ERS Charts of Note
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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, 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.
Thursday, November 15, 2018
Compared to traditional medical delivery systems, telehealth—health services or activities conducted through the internet—allows people to more actively participate in their health care. It also facilitates timely and convenient monitoring of ongoing conditions. To better understand the factors affecting telehealth use, ERS researchers examined rural residents’ participation in three telehealth activities: online health research, online health maintenance (such as contacting providers, maintaining records, and paying bills), and online health monitoring (the transmission of data gathered by remote medical devices to medical personnel). The ERS analysis looked at a number of socioeconomic factors—including family income, educational attainment, age, and employment type and status—that may affect a person’s choice to engage in telehealth activities. Findings show that participation rates for telehealth activities in 2015 increased with the level of educational attainment. For example, rural residents with college degrees were over 5 times more likely to conduct online health research than residents without a high school diploma, and more than 10 times as likely to engage in the other telehealth activities. This chart appears in the November 2018 ERS report, Rural Individuals’ Telehealth Practices: An Overview.
Wednesday, July 25, 2018
Veterans constitute a rapidly aging and increasingly diverse group disproportionally living in rural America. Nearly 18 percent of veterans lived in rural (nonmetro) counties in 2015, compared to 15 percent of the U.S. adult civilian population. Veterans were also overrepresented in some rural counties: about 10 percent of all rural civilian adults were veterans, but in some rural counties, that share reached as high as 25 percent. The U.S. counties with the highest shares of veterans tended to have significant concentrations of elder veterans (65 years or older), relative to the Nation as a whole. About 24 percent of all U.S. counties—often completely rural counties not adjacent to metro areas—had concentrations of elder veterans. By comparison, 28 percent of all U.S. counties—predominantly large urban counties (not shown)—contained concentrations of working-age veterans (18 to 65 years old). Areas with concentrations of both groups were mostly in rural counties adjacent to metro areas (19 percent). Many of these counties contained or were near military installations, reserve bases, or training areas. This chart appears in the September 2017 Amber Waves data feature, “Veterans Are Positioned To Contribute Economically to Rural Communities.”
Tuesday, May 29, 2018
On May 29, 2018, the Chart of Note article “Rural economies depend on different industries” was reposted to correct the industry classification of a few counties and, in the legend, show the number of rural counties only, instead of all counties.
Rural counties depend on different industries to support their economies. Counties’ employment levels are more sensitive to economic trends that strongly affect their leading industries. For example, trends in agricultural prices have a disproportionate effect on farming-dependent counties, which accounted for nearly 20 percent of all rural counties and 6 percent of the rural population in 2017. Likewise, the boom in U.S. oil and natural gas production that peaked in 2012 increased employment in many mining-dependent rural counties. Meanwhile, the decline in manufacturing employment has particularly affected manufacturing-dependent counties, which accounted for about 18 percent of rural counties and 22 percent of the rural population in 2017. This chart is based on the ERS data product for County Typology Codes, updated May 2017.
Tuesday, February 13, 2018
Nearly 19 million veterans lived in the United States in 2015. Almost 18 percent of them lived in rural (nonmetro) counties, compared to 15 percent of the U.S. adult civilian population. About 45 percent of rural veterans were working age (18 to 64 years old); the rest were elder veterans (65 years or older). Overall, about 21 percent of elder rural veterans reported currently working (full- or part-time) or having last worked (if retired or unemployed) in the agriculture industry. By comparison, less than 3 percent of working-age veterans reported the same. Instead, working-age veterans relied more on the manufacturing industry for employment. About 19 percent of working age veterans reported currently working or having last worked in manufacturing, compared to 7 percent of elder veterans. Both working age and elder veterans relied about equally for employment in some industries—including education and health, wholesale and retail trade, and construction. This chart appears in the September 2017 Amber Waves data feature, "Veterans Are Positioned To Contribute Economically to Rural Communities."
