the small geographic areas used to collect population data) by the change in elevation along their roads to create the new Road Ruggedness Scale. Using this scale in conjunction with data on income and how rural a place is, they found that as ruggedness increased, the share of rural residents living in low-income census tracts increased. In contrast, the share of residents in low-income census tracts in urbanized areas decreased as ruggedness increased. Nearly 60 percent of residents in highly rugged rural locations lived in low-income census tracts in 2010, compared with 42 to 48 percent of rural residents in less rugged census tracts. However, fewer than 20 percent of residents in highly rugged, urbanized areas lived in low-income census tracts, compared with nearly 42 percent of urbanized area residents in level census tracts. In urban commuting locations, the share of the population living in low-income census tracts generally increased with ruggedness, but with more variation in the trend. This chart appears in the ERS report Characterizing Rugged Terrain in the United States published in August 2023 and uses data available in ERS’s Ruggedness Scale data product.
Monday, October 16, 2023
Researchers with USDA, Economic Research Service (ERS) developed the Road Ruggedness Scale—a five-category measure of topographic variability along roads—and used it to study the interplay of population, rurality, and ruggedness in the United States. They found that in 2010, as land became more rugged (had greater changes in elevation), generally more of the population lived in rural census tracts (the small geographic areas used to collect population data). For example, in level census tracts, the rural portion of residents was 16.1 percent, while the rural portion living in highly rugged census tracts was nearly double that amount (29.7 percent). The reverse was true for urbanized area census tracts, with the share of residents decreasing from 73.5 percent in level locations to 57.0 percent in highly rugged ones. However, even in the top ruggedness categories, most people lived in urbanized area census tracts, indicating that ruggedness and rurality are not synonymous. The relationship between ruggedness and rurality also varies by region. The rural population share in highly rugged census tracts of the Intermountain West (57.7 percent) and Appalachian Mountains (45.7 percent) was much higher than the national share of 29.7 percent, while the share in the Pacific Coast was much lower (18.6 percent). This chart appears in the ERS report Characterizing Rugged Terrain in the United States published on August 1, 2023.
Wednesday, August 2, 2023
USDA, Economic Research Service (ERS) has developed the Road Ruggedness Scale (RRS) to aid in understanding the unique role of rugged terrain as both a benefit and hindrance to the well-being of communities and their residents. The RRS has five categories based on changes in elevation along roads within census tracts (the small geographic areas used to collect population data). The census tracts are classified as: 1–level, 2–nearly level, 3–slightly rugged, 4–moderately rugged, or 5–highly rugged. Most census tracts have very little topographic variation, with 65.6 percent classified as level in the RRS. The next largest category is nearly level, with 22.4 percent of census tracts. The remaining 12.0 percent of census tracts are classified as slightly to highly rugged, and only 4.4 percent are classified as moderately or highly rugged. The RRS helps to identify landscape characteristics that may present an impediment to settlement and travel, such as the Appalachian and Rocky Mountains, the Pacific Mountain System, the Ozark and Ouachita Mountains, and the Black Hills. These geologic features can make it difficult for people living in rugged areas to access services. They can also attract tourists and prospective residents who prefer rugged terrain or are interested in outdoor activities. To our knowledge, the RRS is the first roads-only, detailed ruggedness measure with full nationwide coverage for the United States. It has the potential to contribute to research on links between the geography and well-being of individuals, especially those living in rural areas, as well as to other research and policy applications. This chart appears in the ERS report Characterizing Rugged Terrain in the United States, published in August 2023. The Road Ruggedness Scale data product published in September 2023.
Wednesday, February 1, 2023
Among racial and ethnic groups (not including non-Hispanic White) in rural areas, Hispanic workers often lead employment in the six largest rural industries. In 2019, Hispanic workers performed 14.4 percent of rural jobs in agriculture and 12.8 percent in accommodation and food services. In rural manufacturing jobs, 8.7 percent of workers were Hispanic; in government, 7.8 percent; in retail, 7.5 percent; and in health care and social assistance, 6.2 percent. Rural Black workers were more evenly distributed with 9.7 percent of the workforce in manufacturing, 9.4 percent in health care and social assistance, 9.5 percent in hotels and restaurants, and 8.8 percent in government. Black workers were less represented in retail (7.0 percent) and in agriculture (2.4 percent). Asian workers constituted less than 2 percent of the rural workforce in most industries, except for accommodation and food services (3.3 percent). Similarly, American Indian or Alaska Native workers represented less than 2 percent of rural employment in most industries except government (3.4 percent). This chart appears in the USDA, Economic Research Service report Rural America at a Glance: 2022 edition.
