Rationalizing Rural Area Classifications for the Economic Research Service A Workshop Summary (2016) / Chapter Skim
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Appendix B: Historical Development of ERS Rural-Urban Classification Systems--John Cromartie
Appendix B: Historical Development of ERS Rural-Urban Classification Systems--John Cromartie
Pages 145-164
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From page 145... ...
This paper traces the development of the Rural-Urban Continuum Codes, the Urban Influence Codes, the Rural-Urban Commuting Area Codes, and the Frontier and Remote Area Codes. Similarities and differences in underlying concepts, methodologies, criteria, data, and geographical building blocks are highlighted.
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From page 146... ...
Census Bureau's urban area definitions, especially the 50,000 population threshold as the basic "rural-urban" dividing line.1 All four move beyond the metro-nonmetro dichotomy, using Census urban geography and other criteria to devise multiple levels of rurality below the 50,000 population threshold. Two are county-based classifications that directly maintain the metro-nonmetro distinction among counties but add additional categories using measures of proximity and urban size.
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From page 147... ...
6 nonmetro metro area For nonmetro counties: Total urban population and adjacency to metro areas Urban Influence Counties 12 categories: For metro counties: 1997 Codes (UIC) 2 metro Population of 10 nonmetro metro area For nonmetro counties: Size of largest city, adjacency to metro areas by size of metro area, and micropolitan status Rural-Urban Census tracts; 10 primary Primary codes: 1998 Commuting results used codes: Urban area size; Area (RUCA)
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From page 148... ...
, and • urban clusters with populations ranging from 2,500 to 49,999. In addition to conducting research that uses the basic metro-nonmetro dichotomy, ERS has developed multilevel county classifications to measure rurality in more detail and to assess the economic and social diversity of nonmetro America.
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. The scheme allows researchers to break county data into residential groups for the analysis of trends in nonmetro areas that are related to urban population size and metropolitan accessibility.
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Brown, and John M Zimmer, for their ERS report, Social and Economic Characteristics of the Population in Metro and Nonmetro Counties: 1970.
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They have been updated with each subsequent decennial census, with only two minor changes in criteria since 1970.2 However, socioeconomic conditions and trends today are not as strongly correlated with the RUCC. In part, this is due to the substantial contraction of nonmetro space overall and the increasing urban influence found in the remaining nonmetro counties.
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From page 152... ...
Differences can be seen in an initial, six-level version of the UIC used in the ERS report documenting socioeconomic conditions and trends in the nonmetro population during the 1980s.4 For that analysis, metro areas were divided into two groups and nonmetro counties were divided into four groups (Ghelfi, 1993) : Metro 1.
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From page 153... ...
The RUCC delineated nonmetro catego ries based on the counties' total urban population size, meaning a county with three towns of 7,000 each would be placed in the highest urban category. Also, if a county contained 2,000 people from an urban area of 40,000 located mostly in a neighboring county, that county would nonetheless be classified in the lowest urban size category.
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From page 154... ...
. The UIC and RUCC use nearly identical concepts of urban size and proximity to characterize counties along an urban-rural continuum, thus the UIC map differs from the RUCC map only slightly in its general aspects.5 Sprawling metro regions of 1 million or more people dominate most of the eastern United States, contrasting sharply with the remote and sparsely-settled Heartland.
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Fortunately, easier access to large Census data files and improving computer capabilities, especially the emergence of Geographic Information Systems (GIS) , were making it possible to consider the use of smaller geographic units as building blocks for urban-rural classifications.
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. RUCA Codes closely follow the same concepts and criteria used by OMB, especially in the use of Census urbanized areas and urban clusters as the starting point for constructing metro and micro areas.
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4.0 No additional code 4.1 Secondary flow 30% to 50% to a UA 5 Micropolitan High Commuting: Primary Flow 30% or More to a Large UC 5.0 No additional code 5.1 Secondary flow 30% to 50% to a UA 6 Micropolitan Low Commuting: Primary Flow 10% to 30% to a Large UC 6.0 No additional code 7 Small Town Core: Primary Flow within an Urban Cluster of 2,500 to 9,999 (small UC) 7.0 No additional code 7.1 Secondary flow 30% to 50% to a UA 7.2 Secondary flow 30% to 50% to a large UC 8 Small Town High Commuting: Primary Flow 30% or More to a Small UC 8.0 No additional code 8.1 Secondary flow 30% to 50% to a UA 8.2 Secondary flow 30% to 50% to a large UC 9 Small Town Low Commuting: Primary Flow 10% to 30% to a Small UC 9.0 No additional code 10 Rural Areas: Primary Flow to a Tract Outside a UA or UC 10.0 No additional code 10.1 Secondary flow 30% to 50% to a UA 10.2 Secondary flow 30% to 50% to a large UC 10.3 Secondary flow 30% to 50% to a small UC SOURCE: USDA Economic Research Service.
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From page 158... ...
Thus, the primary RUCA Codes are further subdivided to identify areas where classifications overlap, based on the size and direction of the secondary, or second largest, commuting flow. For example, 1.1 and 2.1 codes identify areas where the primary flow is within or to a metropolitan core, but another 30 percent or more commute to a larger metropolitan core.
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From page 159... ...
RUCA Codes also identify those parts of nearby non metro counties that are highly connected to metro cores. The tract-based delimitation succeeds in identifying more precisely extent of micropolitan influence (shown in light gray)
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From page 160... ...
The term "frontier and remote" is used here to describe territory characterized by some combination of low population size and a high degree of geographic remoteness. As with the RUCA Codes, demand for a geographically detailed delineation of frontier areas came from the Office of Rural Health Policy, to help administer HHS programs with the legislative mandate to improve access to health-care in frontier areas.
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From page 161... ...
Four FAR levels were defined based on urban area size, with the notion that urban areas of different sizes offer different levels of services and different labor market opportunities. For each of 32.4 million grid cells, travel times to nearby UAs were examined and up to four pieces of information retained -- the travel time in minutes to the edge of the nearest UA with a population in the following size ranges: 2,500-10,000, 10,000-24,999, 25,000-49,999, and 50,000 or more.
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From page 162... ...
For ZIP Code areas containing a mix of frontier and nonfrontier populations, classification was based on the status of the majority of the population. The same analysis can be repeated for census tracts, counties, or other geographic units.
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From page 163... ...
For instance, the FAR classification measures urban access and remoteness using ½ kilometer grid cells, improving geographical accuracy for many applications. At the same time, county-level classifications will continue to be needed given data requirements.
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From page 164... ...
164 RATIONALIZING RURAL AREA CLASSIFICATIONS FOR THE ERS • useful in identifying socioeconomic variation as it is affected by size of place and urban proximity; • useful to policy makers in evaluating programs and delineating eligibility; • useful to a broad range of stakeholders by being relatively easy to use, containing a reasonably small number of categories with discernable criteria; • based on conceptually sound methodology, including justifiable breakpoints; and • consistent with OMB and Census Bureau definitions. It will not be possible to satisfy all these needs perfectly, so tradeoffs need to be considered.
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