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Poverty and Rural Income

Data about income illustrate the extent and prevalence of economic wellbeing experienced by individuals in a community. Poverty, a related measure, illustrates the converse - the extent of economic ill experienced by individuals and families in a community.

What Is Poverty?

The US Census Bureau defines poor families as those whose income fails to meet a minimum threshold, adjusted yearly for inflation, for their family size and type. As an example, the 2007 poverty threshold for a family of four containing two adults and two children is $21,027, and for a family of three with one adult and two children the threshold is $16,705 in annual pre-tax money income (including earnings, unemployment and workers' comp, social and supplemental income, public assistance, pensions, interest and dividends, rent, royalties, income from estates and trusts, and alimony and child support; non-cash benfits such as food stamps do not count).

Money, Microsoft Office Clip Art

Money from Microsoft Office Clip Art

It has been observed that across the United States, nonmetropolitan counties have lower wages, lower median incomes, and higher poverty rates than metropolitan counties. There are many reasons why this might be. There is much debate about the role that differences in cost of living may play. If the cost of living is significantly lower in rural areas, the wages just reflect that reality, a family's purchasing power may be nearly the same, and the higher poverty rate may in fact be an overstatement. How true is that perception? A paper in 2000 estimated that the cost of living in nonmetro counties across the country was about 16% less than in metro ones - although in the west, the nonmetro advantage was only 9% (Nord, 2000). A more recent paper used a detailed analysis of many cost factors associated with residence in different counties in Kentucky - including housing cost, driving costs and food costs - found life in rural areas did not cost less than in urban ones, and that the costs were highly variable by type of nonmetro county (Zimmerman, 2008).

Another factor that can play into the lower wages seen in rural areas is the lower education levels in rural areas. We know, and expect, that higher educational attainment by adults is correlated with higher incomes; since rural areas tend to have lower levels of educational attainment, we would expect to see on average lower incomes. Also, the traditional concentration of rural jobs in lower-paying blue-collar industries means that average wages will appear lower than in areas with a more diverse mix of jobs.

For years researchers have attempted to parse out what portions of lower incomes and higher poverty rates of rural or nonmetro counties is due to the characteristics of the people, the local opportunity structures, lower cost of living, and/or social factors (see Weber et al. 2005 for a review). More recently, studies have turned a more critical eye on the very relationship between rural residence and higher poverty rates by incorporating the role of migration. One paper looked at the migration destinations of the poor and the non-poor and found that the movement of poor people into counties with lower-skilled job opportunities and lower housing costs (and higher poverty) increased the poverty rate in those counties. He concluded that "the cause of high poverty in the persistent-poverty counties may be as much the lack of entry-level jobs and low-cost housing in low-poverty counties as it is the lack of good jobs in the high-poverty counties" (Nord, 1998). Most recently, work by Fisher has used household-data in an attempt to ascertain to what extent the migration decisions made by households influences the resulting higher risk of poverty in nonmetro areas.

A New Look at the Role 'Rurality' Plays in Poverty

Excerpted from: Fisher, Monica. 2007. Why is U.S. Poverty Higher in Nonmetropolitan than in Metropolitan Areas? Growth and Change 38 (1): 56-76.

"Why is poverty higher in nonmetro than in metro areas? One view, the 'structural condition hypothesis,' ascribes a causal role to place of residence. From this perspective, otherwise identical individuals will have lower economic well-being in nonmetro compared with metro settings because of the spatial distribution of economic and social opportunities (Tickamyer and Duncan 1990; Tomaskovic-Devey 1987). The 'residential sorting hypothesis,' by contrast, posits that, holding constant human capital attainment, individuals' prospects for economic prosperity are independent of where they live.

"The rural poverty literature has emphasized the structural condition hypothesis. Data indeed confirm that local nonmetro labor markets generally offer fewer job options, and work tends to be concentrated in minimum wage and part-time jobs offering limited security and little room for advancement (Gibbs 2001; McKernan et al. 2001). Moreover, work supports such as job training programs, formal group child care, and public transportation tend to be limited or completely absent in nonmetro communities (Colker and Dewees 2000; Fletcher et al. 2002).

"Social-context variables such as community capacity, local social norms and networks, and the power and motivations of local government also influence the geographic distribution of poverty (Blank 2005; Weber et al. 2005). Duncan's (1999) fieldwork in rural communities of Appalachia and the Mississippi Delta, for example, reveals a rigid two-class system in which the relatively well-off have taken advantage of the local social structure to maintain their privileged position and keep the poor marginalized. Rupasingha and Goetz (2003) use principal components analysis to develop a county-based social capital index, combining measures of associational density, political involvement, and response rate to the decennial census. They find that nonmetro counties with high social capital have lower family poverty rates, all else being equal. In sum, a key explanation for enduring nonmetro poverty is that the local context of many nonmetro areas makes it hard for people to succeed economically.

"This article explores the residential sorting hypothesis of metro-nonmetro differences in economic well-being, asking whether the disproportionate poverty observed in nonmetro communities partly reflects the attitudes of people with personal characteristics related to human impoverishment: they may be attracted to nonmetro places or otherwise reluctant (or unable) to leave them...