Wednesday, January 4, 2023
Human movements between places vary considerably across space, so their contribution to the spread of COVID-19 also varied spatially. For instance, some rural communities have long histories as recreation or tourist destinations and more established migration connections to larger cities. In examining county-to-county migration patterns, researchers organized nonmetropolitan (nonmetro) counties into four equal groups, or quartiles, based on the rate at which people moved to or from metropolitan (metro) counties. The counties in the lowest quartile (lightest blue on the map) have the weakest migration connections with metro regions, meaning few people move back and forth proportionately. Remote counties far from any metro region, such as in the central and northern Great Plains, fall in the lowest quartile. Those counties in the fourth quartile (darkest blue) have the strongest migration connectivity and are typically adjacent to metro centers, such as southern New Hampshire, along the Front Range in Colorado, and in parts of Texas adjacent to Houston, Dallas-Fort Worth, and San Antonio. However, some very remote areas have high migration ties to metro counties, such as areas of Wyoming, Idaho, and North Dakota. These are places that have unique economic conditions that tie them to urban areas. Western North Dakota had a burgeoning energy sector from 2012 to 2016 (when these migration flows were measured), and there are established amenity destinations in the Colorado Rockies; Sun Valley, Idaho; Jackson, Wyoming; and along the Washington and Oregon coasts. Nonmetro counties with higher migration connectivity to metro areas were more likely to experience outbreaks of COVID-19 during the first few weeks and months of the pandemic compared with less-connected nonmetro counties. This chart appears in the USDA, Economic Research Service report COVID-19 Working Paper: Migration, Local Mobility, and the Spread of COVID-19 in Rural America, published in November 2022.
Thursday, December 15, 2022
In the early weeks of the Coronavirus (COVID-19) pandemic, when local and State authorities were issuing stay-at-home orders, employees in farming-dependent counties maintained a relatively high level of onsite work and commuting. Researchers at USDA, Economic Research Service (ERS) and Middlebury College divided all rural (nonmetro) counties into four equal groups based on how much work-related local travel was reduced. The four groups were: greatest reduction, second-greatest, second-least, and least reduction. Those in the “least reduction” group had mobility levels similar to pre-pandemic levels. In mid-April 2020, 7 weeks after the virus first arrived in a rural county and a month after stay-at-home orders were issued, there were three times as many farming-dependent counties in the “least reduction” group as in the “greatest reduction” group. Counties dependent on government and recreation jobs showed the greatest mobility reductions during the early months of the pandemic. These differences in mobility reduction help explain differences in the initial spread of COVID-19 within counties. By the third week of April 2020, “least reduction” counties were experiencing infection rates nearly double those in counties with greater reductions in work-related mobility. This chart appears in the ERS report Migration, Local Mobility, and the Spread of COVID-19 in Rural America, published in November 2022.
Friday, November 25, 2022
According to U.S. Census Bureau estimates for 2015-19, there were 469 nonmetropolitan (nonmetro) counties with a poverty rate of 20 percent or more, which USDA, Economic Research Service (ERS) designates as high poverty. The high poverty classification in more than half of the counties (236) is characterized by a concentration of poverty within racial and ethnic minority groups, including Black or African American (153 counties), Hispanic (49 counties) and American Indian and Alaska Natives (34 counties). Many of the American Indian and Alaska Native high poverty counties are areas of historic tribal presence or were designated as reservation settlements in the 19th century. The average poverty rate for those 34 counties is 31.5 percent for the total population and 40.5 percent for the American Indian and Alaska Native population alone, a level considered to be extreme poverty. The average poverty rates for the other racial-ethnic high poverty county types are below 30 percent for the total population and below 40 percent for the Black or African American and Hispanic population groups. This chart uses information from the ERS Atlas of Rural and Small-Town America to update information on the Rural Poverty and Well-being topic page and the Amber Waves feature Anatomy of Nonmetro High-Poverty Areas: Common in Plight, Distinctive in Nature, published in February 2004.