Thursday, September 28, 2017
Veterans tend to have higher earnings compared to nonveterans. In 2015, rural veterans who were full-time wage and salary workers had median earnings of about $50,000. That’s $11,000 more than the median earnings of their nonveteran counterparts. Earnings for veterans and nonveterans varied by industry, however. For example, compared to nonveterans, the median earnings for veterans was $29,000 higher in financial services, $20,000 higher in education and health, and $11,500 higher in transportation and utilities. Differences in median earnings by industry between veterans and nonveterans generally track closely with educational attainment. However, in 2015, even in industries where fewer veteran than nonveteran earners had a college degree, the median income for veterans was near or greater than that of nonveterans. This may be explained by a variety of factors, including differences in demographic composition and job skills. For example, veterans tend to be older and are predominantly male, and thus on average more likely to have higher earnings than the general population. This chart appears in the September 2017 Amber Waves data feature, "Veterans Are Positioned To Contribute Economically to Rural Communities."
Monday, September 19, 2016
Between 2010 and 2015, the population of rural and small-town America declined by 0.3 percent, according to Census population estimates. This loss of 137,000 people was a relatively small change that masked larger racial-ethnic trends. The non-Hispanic White population declined by 738,000 in rural (nonmetro) counties, while all other racial-ethnic groups increased by 601,000. The rural Hispanic population alone grew by 376,000 (10 percent) during this time period. The increasing Hispanic population helped nearly 10 percent of rural counties (188 counties) in Texas, New Mexico, and 32 other states maintain population growth, continuing a 30-year trend. Immigration and domestic migration drove this trend early on as Hispanic workers filled jobs in textiles, food processing, and other agricultural-related industries. Today, immigration has slowed and most of the growth in the rural Hispanic population comes from natural increase (more births than deaths). The resulting change in the composition of Hispanic families may lead to new community needs for housing, schools, and family services. Find county-level maps and data on the U.S. Hispanic population in ERS’s Atlas of Rural and Small-Town America.
Tuesday, June 7, 2016
Racial and ethnic minorities made up 21 percent of rural residents in 2014. Hispanics (who may be of any race) and Asians are the fastest growing minority groups in the United States as a whole and in rural areas. Over 2010-14, the rural Hispanic population increased 9.2 percent, and their share of the total rural population rose from 7.5 to 8.2 percent. Asians and Pacific Islanders represent a small share of the rural population—about 1 percent—but their population grew by 18 percent between 2010 and 2014, while rural Native American and Black populations grew at more modest rates. This is in contrast to the rural non-Hispanic White population, which declined by 1.7 percent between 2010 and 2014. Overall rural population loss (which was -0.2 percent for the period) would have been much higher if not for the growth in the rural racial and ethnic minority groups. Rural minorities tend to be younger on average and have larger families than non-Hispanic Whites, and this, along with net migration, is reflected in the varying growth rates. This chart updates one found in the ERS publication, An Illustrated Guide to Research Findings from USDA's Economic Research Service.
Thursday, March 3, 2016
The proportion of adults lacking a high school diploma or equivalent declined in rural America (defined here as nonmetro counties), from 32 percent in 1990 to 15 percent in 2014. The proportion of rural adults with college degrees also increased from 12 to 19 percent during that time. Despite these overall gains, educational attainment varies widely across rural areas. ERS’s latest county typology classifies low-education counties as those where at least one of every five working-age adults (age 25-64) has not completed high school. In an average of data over 2008-12, ERS identified 467 low-education counties in the United States, 367 of which were rural. Eight out of 10 of all low-education counties are located in the South. Three-fourths of rural low-education counties also qualified as low-employment in the latest ERS county typology. Over 40 percent of rural low-education counties were both low-employment and persistently poor, reflecting the difficulty that adults without high school diplomas have in finding and retaining jobs that pay enough to place them above the poverty line. This map is part of the ERS data product on County Typology Codes, released December 2015.
Tuesday, August 4, 2015
The number of rural (nonmetropolitan) counties that lost population in 2010-14 reached a historic high of 1,310. The recent economic recession, increased global competition, and technological changes led to widespread job losses in rural manufacturing. Population loss occurred throughout the eastern United States, especially in manufacturing-dependent regions such as along the North Carolina-Virginia border and southern Ohio. Population growth did occur in 666 nonmetro counties. Large sections of the northern Great Plains started to gain population after decades of persistent decline, due largely to the inmigration of workers capitalizing on the shale oil and gas production boom. Nonmetro counties in southeastern New Mexico and parts of eastern Texas also gained population from energy-related job growth. This chart appears in the August 2015 Amber Waves finding, “Population Loss in Nonmetro Counties Continues.”
