Rural and urban poverty in the U.S. often have a very different character, with different causes, correlates and solutions. To craft effective anti-poverty policies, decision makers need a sound understanding of the ruralness or urbanness of specific places. Government agencies and researchers have created a number of different classification schemes for urban and rural areas which then drive the application of policy. How do these classification schemes impact local populations and their access to government programs and services?
With support from the West Coast Poverty Center, researchers Rachel Garshick Kleit, Man Wang, Jane Cover and Christopher Fowler compared several widely used classification schemes and analyzed the varying magnitudes of poverty they reveal in Washington, Oregon, and California. This Dialogue report describes their findings, beginning with an overview of the geography of poverty and a summary of the four common urban/rural classification schemes and continuing with an analysis of how these classification discrepancies influence our understanding of urban and rural poverty and subsequent policy decisions.
The researchers investigated four different classification schemes, including the widely used federal Office of Management and Budget’s (OMB) Metro/Non-metro scheme, as well as three other schemes developed by the Census Bureau and independent researchers. The team found that total rural/urban population size and the rural and urban population composition vary in the three west coast states, according to the classification definition used. The poverty rate across west coast urban places also varies. While the OMB’s metropolitan and non-metropolitan scheme is a convenient short-hand, U.S. metropolitan areas contain diverse mixes of rural and urban places that belie that dichotomy. Such confusion can also contribute to the mistargeting of resources meant to reduce poverty and associated social problems.
Policymakers commented that broader definitions of what is considered urban/suburban/rural have been changing especially quickly, leading to difficulties in measuring these populations. Immigration to the west coast has been a key factor, as people migrating from Mexico and Central America move to locations all along the urban-rural spectrum. Definitions based on county data (which may overlook sub-county differences) are misleading, one policymaker noted, and the resulting disparity in dollars coming into the west translates into health disparities. In future research, practitioners were eager to see more specific examples that exemplified the problems of using the common classification schemes, and what those decisions mean in terms of dollars.
The full DIALOGUE report includes more information about the way the clusters were defined, more detailed findings, and a summary of the discussion with the practitioners and policymakers. Download the full report here.
DIALOGUES INTERVIEW with Rachel Kleit on Spatial Variations in West Coast Poverty
Census 2000 Urban and Rural Classification
OMB Metropolitan and Non-metropolitan Definitions
Rural Urban Density Code Developed by Andrew Isserman
Isserman, A. (2005). In the national interest: defining rural and urban correctly in research and public policy. International Regional Science Review, 28(4): 465-499.
A metro area is not uniform in geography; rather, it includes counties that vary in their urban and rural character. Among the 65 metro counties in California, Oregon, and Washington, the RUDC classifies 12 counties (18%) as urban, and 12% as mixed urban, leaving over two-thirds (44 counties) fall under the RUDC’s mixed rural classification. While OMB’s non-metro county category is fairly consistent with RUDC’s rural definition with about 99% of non-metro counties classified as either rural or mixed rural, the classification of many metro areas as having a more rural character pinpoints an issue – the diversity of metro areas – that has not drawn enough attention from researchers and policy makers.
Depending on the classification scheme, the rate of poverty in an urban place varies. According to Census definitions, urban places have higher rates of poverty but also higher median incomes and more college graduates than do rural places. Yet, Census urban places have a similar poverty rate as metro places do (about 13.5%), and non-metro poverty rates are generally higher than metro rates (around 14.7%). Furthermore, poverty rates are similar across Census urban, OMB metro, and RUDC urban categorizations and also consistently higher than those of non-metro or rural counties. Yet, when we disaggregate the poverty rates for the three RUCC metro categories, a different picture emerges. While the poverty rate for RUCC large metro counties (12.9%) is similar to that of Census urban, OMB metro, and RUDC urban counties, RUCC medium metro and small metro counties have much higher poverty rates-- so high that they are more similar to OMB non-metro/non-core and RUDC rural places. RUCC medium metro counties have the highest poverty rates of all categories (15.2%). Differences in poverty among these disaggregated categorizes of metro areas indicate that poverty rates vary greatly depending upon the actual metropolitan geography. Crucial differences also emerge in the comparison of the mixed categories from RUDC with their OMB and RUCC counterparts. RUDC mixed urban counties have the lowest poverty rate of all categories (10.6%), much lower than that for RUDC urban, OMB metro and RUCC metro areas. Other indicators of socioeconomic status demonstrate patterns similar to those for the poverty level, except that RUDC mixed-rural places have higher rates of EITC receipt (17.6%) and more food stamps per person (on par with those for RUCC medium metro counties), than either RUDC rural, mixed-urban or urban places. Furthermore, while there are 3.2 million people in RUDC Urban counties, there are an additional 2 million poor people living in mixed-rural counties.
Notes on Graph:
1. Metro includes all RUDC urban, mixed urban, mixed rural and rural counties. Since there is only one metro rural county in the Western States, results for that county are not shown on the chart.
2. The following measures are derived from the 2000 Census Summary File 3: poverty rate (%100 FPL), number of people who are below federal poverty level (Poor Population), poverty by race, median household income (Median HH Inc), unemployment rate (% unemployed), and education.
3. % EITC is the percentage of people who received Earned Income Tax Credit returns in 2000 based on IRS data. Food stamp percentage is in 2000, based on data from Census Consolidated Federal Funds. % Uninsured is the percentage of population who do not have health insurance in 2000, and is from Census Small Area Health Insurance Estimates (SAIHE). “All” is for total population and “<18” is for people who are age18 or younger.
Metro places that have a more rural character (metro mixed rural) appear to be somewhat worse off than metro places with an urban character. For counties that are classified as metropolitan by the OMB but mixed-rural in the RUDC system, the poverty rate is higher than the overall metro rate (14.8% vs. 13.5%) and more comparable to non-metro places. Metro mixed rural counties also have the highest percentage of people who are not covered by health insurance, as well as higher unemployment levels than urban, rural, or mixed-urban counties in metropolitan areas. People in these counties are also more likely to receive the Earned Income Tax Credit. Metro mixed-urban places, in contrast, have lower poverty rates than the metro average (10.7% vs. 13.5%), while metro urban counties have a rate that is on-par with the overall metropolitan category (13.2). Over 1.8 million poor people – more than a third of the poor in metropolitan areas – live in these metro mixed rural places, making poverty in such areas an important focus for policy.
With the long run decentralization of population and jobs in the U.S., suburbs have grown rapidly in some places, opening up new housing and employment opportunities. These fast-growing suburban counties are different from the traditional suburbs in that residents living in these places are more racially and economically diverse (Berube and Frey, 2002). They are “neither urban nor suburban both in terms of form and character” (Langh, Blakley, and Gough, 2005, p. 381). Among the 50 largest fast growing suburban counties across the U.S., 14 of them are in Washington, Oregon, and California (Langh, etc, 2005). A map of the location of fast growing suburban counties in relation to inconsistently classified counties shows overlap between the two, with seven metro mixed rural counties and five metro mixed urban counties identified as fast growing suburbs. Living in the suburbs does not guarantee access to social services and employment opportunities for low income populations. As we have seen, while metro mixed rural counties have the highest rates of poverty, unemployment, and the uninsured, metro mixed urban counties are better off across every indicator.