Wednesday, November 16, 2022
In nonmetro areas from 2010 to 2020, the working-age population (ages 18 to 64) declined by 4.9 percent, and the population under age 18 declined by 5.7 percent. At the same time, the population of those 65 years and older grew by 22 percent. In metro areas, the working-age population increased by 6 percent during the 2010s; however, this growth was overshadowed by the 37 percent growth in the 65 and older population. Nationwide, the overall U.S. population has aged as the baby boomer generation entered their 60s and 70s. Nonmetro areas, in addition to having an aging population, also face population decline. Between 2010 and 2020, U.S. Census data show the population in nonmetro counties declined by 0.6 percent, the first decade of overall nonmetro population decline in U.S. census history. Nonmetro population subsequently increased in the first year and a half of the Coronavirus (COVID-19) pandemic from 2020 to 2021 which saw people move out of metro areas into rural places. However, population gains due to COVID-19 were not enough to offset a decade-long slide in the share of the population that is of working-age nor to reduce the share of the rural population that was 65 or older during this period. Overall, population decline and an increase in average age in rural areas will affect the makeup and availability of the rural labor force. This chart appears in the USDA, Economic Research Service report Rural America at a Glance: 2022 edition, published on November 15, 2022.
Monday, November 15, 2021
During the decade from 2010-20, 24 States lost population in nonmetropolitan, or rural areas, according to the 2020 U.S. census. Sixteen of those States lost population overall or showed slow population growth (less than 5 percent) during the period. Data from the 2020 census show the U.S. population grew 7.4 percent from 2010 to 2020, slower than the 9.7 percent growth in the previous decade. West Virginia, Mississippi, and Illinois lost population in the most recent decade, with the population declining the most in West Virginia at 3.2 percent. West Virginia also was the only State to lose population in metropolitan areas as well as in nonmetro areas. The highest-population growing State from 2010 to 2020 was Utah at 18.4 percent, and Idaho, Texas, North Dakota, and Nevada also showed population growth of 15 percent or more. This map uses data from the USDA, Economic Research Service’s State Fact Sheets data product, updated in November 2021.
Monday, August 23, 2021
Across all races and ethnicities, U.S. poverty rates in 2019 were higher at 15.4 percent in nonmetro (rural) areas than in metro (urban) areas at 11.9 percent. Rural Black or African American residents had the highest incidence of poverty in 2019 at 30.7 percent, compared with 20.4 percent for that demographic group in urban areas. Rural American Indians or Alaska Natives had the second highest rate at 29.6 percent, compared with 19.4 percent in urban areas. The poverty rate for White residents was about half the rate for either Blacks or American Indians at 13.3 percent in rural areas and 9.7 percent in urban settings. Rural Hispanic residents of any race had the third highest poverty rate at 21.7 percent, compared with 16.9 percent in urban areas. Non-Hispanic White residents had the lowest poverty rates in both rural (12.7 percent) and urban (8.2 percent) areas in 2019. This chart appears in the Economic Research Service topic page for Rural Poverty & Well-Being, updated June 2021.
Wednesday, August 11, 2021
A recent USDA, Economic Research Service study of U.S. poverty identified 310 counties—10 percent of all counties—with high and persistent levels of poverty in 2019. High and persistent poverty counties had poverty rates of 20 percent or more in 1980, 1990, 2000, and on average for 2007-2011 and 2015-2019. Of those 310 counties, 86 percent, or 267 counties, were rural (nonmetro). These rural counties were concentrated in historically poor areas of the Mississippi Delta, Appalachia, the Black Belt, and the southern border regions, as well as on Federal Indian reservations. More than 5 million rural residents, or about 12 percent of the U.S. rural population, lived in counties that had high and persistent poverty rates in 2019. Of those, 1.5 million individuals had incomes below the Federal poverty threshold, accounting for 20 percent of the total rural poor population. Rural residents who identify as Black or African American and American Indian or Alaska Native were particularly vulnerable. Nearly half the rural poor within these groups lived in high and persistent poverty counties in 2019. By comparison, 20 percent of rural poor Hispanics and 12 percent of rural non-Hispanic Whites lived in those counties. This chart appears in the August 2021 Amber Waves finding, Rural Poverty Has Distinct Regional and Racial Patterns.