Monday, June 29, 2015
During 2010-14, the number of nonmetro counties that lost population reached a historic high of 1,310. County population loss stems from two possible sources: more people leaving a county than moving into it (net outmigration) and/or more people dying than are being born (natural decrease). Historically, the vast majority of counties that lost population still continued to experience natural increase, just not enough to offset losses from net outmigration (this scenario describes less than half of the 2010-14 population loss counties). The number of nonmetro counties with population loss from both net out-migration and natural decrease grew from 387 before the recession (2003-07) to 622 during 2010-14. Clusters of counties experiencing this demographic ‘double-jeopardy’ have expanded, especially in Alabama, southern Appalachia, along the Virginia-North Carolina border, and in New England. The rising number of double-jeopardy counties signals new challenges in maintaining future population growth and sustained economic development. This map is based on information found in the Population & Migration topic page, updated June 2015.
Thursday, May 14, 2015
Small population size and geographic remoteness provide benefits for residents and visitors alike, but those same characteristics often create economic and social challenges. Job creation, population retention, and provision of goods/services (such as groceries, health care, clothing, household appliances, and other consumer items) require increased efforts in very rural, remote communities. The newly updated ERS Frontier and Remote area (FAR) codes identify remote areas of the United States using travel times to nearby cities. Results for level one FAR codes (which include ZIP code areas with majority of their population living 60 minutes or more from urban areas of 50,000 or more people) show that 12.2 million Americans reside more than a one-hour drive from any city of 50,000 or more people. They constitute just 3.9 percent of the U.S. population living in territory covering 52 percent of U.S. land area. Wyoming has the highest share of its population living in FAR level one ZIP code areas (57 percent), followed by Montana, North Dakota, South Dakota, and Alaska. This map, along with the full detail of FAR codes levels 1-4 may be found in the ERS data product, Frontier and Remote Area Codes, updated April 2015.
Wednesday, February 25, 2015
The estimated 42 million African Americans living in the United States in 2013 made up close to 13 percent of the population. During a post-recession population slowdown in the United States, African Americans have continued to experience relatively high rates of population growth, the result of higher fertility rates and a younger average population. Population estimates from the U.S. Census Bureau show gains among African Americans in all urban/rural county types except for the most sparsely-settled and remote areas (nonadjacent rural) during 2010-13. For the total population, suburbanization trends in the U.S. slowed markedly with the onset of the housing crisis and recession. Suburban fringe counties (metro outlying) now show slower rates of growth than the central cities of metro areas, although the African American population growth rate has not yet experienced this historic shift. Similarly, the African American population continues to show gains in those nonmetro counties most likely to be suburbanizing (nonmetro adjacent) at a time when those counties show overall population declines. This chart expands on one found in Shifting Geography of Population Change, a chapter in the ERS website topic page on Rural Population and Migration.
Wednesday, May 14, 2014
Population change is varied across rural and small-town America. Since 2010, over 1,200 rural (nonmetropolitan) counties have lost population, with declines totaling nearly 400,000 people. At the same time, the population of just over 700 rural counties grew, together adding just over 300,000 residents. New regional patterns of growth and decline emerged in recent years. Areas of population decline appeared for the first time in the eastern United States, including New England, the North Carolina-Virginia border, and southern Ohio. Falling birth rates, an aging rural population, and a declining manufacturing base contributed to population downturns in these regions. In the Mountain West, population growth also slowed considerably, and in some cases turned negative, for the first time in decades, affecting numerous counties in western Colorado and Wyoming, central Oregon, and northern Idaho. In contrast, an energy boom has spurred population growth in sections of the northern Great Plains that had previously experienced long-term population declines. This map is found in the ERS topic page on Rural Population and Migration, updated April 2014.
