Empirically based spatial projections of US population age structure consistent with the shared socioeconomic pathways
Spatially-explicit population projections by age are increasingly needed for understanding bilateral human–environment interactions. Conventional demographic methods for projecting age structure experience substantial challenges at small spatial scales. In search of a potentially better-performing a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2019-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ab4a3a |
| _version_ | 1797747920897835008 |
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| author | Erich Striessnig Jing Gao Brian C O’Neill Leiwen Jiang |
| author_facet | Erich Striessnig Jing Gao Brian C O’Neill Leiwen Jiang |
| author_sort | Erich Striessnig |
| collection | DOAJ |
| description | Spatially-explicit population projections by age are increasingly needed for understanding bilateral human–environment interactions. Conventional demographic methods for projecting age structure experience substantial challenges at small spatial scales. In search of a potentially better-performing alternative, we develop an empirically based spatial model of population age structure and test its application in projecting US population age structure over the 21st century under various socioeconomic scenarios (SSPs). The model draws on 40 years of historical data explaining changes in spatial age distribution at the county level. It demonstrates that a very good model fit is achievable even with parsimonious data input, and distinguishes itself from existing methods as a promising approach to spatial age structure modeling at the global level where data availability is often limited. Results suggest that wide variations in the spatial pattern of county-level age structure are plausible, with the possibility of substantial aging clustered in particular parts of the country. Aging is experienced most prominently in thinly populated counties in the Midwest and the Rocky Mountains, while cities and surrounding counties, particularly in California, as well as the southern parts of New England and the Mid-Atlantic region, maintain a younger population age structure with a lower proportion in the most vulnerable 70+ age group. The urban concentration of younger people, as well as the absolute number of vulnerable elderly people can vary strongly by SSP. |
| first_indexed | 2024-03-12T15:57:34Z |
| format | Article |
| id | doaj.art-4b3b59efebfd48e1972126a674d39841 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:57:34Z |
| publishDate | 2019-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-4b3b59efebfd48e1972126a674d398412023-08-09T14:47:17ZengIOP PublishingEnvironmental Research Letters1748-93262019-01-01141111403810.1088/1748-9326/ab4a3aEmpirically based spatial projections of US population age structure consistent with the shared socioeconomic pathwaysErich Striessnig0https://orcid.org/0000-0001-5419-9498Jing Gao1https://orcid.org/0000-0003-1778-8909Brian C O’Neill2https://orcid.org/0000-0001-7505-8897Leiwen Jiang3https://orcid.org/0000-0002-2073-6440Wittgenstein Centre for Demography and Global Human Capital (IIASA, VID/ÖAW, WU), AustriaUniversity of Delaware , United States of AmericaUniversity of Denver , United States of AmericaPopulation Council, United States of America; Asian Demographic Research Institute (ADRI), People’s Republic of ChinaSpatially-explicit population projections by age are increasingly needed for understanding bilateral human–environment interactions. Conventional demographic methods for projecting age structure experience substantial challenges at small spatial scales. In search of a potentially better-performing alternative, we develop an empirically based spatial model of population age structure and test its application in projecting US population age structure over the 21st century under various socioeconomic scenarios (SSPs). The model draws on 40 years of historical data explaining changes in spatial age distribution at the county level. It demonstrates that a very good model fit is achievable even with parsimonious data input, and distinguishes itself from existing methods as a promising approach to spatial age structure modeling at the global level where data availability is often limited. Results suggest that wide variations in the spatial pattern of county-level age structure are plausible, with the possibility of substantial aging clustered in particular parts of the country. Aging is experienced most prominently in thinly populated counties in the Midwest and the Rocky Mountains, while cities and surrounding counties, particularly in California, as well as the southern parts of New England and the Mid-Atlantic region, maintain a younger population age structure with a lower proportion in the most vulnerable 70+ age group. The urban concentration of younger people, as well as the absolute number of vulnerable elderly people can vary strongly by SSP.https://doi.org/10.1088/1748-9326/ab4a3aspatial populationage structurepopulation projectionsshared socioeconomic pathways |
| spellingShingle | Erich Striessnig Jing Gao Brian C O’Neill Leiwen Jiang Empirically based spatial projections of US population age structure consistent with the shared socioeconomic pathways Environmental Research Letters spatial population age structure population projections shared socioeconomic pathways |
| title | Empirically based spatial projections of US population age structure consistent with the shared socioeconomic pathways |
| title_full | Empirically based spatial projections of US population age structure consistent with the shared socioeconomic pathways |
| title_fullStr | Empirically based spatial projections of US population age structure consistent with the shared socioeconomic pathways |
| title_full_unstemmed | Empirically based spatial projections of US population age structure consistent with the shared socioeconomic pathways |
| title_short | Empirically based spatial projections of US population age structure consistent with the shared socioeconomic pathways |
| title_sort | empirically based spatial projections of us population age structure consistent with the shared socioeconomic pathways |
| topic | spatial population age structure population projections shared socioeconomic pathways |
| url | https://doi.org/10.1088/1748-9326/ab4a3a |
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