Friday, May 28, 2021
Early during the Coronavirus (COVID-19) pandemic, U.S. employment fell at rates not seen since the Great Depression, with the greatest declines occurring in metro areas. Before the pandemic, employment growth in metro areas had averaged 1.4 percent per year for the 12 months prior to March 2020, more than twice the rate in nonmetro areas (0.6 percent per year). After March 2020, the situation reversed. In April 2020, metro employment was 15.0 percent below 12 months earlier, while nonmetro employment was 12.2 percent lower. Employment has since largely recovered in both metro and nonmetro areas but remained lower in February 2021 than levels 12 months earlier. The extent to which employment was still depressed in February 2021 is greater in metro areas: Metro employment was 5.7 percent lower in February 2021 than in February 2020, while nonmetro employment was 3.4 percent lower. This chart appears in the Economic Research Service topic page, The COVID-19 Pandemic and Rural America, updated May 2021.
Friday, April 2, 2021
Since the late 1990s, an opioid epidemic has afflicted the U.S. population, particularly those in the prime working ages of 25-54. As a result, the National age-adjusted mortality rate from drug overdoses rose from 6.1 per 100,000 people in 1999 to 21.7 per 100,000 in 2017, then dipped to 20.7 per 100,000 in 2018 and rose back to 21.6 in 2019. Among the prime working age population, the drug overdose mortality rate was 37.8 deaths per 100,000 people in 2019. This rate was exceeded only by cancer (39.2 deaths per 100,000) in 2019 as a major cause of death in this population. ERS researchers, examining the opioid epidemic from 1999 to 2018, observed two distinct phases: a “prescription opioid phase” (1999-2011) and a succeeding “illicit opioid phase” (2011-2018), marked especially by the spread of fentanyl and its analogs. Updated data show the second phase has extended into 2019. Mortality data indicate that in the prescription opioid phase, drug overdose deaths were most prevalent in areas with high rates of physical disability, such as central Appalachia. Rural residents, middle-age men and women in their 40s and early 50s were most affected, as were Whites and American Indian/Alaskan Natives. Opioid prescriptions ceased driving the epidemic in 2011 as increased regulation and greater awareness of prescription addiction problems took hold. The illicit opioid phase that followed involved primarily heroin and synthetic opioids, such as fentanyl. Fentanyl and its analogs are often used to spike other addictive drugs, including prescription opioids, creating powerful combinations that make existing drug addictions more lethal. During the study period, this second phase was concentrated in the northeastern United States, particularly in areas of employment loss. This phase most often involved urban young adult males, ages 25 to 39. All the racial/ethnic groups studied—Hispanics, Blacks, American Indian/Alaskan Natives, and Whites—were affected. This chart updates data found in the Economic Research Service report The Opioid Epidemic: A Geography in Two Phases, released April 2021.
Friday, March 19, 2021
During the initial COVID-19 surge between March and June 2020, large urban areas had the highest weekly death rates from the virus in the United States. Those numbers declined as medical professionals learned more about the virus, how to treat it, and how to prevent its spread. As the virus spread from major urban areas to rural areas, the second COVID-19 surge, from July to August 2020, brought more deaths to rural areas. The peak in deaths associated with this surge was smaller because testing was more widespread, the infected population was younger and less vulnerable, and treatments were more effective. However, in early September 2020, COVID-19 death rates in rural areas surpassed those in urban areas. This trend continued into a third, still ongoing, surge that spiked in rural areas during the holiday season and again shortly thereafter. Rural areas have shown higher death rates per 100,000 adults since September in part because they had higher rates of new infections than urban areas, but that is not the whole story. Rural COVID-19 deaths per 100 new infections 2 weeks prior (to account for the lag between infection and death) were 2.2 in the first 3 weeks of February—35 percent higher than the corresponding urban mortality rate of 1.6 deaths per 100 new infections 2 weeks earlier. The rural population appears to be more vulnerable to serious infection because of the older age of its population, higher rates of underlying medical conditions, lack of health insurance, and greater distance to an intensive care hospital. As of early February, death rates have started decreasing, possibly because of more widespread vaccinations among the most vulnerable populations. This chart updates data found in the February 2021 Amber Waves data feature, “Rural Residents Appear to be More Vulnerable to Serious Infection or Death from COVID-19.”