John Cromartie

Metropolitan, Urban, and Rural Commuting Areas: Toward a Better Depiction of the United States Settlement System.

Discontent with the current definition of metropolitan areas and the lack of differentiation within nonmetropolitan territory provided the incentive for the research presented here. Census tracts rather than counties were used as the building blocks for assignment of tracts, not just to metropolitan areas, but also to larger towns (10,000 to 49,999) and to smaller urban places (2,500 to 9,999). The analysis used 1990 census-defined urbanized areas and tract-to-tract commuter flows. Results include a modest shift of population from metropolitan to nonmetropolitan, as well as a significant reduction in the areal size of metropolitan areas, disaggregation of many areas, and frequent reconfiguration to a more realistic settlement form. [Key words: metropolitan, urban-rural, commuting.]

Micropolitan Areas and the Measurement of American Urbanization

With the official designation of micropolitan areas in June 2003, as part of the new core-based statistical area system, non-metropolitan territory is no longer an undifferentiated residual. In this paper we compare the demographic and socioeconomic characteristics of a preliminary set of micropolitan areas with more highly urbanized territory and with territory outside core-based statistical areas, to answer questions about the micropolitan categorys conceptual validity. Demographic and economic data are used, along with a mail survey of county officials in a random sample of small metropolitan, micropolitan, and non-core-based statistical areas (non-CBSAs). The analysis shows substantial differentiation between micropolitan and non-CBSA areas, and demonstrates the importance of distinguishing between these two types of non-metropolitan areas. As an intermediate category, micropolitan areas provide stability to the decade-to-decade swings in non-metropolitan population change during periods of higher out-migration, but share almost equally with non-CBSA areas in attracting migrants during periods of high non-metropolitan in-migration. In terms of services available and their function as urban centers, micropolitan areas are intermediate between small metropolitan and non-CBSA areas, but more similar to small metropolitan areas.

Baby Boom Migration and Its Impact on Rural America

Members of the baby boom cohort, now 45-63 years old, are approaching a period in their lives when moves to rural and small-town destinations increase. An analysis of age-specific, net migration during the 1990s reveals extensive shifts in migration patterns as Americans move through different life-cycle stages. Assuming similar age patterns of migration, this report identifies the types of nonmetropolitan counties that are likely to experience the greatest surge in baby boom migration during 2000-20 and projects the likely impact on the size and distribution of retirement-age populations in destination counties. The analysis finds a significant increase in the propensity to migrate to nonmetro counties as people reach their fifties and sixties and projects a shift in migration among boomers toward more isolated settings, especially those with high natural and urban amenities and lower housing costs. If baby boomers follow past migration patterns, the nonmetro population age 55-75 will increase by 30 percent between now and 2020.

Nonmetropolitan Outmigration Counties: Some are Poor, Many are Prosperous

Population loss through net outmigration is endemic to many rural areas. Over a third of nonmetro counties lost at least 10 percent of their population through net outmigration over 1988-2008. Some of these counties have had very high poverty rates, substantial loss in manufacturing jobs, and high unemployment. Lack of economic opportunity was likely a major factor in their high outmigration. Most high net outmigration counties, however, are relatively prosperous, with low unemployment rates, low high school dropout rates, and average household incomes. For these counties, low population density and less appealing landscapes distinguish them from other nonmetro counties. Both types of outmigration counties stand out on two measures, indicating that quality-of-life factors inhibit inmigration: a lack of retirees moving in and local manufacturers citing the area’s unattractiveness as a problem in recruiting managers and professionals.

Reasons for Returning and Not Returning to Rural U.S. Communities

Population loss persists in nonmetropolitan America, especially in isolated counties with limited natural amenities. Communities in these counties experience high levels of outmigration among high school graduates, but low in-migration is more important in distinguishing declining from growing nonmetropolitan counties, and return migration is a much more prominent component of in-migration to these locationally disadvantaged areas. This research uses a multisited, interview-based methodology to understand the factors that influence decisions of people in their late twenties to late forties to move back to rural communities and the barriers that keep others from making such moves. The life course segment considered here captures a critical “settling down” period when career and family obligations overlap and return migration peaks. Interviews at high school reunions, the only venues where stayers, return migrants, and nonreturn migrants are found together, show that limited rural employment opportunities are barriers for nonreturnees. Others intent on returning find ways to secure or create employment but are primarily influenced to move home by family concerns. Connections to the larger social and physical environment of the community are important as well. Interviews affirm that factors affecting migration decisions work in combination, and ties to both people and place are critical for understanding rural return migration.