Wednesday, October 23, 2013
Metropolitan (metro) counties have fared better than both micropolitan and noncore counties (shown in the map) following the 2007-09 recession. ERS researchers generally define “rural” as micropolitan and noncore counties (together referred to as nonmetropolitan or nonmetro counties), and “urban” as metropolitan or metro counties. During the National economic recovery period between 2010 and 2012, employment increased by 2.5 percent in metro counties, compared with 1.1 percent in micropolitan, and 0.5 percent in noncore counties. Metro counties are densely settled counties with an urban core population of 50,000 or more, and outlying counties tied to the central core by labor force commuting. Micropolitan counties are similar to metro counties, but include an urban core with a population between 10,000 to 49,999, and outlying counties tied to the core by commuting. Noncore areas are the remaining counties that are neither metro nor micropolitan. As of February 2013, the Office of Management and Budget identified 1,167 metro counties, 641 micropolitan counties, and 1,335 noncore counties. This map is found in the ERS topic page on Rural Classifications, updated in May 2013.
Thursday, July 11, 2013
All sectors of the economy were not equally affected by the 2007-09 economic recession and the subsequent recovery. Specialization within local economies has shaped county-to-county differences in recent rural (nonmetro) growth in jobs. Boosted by high farm income and, in some areas, booming gas-extraction activities, farming-dependent counties have seen job growth for the first time in many years, growing during and after the recession. Manufacturing counties, affected by global competition, showed weak job growth in the early 2000s, followed by substantial losses during the recession. Recreation counties, which experienced above-average job growth in 2001-07, lost jobs in 2007-09 as their housing markets collapsed and the recession reduced tourism. Weak postrecession job growth did not bring jobs back to prerecession levels in most nonmetro counties by 2011. County economic types were defined by ERS in 2004 and are scheduled to be updated next year. This chart combines the ERS county typology codes with employment data from U.S. Department of Commerce, Bureau of Economic Analysis.
Friday, June 14, 2013
The Urban Influence (UI) codes classify all U.S. counties, as well as “municipios” in Puerto Rico, by size of metropolitan area, adjacency to a metropolitan or micropolitan area, and size of the largest town. These codes are updated every 10 years after the release of new decennial census data and updated metropolitan and micropolitan areas by the Office of Management and Budget (OMB). The latest UI codes were released in May 2013. Compared with 2003, in 2013 there are an additional 78 metropolitan counties, 114 counties moved from nonmetropolitan to metropolitan, and 36 counties changed from metropolitan to nonmetropolitan for a total of 1,167. The number of nonmetro counties fell from 2,053 to 1,976 between 2003 and 2013. The UI codes enable users to analyze the diversity of rural counties by their size, and access to larger economies that serve as centers of trade, finance, information, and communications. The codes provide a more finely articulated measure of rural and take advantage of OMB’s metropolitan, micropolitan, and noncore classification system. ERS uses the codes extensively in its research on rural labor, poverty, population change, employment, and unemployment. This map is found on the ERS website as part of the Urban Influence Codes data product, updated May 2013.
Wednesday, May 15, 2013
As it has done with every decennial census since 1950, in late February 2013, the Office of Management and Budget announced the latest delineation of metropolitan areas in the United States. ERS uses this delineation as the foundation for its Rural-Urban Continuum Codes and Urban Influence Codes, which further identify each county by size of metro core (for metro counties), or degree of urbanization and proximity to metro areas (for nonmetro counties). Generally, nonmetro counties that grew rapidly over the previous decade are reclassified as metro. In the latest update, 113 nonmetro counties (with just under 5.9 million people) switched to metro status while 36 counties (with just over 1 million people) no longer qualified as metro, resulting in a net nonmetro population "loss" of 4.8 million from reclassification. The 1,976 counties now classified as nonmetro include 15 percent of the U.S. population (46 million people) and 72 percent of the Nation’s land area. This map is found on the ERS topic page, Population & Migration, updated May 2013.
Wednesday, July 11, 2012
Population retention, job creation, and acquisition of goods and services often require increased effort in very rural, remote U.S. communities. ERS has developed a set of frontier and remote (FAR) area codes to aid research and policymaking on such communities. The initial version classifies ZIP code areas and includes four FAR level codes, based on different population and travel-time thresholds. The levels are meant to reflect likely access to various levels of public and private services. Level one-shown on the map-identifies areas lacking easy access to services commonly provided in large urban centers, such as advanced medical procedures, major household appliances, regional airport hubs, or professional sports franchises. Other levels identify increasingly remote areas of the country that may lack easy access to even basic services, such as grocery stores, gas stations, and basic health-care. The map is from the Frontier and Remote Area Codes data product on the ERS website, updated June 1, 2012.