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Metropolitan Reclassification and the Urbanization of Rural America

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Demography

Abstract

We highlight the paradoxical implications of decadal reclassification of U.S. counties (and America’s population) from nonmetropolitan to metropolitan status between 1960 and 2017. Using data from the U.S. Census Bureau, we show that the reclassification of U.S. counties has been a significant engine of metropolitan growth and nonmetropolitan decline. Over the study period, 753—or nearly 25% of all nonmetropolitan counties—were redefined by the Office of Management and Budget (OMB) as metropolitan, shifting nearly 70 million residents from nonmetropolitan to metropolitan America by 2017. All the growth since 1970 in the metropolitan share of the U.S. population came from reclassification rather than endogenous growth in existing metropolitan areas. Reclassification of nonmetropolitan counties also had implications for drawing appropriate inferences about rural poverty, population aging, education, and economic growth. The paradox is that these many nonmetropolitan “winners”—those experiencing population and economic growth—have, over successive decades, left behind many nonmetropolitan counties with limited prospects for growth. Our study provides cautionary lessons regarding the commonplace narrative of widespread rural decline and economic malaise but also highlights the interdependent demographic fates of metropolitan and nonmetropolitan counties.

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Data Availability

All the data used are publicly available from the sources listed in the Data section of this article.

Notes

  1. We use the terms rural and nonmetropolitan as well as metropolitan and urban interchangeably here.

  2. A substantial majority of nonmetropolitan residents voted for Donald Trump over Hillary Clinton, seemingly registering their dissatisfaction with the political status quo and urban-centric political concerns and public policy (Scala and Johnson 2017; Wuthnow 2018).

  3. A 2015 National Academy of Sciences report on the “Workshop on Rationalizing Rural Area Classifications” highlighted this central point (Wunderlich 2016). Throughout U.S. demographic history, rural people and places have become part of the urban population through rural-to-urban migration but also through reclassification by OMB as nonmetropolitan populations are redefined as metropolitan.

  4. Recent data suggest that nonmetropolitan areas have resumed growth in the past two years, although they have lost population over the entire period from 2010 to 2018 (Johnson 2019).

  5. The number of counties will vary slightly from analysis to analysis because of boundary changes that complicate longitudinal analysis. Over the past century, a few new counties have been added, others have had boundary changes, and Virginia has introduced the concept of independent cities.

  6. There are minor differences between the decadal reclassifications reported here and the early and late transition counties reported earlier. A modest number of decadal reclassifications were temporary. For example, a few counties reclassified as metropolitan in 1973 reverted to nonmetropolitan status in 1983. Such counties would be included in the decadal changes but not in the early and late transition classification, which delineates change over longer periods.

  7. There is considerable disagreement about the most appropriate income measure to define economic well-being (Katz 2012). Katz noted that alternative income measures differ in terms of the sources of income (earnings or non-earned income, such as pension income) and their sensitivity to demographic factors, such as household size or number of working adults. Here per capita income is used. The correlation between the per capita income and median family income, for example, is quite high (.8), so overall patterns evident in one measure will be reflected in the other.

  8. Detailed analysis of the longitudinal patterns of education and the other three human capital indicators (not included here) reveals that the significant gap between the continuously nonmetropolitan and the transition counties already existed in 1970 and remained relatively stable between 1970 and 2017. For example, the percentage of college graduates was 44% higher in the early transition counties than in continuously nonmetropolitan counties in 1970. In 2017, the gap was 48%. For per capita income, the percentage income difference between the early transition and continuously nonmetropolitan was 16.6% in 1970 and 21% in 2017. Thus, it was not becoming metropolitan that created the substantial differences in 2017 but rather the counties that transitioned had higher levels of human capital to begin with.

  9. To maintain consistency with data provided by the Economic Research Service of the USDA (2019), we calculate the poverty rate as the number of people below the poverty line divided by the total population. This is not consistent with the U.S. Census Bureau calculation of the poverty rate, which is the number of people below the poverty line divided by the population for whom poverty status is known. As a result, our measure is lower than the official poverty rate. For example, in 2017, the official poverty rate was 14.6% compared with our reported percentage in poverty of 13.2%.

References

  • Brown, D. L. (1979). Metropolitan reclassification: Some effects on the characteristics of the population in metropolitan and nonmetropolitan counties. Rural Sociology, 44, 791–801.