Intergenerational Relationships and Rural Return Migration

Many rural communities lose population through outmigration of rural youth, resulting in a high concentration of elderly. Concern about these issues sparked our interest in researching rural return migration as a way of countering net migration loss. In the process, we found that intergenerational family dynamics and aging parents residing in the rural hometown are critical for promoting the return move of adult children and grandchildren. Intergenerational relationships and migration to be closer to family provide a context for understanding these moves. Prior research on intergenerational relationships and geographic proximity has focused on the moves of aging parents toward adult children, often using quantitative methodologies. This research focuses on the moves of adult children, using a qualitative methodology. It reveals that the return move of adult children can substitute for aging parents’ move away from a long-term rural residence to live closer to adult children and grandchildren. Migration decisions on the part of adult children thus affect elderly parents’ opportunities for aging in place. Community leaders, especially in relatively isolated, rural towns that find it difficult to attract newcomers, should become cognizant that aging parents can attract younger generations back to their rural home towns.

Defining frontier areas in the United States

Demand is growing for a statistically based, nationally consistent definition of frontier territory, one that is adjustable within a reasonable range and applicable in different research and policy contexts. The need arises from Congressional mandates affecting rural health programs and from limitations of previous classification schemes. As used here, the term frontier denotes territory characterized by some combination of relatively low-population density and high geographic remoteness. Two features distinguish the methodology described here from earlier classifications. First, the approach strives for the most accurate measures of distance possible for the smallest units of geography containing population data. Travel time by car to nearby urban areas is calculated for coterminous US territory at the 1 × 1 kilometer grid level. Once frontier territory is delimited at the grid level, frontier populations may be summed to ZIP code areas, as demonstrated on the Main Map, or to census tracts, counties, or other useful geographic entities. Second, travel-time thresholds around urban areas were allowed to vary by urban-area population size. This is desirable because the effect of urban population size on adjacent rural population density is discontinuous. At any given distance from an urban area, population density increases as the size of the nearby urban area increases.

METRO EXPANSION AND NONMETRO CHANGE IN THE SOUTH

Demographic trends over the past several decades reflect a relentless geographic expansion of U.S. metropolitan (metro) areas, a steady rise in the number of long-distance commuters, and rapid population growth in adjacent, nonmetropolitan (nonmetro) counties. As suburbs expand, nearby nonmetro counties enter a period of change marked by increasing economic integration with metro economies, steady losses of rural and small-town landscapes and livelihoods, and eventual reclassification from nonmetro to metro status. Such transitions intensified during the 1990s as migration into nonmetro areas rebounded. Given the complexity of land-use patterns and socioeconomic conditions emerging along the metro-nonmetro boundary, it’s important to understand the transition process and its effect on communities and people. In addition, such extensive transitions call into question the use of nonmetro counties to identify rural and small town settlement areas. Researchers and policy makers must apply rural and urban concepts cautiously or even consider new thinking altogether. In this paper I examine what happens to nonmetro counties and their mostly rural and small-town settlement patterns as they become metro. Previous research assumed no systematic process by which nonmetro counties became integrated into metro areas, and no one has proposed or measured any type of transitional sequence. I attempt to do this by exploring the following questions concerning metro expansion and nonmetro change in the South: 1. Over time, is it possible to describe a consistent developmental pattern followed by a significant portion of nonmetro counties in the process of becoming metro? In particular, would this sequence commonly include a period of increasing commuting from the rural and small town periphery prior to suburban in-migration and the land-use changes associated with sprawl? 2. At any given point in time, is it possible to distinguish counties at different stages in this developmental sequence? In particular, is it possible to

Subprime Lending and its Impacts on Rural Housing Markets

Abstract Housing markets and mortgage lending played critical roles in the ‘Great Recession,’yet the ways in which this recent and acute economic crisis have played out within rural and small town America are poorly understood. The narrow research and media focus on overheated housing markets in rapidly growing metropolitan areas such as Las Vegas or Phoenix is understandable, yet housing plays a somewhat distinct role in rural communities where a larger share of the population owns their own home, and a larger proportion of the workforce is employed in the home construction sector. This paper draws on an array of publically available data sources to examine various dimensions of nonmetropolitan subprime lending and housing markets at different spatial scales over the time period leading up to and following the ‘Great Recession. ‘ At the county level, analysis revealed striking regional variation in nonmetropolitan subprime lending. Individual-level analysis highlights the racial, economic, and geographic factors that distinguished subprime borrowers. The final stage of analysis focused on housing units financed with higher cost loans and revealed these structures to be older, experience greater residential turnover, and to be increasingly likely to be ‘underwater’ as their homeowners owed more than the properties were currently worth.