America’s baby boom generation is beginning to transition out of the oldest working cohorts and into the youngest retiring cohorts. The size of this transition is presenting challenges to local and regional planners and national programs [1]. It is also expected to ensure, along with still lengthening life spans [2], that the old-age dependency ratio, which measures the number of older people (age 65 or older) as a share of those of working age (between the ages 16 and 64), will rise quickly over the next twenty-five years. Some impacts of the so-called silver tsunami might become amplified if labor force participation rates among prime age workers (ages 25 to 54) continue to decline as expected [3].
Social scientists have documented age-related migration patterns up and down the US urban hierarchy (e.g., [4][5][6]) and found, for example, that movers in the emerging adult group (ages 15 to 24) typically move up the hierarchy toward larger places with more education or employment opportunities than home supplies. Conversely, movers in the empty-nester / early retiree age group (ages 55 to 64) move effectively down the urban hierarchy and predominantly toward amenity-rich micropolitan and rural counties. The Delaware River Watershed (DRW) hosts a strong rural-to-urban gradient and many boomers that are now between the ages 55 and 64.
Using population projections produced by the five states that intersect the DRW [7][8][9][10][11], we calculated and mapped old-age dependency ratios, by county, for the period 2010 to 2040 (see accompanying figure). According to our results, the old-age dependency ratio for the entire region is projected to increase from 23.0, in 2010, to 41.8, by 2040. Three metropolitan counties exhibited the lowest ratios in 2010 (Orange County, NY – 16.9; Sussex County, NJ – 17.7; Philadelphia County, PA – 17.9) and are projected to have the lowest (albeit higher) ratios into 2040. In 2010, three metropolitan counties in the southern and coastal part of the watershed exhibited the highest old-age dependency ratios (Ocean County, NJ – 36.1; Cape May County, NJ – 34.7; Sussex County, DE – 34.2), but three nonmetropolitan counties in the northern part of the watershed are projected to exhibit some of the highest ratios by the year 2030 (Delaware County, NY – 66.1; Wayne County, PA – 53.3; Chenango County, NY – 50.6). At least 40% of DRW counties are expected to exhibit old-age dependency ratios that double sometime before 2040.
Our findings are based on traditional retirement ages and projections that rely on some necessary assumptions about future fertility and mortality rates, migration rates. Those noted, the aging DRW population is still predictable and important to consider, for older footloose persons generally demand products and services that are different from those required by younger persons who are tied to places of work (or schools) and trying to establish themselves or households. Mapping where concentrations of older persons are expected to change rapidly can reveal places where economic and political opportunities and challenges might follow, and it can help conservationists and planners consider how to talk about protecting clean water supplies in the Delaware River Watershed amid a substantial demographic transition.
– Scott A. Drzyzga
References cited
[1] Ortman, Jennifer M., Victoria A. Velkoff, and Howard Hogan. 2014. An Aging Nation: The Older Population in the United States, Current Population Reports, P25-1140. U.S. Census Bureau, Washington, DC. Last accessed on June 18, 2016 at https://www.census.gov/prod/2014pubs/p25-1140.pdf
[2] Centers for Disease Control and Prevention. 2013. The State of Aging and Health in America 2013. Atlanta, GA: Centers for Disease Control and Prevention, US Dept of Health and Human Services. Last accessed on June 18, 2016 at http://www.cdc.gov/aging/pdf/state-aging-health-in-america-2013.pdf
[3] Toosi, Mitra. 2012. Projections of the labor force to 2050: a visual essay. US Bureau of Labor Statistics Monthly Labor Review (October 2012). Last accessed on June 23, 2016 at http://www.bls.gov/opub/mlr/2012/10/art1full.pdf
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[5] Plane, David A., and Jason R. Jurjevich. 2009. Ties That No Longer Bind? The Patterns and Repercussions of Age-Articulated Migration. The Professional Geographer, 61(1):4-20.
[6] Partridge, Mark. D. 2010. The duelling models: NEG vs amenity migration in explaining US engines of growth. Papers in Regional Science, 89(3):513-536.
[7] The Center for Rural Pennsylvania. 2014. State and County Population Projections by Age and Gender, Pennsylvania: 2010 to 2040. Pennsylvania State Data Center. Last accessed on June 23, 2016 at https://pasdc.hbg.psu.edu/Data/Projections/tabid/1013/Default.aspxhttp://www.rural.palegislature.us/documents/reports/Population_Projections_Report.pdf
[8] Delaware Population Consortium. 2015. Annual Population Projections – Version 2015.0. State of Delaware Office of State Planning Coordination. Last accessed on June 23, 2016 at http://stateplanning.delaware.gov/information/dpc_projections.shtml
[9] Maryland Department of Planning. 2015. Total population projections by age, sex, and race – January 2015. Maryland State Data Center. Last accessed on June 23, 2016 at http://www.mdp.state.md.us/msdc/s3_projection.shtml
[10] Program on Applied Demographics at Cornell University. 2011. New York State Projection Data by County. New York State Department of Labor. Last accessed on June 23, 2016 at https://labor.ny.gov/stats/nys/statewide-population-data.shtm
[11] State of New Jersey Department of Labor and Workforce Development. 2012. Projections of County Population by Sex and Age: New Jersey, 2012 to 2032. State of New Jersey Department of Labor and Workforce Development. Last accessed on June 23, 2016 at http://lwd.dol.state.nj.us/labor/lpa/dmograph/lfproj/lfproj_index.html