    Google Scholar 

  • Bureau of Economic Analysis. (2019). Personal income by county, metro and other areas (Report). Retrieved from https://www.bea.gov/data/income-saving/personal-income-county-metro-and-other-areas

  • Cromartie, J. B. (2017). Rural areas show overall population decline and shifting regional patterns of population change (Amber Waves report). Washington, DC: U.S. Department of Agriculture, Economic Research Service. Retrieved from https://www.ers.usda.gov/amber-waves/2017/september/rural-areas-show-overall-population-decline-and-shifting-regional-patterns-of-population-change/

  • Fallows, J. (2019, May 28). The rural-urban divide is more complicated than you think. The Atlantic Magazine. Retrieved from https://www.theatlantic.com/notes/2019/05/rural-urban-divide-more-complicated-you-think/590326/

  • Frey, W. H. (2017). The fading of city-suburb and metro-nonmetro distinctions in the United States. In T. Champion & G. Hugo (Eds.), New forms of urbanization: Beyond the rural-urban dichotomy (pp. 67–88). New York, NY: Routledge.

    Chapter  Google Scholar 

  • Fuguitt, G. V., Heaton, T. B., & Lichter, D. T. (1988). Monitoring the metropolitanization process. Demography, 25, 115–128.

    Article  Google Scholar 

  • Gibson, C. (2010). American demographic history chartbook: 1790 to 2010. Retrieved from http://demographicchartbook.com/

  • Glasgow, N., & Brown, D. L. (2012). Rural ageing in the United States: Trends and contexts. Journal of Rural Studies, 28, 422–431.

    Article  Google Scholar 

  • Goetz, S. J., Partridge, M. D., & Stephens, H. M. (2018). The economic status of rural America in the President Trump era and beyond. Applied Economic Perspectives and Policy, 40, 97–118.

    Article  Google Scholar 

  • James, W., Cossman, J., & Wolf, J. (2019, January 21). The ultimate inequality: Vast mortality disparities across U.S. regions. N-IUSSP on-line news magazine. Retrieved from http://www.niussp.org/article/the-ultimate-inequality-vast-mortality-disparities-across-u-s-regionsde-grandes-disparites-de-mortalite-entre-les-regions-americaines/#more-3306

  • Johnson, K. M. (2011). The continuing incidence of natural decrease in American counties. Rural Sociology, 76, 74–100.

    Article  Google Scholar 

  • Johnson, K. M. (2019). Rural America growing again due to migration gains (Carsey Data Snapshot). Durham: University of New Hampshire, Carsey School of Public Policy.

    Book  Google Scholar 

  • Johnson, K. M., Field, L. M., & Poston, D. L. (2015). More deaths than births: Subnational natural decrease in Europe and the United States. Population and Development Review, 41, 651–680.

  • Johnson, K. M., & Lichter, D. T. (2008). Natural increase: A new source of population growth in emerging Hispanic destinations in the United States. Population and Development Review, 34, 327–346.

    Article  Google Scholar 

  • Johnson, K. M., & Lichter, D. T. (2016). Diverging demography: Hispanic and non-Hispanic contributions to U.S. population redistribution and diversity. Population Research and Policy Review, 35, 705–725.

    Article  Google Scholar 

  • Johnson, K. M., & Lichter, D. T. (2019). Rural depopulation: Growth and decline processes over the past century. Rural Sociology, 84, 3–27.

    Article  Google Scholar 

  • Johnson, K. M., Nucci, A., & Long, L. (2005a). Population trends in metropolitan and nonmetropolitan America: Selective deconcentration and the rural rebound. Population Research and Policy Review, 24, 527–542.

    Article  Google Scholar 

  • Johnson, K. M., Voss, P. R., Hammer, R. B., Fuguitt, G. V., & McNiven, S. (2005b). Temporal and spatial variation in age-specific net migration in the United States. Demography, 42, 791–812.

    Article  Google Scholar 

  • Johnson, K. M., & Winkler, R. (2015). Migration signatures across the decades: Net migration by age in U.S. counties, 1950–2010. Demographic Research, 22, 1065–1080. https://doi.org/10.4054/DemRes.2015.32.38

  • Katz, A. J. (2012). Explaining long-term differences in census and BEA measures of household income (BEA Working Paper). Washington, DC: Bureau of Economic Analysis. Retrieved from https://www.bea.gov/research/papers/2012/explaining-long-term-differences-between-census-and-bea-measures-household

  • Lichter, D. T., & Brown, D. L. (2011). Rural America in an urban society: Changing spatial and social boundaries. Annual Review of Sociology, 37, 565–592.

    Article  Google Scholar 

  • Lichter, D. T., & Ziliak, J. P. (2017). The rural-urban interface: New patterns of spatial interdependence and inequality in America. Annals of the American Academy of Political and Social Science, 672, 6–25.

    Article  Google Scholar 

  • Monnat, S. M., & Brown, D. L. (2017). More than a rural revolt: Landscapes of despair and the 2016 presidential election. Journal of Rural Studies, 55, 227–236.