"Why would people with low-income capacity 'choose' to live in or be reluctant to leave nonmetro communities? It is conceivable, as argued by Nord (1998), that individuals with low education and limited work experience are drawn to places that offer opportunities matching their skills and needs, for example communities with a high share of entry-level positions and where living costs are low. Low-skill occupations continue to make up a higher percentage of total jobs in nonmetro areas (42 percent) than in the nation as a whole (35.5 percent) (Gibbs, Kusmin, and Cromartie 2004); perhaps a lack of agglomeration in nonmetro areas attracts such an occupational structure.

"The study's first hypothesis is that householders with low educational attainment tend to sort themselves into nonmetro areas...results...suggest that one reason economic well-being is lower in nonmetro than in metro areas is that there is a relative concentration of people with low educational attainment in nonmetro places.

"The second study hypothesis is that people with unobserved attributes related to having low income tend to sort themselves into nonmetro localities...This finding, rather than lending support to the residential sorting hypothesis, provides indirect evidence in favor of the structural condition hypothesis"”that otherwise identical individuals will have lower economic well-being in nonmetro compared with metro settings because of the spatial distribution of economic opportunities. Another plausible interpretation is that equally able workers earn lower wages in rural than in urban areas because of a lack of agglomeration economies in rural places.

"Taken together, study findings suggest enduring nonmetro poverty is explained both by a sorting of low human capital individuals into nonmetro areas and by reduced economic opportunities in nonmetro compared to metro places. This conclusion, however, must be qualified given that the empirical approach of this study is very indirect."

Explore on Your Own!

What rural areas in Oregon are characterized by higher poverty and lower wages? Are there areas that don't follow this pattern? Why might certain areas be different?

Launch the Oregon Communities Reporter Tool

Poverty and Income-Related Terms

Using the Oregon Communities Reporter and the Advanced Mapping Tool, you can explore these issues and data across the state among the following variables:

  • Median Household Income: The household incomeat which 50% of households in the population earn less and 50% earn more.
    Source: US Census Bureau

  • Poverty Rate: The percentage of individuals whose family income falls below the poverty threshold for their family size.
    Formula: ([# of individuals below poverty line]/[# of people for whom poverty status is determined])*100
    Source: US Census Bureau

  • Child Poverty Rate: The percentage of children under 18 whose families' income falls below the poverty threshold for their family size.
    Formula: ([# of children with income less than poverty level]/[total children with poverty status determined])*100
    Source: US Census Bureau

  • Students Eligible for Free or Reduced Lunch Program: Qualification is based on the Department of Health and Human Services federal poverty guidelines for a given household size. Households with net income at or below 130% of the guidelines qualify for free lunches; those between 130% and 185% qualify for reduced price lunches.
    Formula: (([#eligible for free lunch]+[# eligible for reduced price lunch])/[total enrolled students)*100
    Source: Oregon Department of Education

  • Extreme Poverty Rate: The percentage of individuals with family income less than 50% of the poverty threshold that corresponds to their family size.
    Formula: ([# of individuals at 50% of poverty]/[total # of people for whom poverty status is determined])*100
    Source: US Census Bureau

  • Individuals with Income 185% of the Poverty Level: The percentage of individuals with family income less than or equal to 185% of the poverty threshold that corresponds to their family size.
    Formula: ([# of individuals with income less than 185% of poverty level]/[total individuals with poverty status determined])*100
    Source: US Census Bureau
    Use the Advanced Mapping Tool to show individuals with income at 185% of the poverty level by census tract, for 2000

  • Per capita Personal Income as a Percentage of US Personal Income: Per capita personal income expressed as a percentage of the US per capita personal income.
    Formula: ([local per capita income]/[U.S. per capita income])*100
    Source: US Bureau of Economic Analysis Regional Economic Accounts

  • Household Income Types: Wage & Salary, Social Security, Public Assistance, and retirement: The percentage of households receiving these types of income.
    Formula example: ([# households with wage & salary income]/[# of all households])*100
    Source: US Census Bureau

  • Income Distribution: A bar graph where each bar represents the number of households with annual income in that income range.
    Source: US Census Bureau


Fisher, Monica. 2007. Why is U.S. Poverty Higher in Nonmetropolitan than in Metropolitan Areas? Growth and Change 38 (1): 56-76.

Nord, Mark. 1998. Poor People on the Move: County-To-County Migration and the Spatial Concentration of Poverty. Journal of Regional Science 38(2): 329-351.

Nord, Mark. 2000. Does It Cost Less to Live in Rural Areas? Evidence from New Data on Food Security and Hunger. Rural Sociology 65(1): 104-125.

Weber, Bruce, Leif Jensen, Kathleen Miller, Jane Mosley and Monica Fisher. 2005. A Critical Review of Rural Poverty Literature: Is There Truly a Rural Effect? International Regional Science Review 28(4): 381-414.

Zimmerman, Julie, Sunny (Seonok) Ham, and Sarah Frank. 2008. Does it or Doesn't it? Geographic Differences and the Costs of Living. Rural Sociology 73(3): 463-486.

Authored and compiled by Mindy Crandall, Faculty Research Assistant, Oregon State University Extension Service (2008)