Using the 2003 Urban Influence Codes To Understand Rural America
County-level data analysis adds depth to research on rural America. The size of the largest city or town in a county determines the variety of goods and services available and the adequacy of the labor supply to meet business needs. Proximity to larger economies also has a significant effect on county development, as easy access to larger centers of information, trade, health care, and finance may connect the county to national and international marketplaces. These basic concepts underpin ERS's new 2003 urban influence codes, which were developed to help researchers and policymakers understand geographic differences in economic opportunities at the county level. The importance of city size and adjacency to larger places is reflected in various county-level measures, such as population change, educational attainment, managerial/professional employment, and earnings.
ERS's 2003 urban influence codes divide counties, county equivalents, and independent cities in the United States into 12 groups—2 metropolitan (metro) and 10 nonmetropolitan (nonmetro) (see Behind the Data). Metro counties are either large (those with populations of 1 million or more) or small (those with less than a million residents). Nonmetro counties are first classified as either micropolitan (with an urban core of at least 10,000 residents) or noncore (without an urban core that large). The micropolitan (micro) counties are further classified by adjacency to a large metro area, a small metro area, or no metro area. The noncore counties are further classified by adjacency to metro or micro areas and by whether or not they have a town of at least 2,500 residents. The 2003 urban influence codes are based on the June 2003 Office of Management and Budget (OMB) definitions of metro and nonmetro areas.
|County types||Counties (number)||Share of residents 25+ with at least a bachelor's degree, 2000 (percent)||Share of employed civilians 16+ with managerial or professional jobs, 2000 (percent)||Earnings per job, 2001 (dollars)|
|Adjacent to large metro||92||15.7||26.3||27,200|
|Adjacent to small metro||301||15.6||26.6||26,847|
|Not adjacent to a metro area||282||18.1||28.0||26,403|
|Adjacent to large metro||123||12.5||24.8||23,381|
|Adjacent to small metro with own town||358||12.8||25.3||23,625|
|Adjacent to small metro no town||185||12.2||25.7||21,706|
|Adjacent to micro with own town||201||13.4||25.9||23,251|
|Adjacent to micro no town||198||12.4||27.8||20,431|
|Not adjacent to metro/micro with own town||138||15.7||28.2||24,796|
|Not adjacent to metro/micro no town||174||14.5||29.7||20,622|
|Sources: Education and occupation calculated using data from the 2000 Census of Population; earnings calculated using data from the Bureau of Economic Analysis' Regional Economic Information System.|
Between 1990 and 2000, population grew fastest in large metro counties and in nonmetro counties adjacent to them. Nonmetro counties adjacent to large metro areas grew faster than small metro areas did. This contrasts with population change in the 1980s, when alltypes of nonmetro counties grew more slowly than both large and small metro counties. Much of the growth in adjacent nonmetro counties is due to spillover effects as residents of large metro areas moved to such counties for rural amenities or lower housing costs. Nonmetro micro counties had higher population growth than noncore counties. And, within noncore counties, those with towns grew more than those without towns. Small towns often serve as regional service centers for surrounding counties without such towns.
The highest shares of persons with college degrees are found in large (28 percent) and small (23 percent) metro areas. These areas also have large numbers of professional and managerial jobs (employing about one-third of civilian workers) that generally require a college degree. Micro counties adjacent to large and small metro areas have lower proportions of persons with college degrees (16 percent) than nonadjacent micro counties (18 percent). The college-educated are more likely to find jobs and live in metro areas, partially explaining the lower proportion of college graduates in adjacent micro counties. Nonadjacent micro counties have more college-educated residents because they are often home to small colleges and universities and serve as regional centers of specialized services.
Among noncore counties, those adjacent to metro or micro areas have lower shares of college graduates (12-13 percent) than nonadjacent noncore counties (15-16 percent). Lacking direct competition from larger communities in professional and managerial services, nonadjacent noncore counties have slightly higher shares of residents employed in such jobs (28-30 percent) than adjacent counties (24-25 percent) .
Earnings per job are far higher in metro areas (both large and small) than in any of the nonmetro county groups. Large metro areas averaged $43,102 per job and small metro areas $32,417 per job, compared with $20,431 to $27,200 per job in nonmetro counties. Among micro counties, those adjacent to large metro areas had the highest earnings per job—$27,200. Competition for workers from large metro areas may push employers in adjacent micro counties to offer higher wages. Micro counties adjacent to small metro areas had earnings per job ($26,847) only slightly higher than nonadjacent micro areas ($26,403). Because average earnings in small metro areas are much lower than in large metro areas, small metro areas apparently provide less competitive pressure on wages than large metro areas.
Noncore counties with towns average higher earnings than those without towns. Adjacency to either metro or micro areas does not seem to boost earnings in noncore counties. Just as higher percentages of college graduates and workers in professional and managerial jobs are found in nonadjacent-noncore counties, earnings per job are higher in noncore counties with towns than in adjacent-noncore counties with towns.
Urban Influence Codes, by John Cromartie, USDA, Economic Research Service, October 2019
Rural Classifications, by John Cromartie, USDA, Economic Research Service, November 2022