    Article  Google Scholar 

  • Murdock, S. H., Cline, M., & Zey, M. (2012). Challenges in the analysis of rural populations in the United States. In L. J. Kulcsar & K. J. Curtis (Eds.), International handbook of rural demography (pp. 7–15). Dordrecht, the Netherlands: Springer.

  • Nucci, A., & Long, L. (1995). Spatial and demographic dynamics of metropolitan and nonmetropolitan territory in the United States. International Journal of Population Geography, 1, 165–181.

    Article  Google Scholar 

  • Office of Management and Budget (OMB). (1998). Alternative approaches to defining metropolitan and nonmetropolitan areas. Federal Register, 63, 70526–70561.

  • Office of Management and Budget (OMB). (2010). 2010 standards for delineating metropolitan and micropolitan statistical areas. Federal Register, 74, 37245–37252.

  • Scala, D. J., & Johnson, K. M. (2017). Political polarization along the rural-urban continuum? The geography of the presidential vote, 2000–2016. Annals of the American Academy of Political and Social Science, 672, 162–184.

    Article  Google Scholar 

  • Schaeffer, P. V., Kahsai, M. S., & Jackson, R. W. (2013). Beyond the rural–urban dichotomy: Essay in honor of Professor A. M. Isserman. International Regional Science Review, 36, 81–96.

    Article  Google Scholar 

  • Thiede, B., Brown, D. L., Sanders, S. R., Glasgow, N., & Kulcsar, L. J. (2017). A demographic deficit? Local population aging and access to services in rural America, 1990–2010. Rural Sociology, 82, 44–74.

    Article  Google Scholar 

  • Thiede, B., Kim, H., & Valasik, M. (2018). The spatial concentration of America’s rural poor population: A post-recession update. Rural Sociology, 83, 109–144.

    Article  Google Scholar 

  • U.S. Census Bureau. (2018). Annual estimates of the resident population: April 1 2010 to July 1 2017 [Data set]. Retrieved from https://www.census.gov/data/tables/time-series/demo/popest/2010s-counties-total.html

  • U.S. Department of Agriculture (USDA). (2019). Data sources for poverty and education [County-level data sets]. Washington, DC: U.S. Department of Agriculture, Economic Research Service. Retrieved from https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/

  • Van Dam, A. (2019, May 24). The real (surprisingly comforting) reason rural America is doomed to decline. The Washington Post. Retrieved from https://www.washingtonpost.com/business/2019/05/24/real-surprisingly-comforting-reason-rural-america-is-doomed-decline/

  • Winkler, R. L., Johnson, K. M., Cheng, C., Voss, P. R., & Curtis, K. J. (2013). County-specific net migration by five-year age groups, Hispanic origin, race and sex 2000–2010 (CDE Working Paper 2013-04). Madison: University of Wisconsin–Madison, Center for Demography and Ecology.

  • Wunderlich, G. S. (2016). Rationalizing rural area classifications for the economic research service: A workshop summary. Washington, DC: National Academies Press.

    Google Scholar 

  • Wuthnow, R. (2018). The left behind: Decline and rage in rural America. Princeton, NJ: Princeton University Press.

    Book  Google Scholar 

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Acknowledgments

The authors gratefully acknowledge John Cromartie of the Economic Research Service of the USDA for his contribution to the early analytical work on this project. Kenneth Johnson’s research was supported by an Andrew Carnegie Fellowship from the Carnegie Corporation of New York and by the New Hampshire Agricultural Experiment Station in support of Hatch Multi-State Regional Project W-4001 through joint funding of the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award number 1013434, and the state of New Hampshire. Barbara Cook of the Carsey School of Public Policy provided GIS support. The content is solely the responsibility of the authors and does not necessarily represent the official views of the agencies supporting their research.

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Authors and Affiliations

  1. Department of Sociology and Carsey School of Public Policy, University of New Hampshire, 345B McConnell Hall, 15 Academic Way, Durham, NH, 03824, USA

    Kenneth M. Johnson

  2. Department of Policy Management and Analysis and Cornell Population Center, Cornell University, MVR 3226, Ithaca, NY, 14853, USA

    Daniel T. Lichter

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  1. Kenneth M. Johnson
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  2. Daniel T. Lichter
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Both authors contributed equally to the conception, design, and execution of the project, including drafting and editing the final manuscript. Johnson was responsible for the acquisition and management of data and carried out the analyses in consultation with Lichter. Both authors read and approved the final manuscript.

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Correspondence to Kenneth M. Johnson.

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Johnson, K.M., Lichter, D.T. Metropolitan Reclassification and the Urbanization of Rural America. Demography 57, 1929–1950 (2020). https://doi.org/10.1007/s13524-020-00912-5

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