A neural network architecture for disaggregating age-specific population projections to the sub-national level

20889 8 111209 2 336408 document 111209 WP-25-003.pdf application/pdf 64164f7ce11d184527916a3375bf0fb2 MD5 2063729 2025-09-23 06:48:00 https://pure.iiasa.ac.at/id/eprint/20889/1/WP-25-003.pdf 20889 1 1 application/pdf text en public cc_by_nc_4

WP-25-003.pdf

published 111210 1 336415 document 111210 indexcodes.txt text/plain f92728148014fb5e5312a0e418208004 MD5 18547 2025-09-23 06:58:13 https://pure.iiasa.ac.at/id/eprint/20889/2/indexcodes.txt 20889 2 2 text/plain other Generate index codes conversion from text to indexcodes en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/111209 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/111209 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/111209 archive 353 disk0/00/02/08/89 2025-09-23 06:51:07 2025-09-23 06:51:07 2025-09-23 06:51:07 monograph show 1 Tamburini A. 2501 Bosco C. Striessnig S. Anne Goujon, Population and Just Societies Program A neural network architecture for disaggregating age-specific population projections to the sub-national level pub POPJUS MDM MIG Improving our understanding of future risk from climate change requires realistic projections of future populations, both in their size and distribution. Distribution refers not only to geographic breakdowns but also to the breakdown by important characteristics, such as age. While the location where people will live may determine future exposure to hazards, population characteristics also co-determine the degree of vulnerability and the capacity to adapt to changing environmental conditions. Despite the importance of these factors, there remains a paucity of population projections (or disaggregations thereof) at the sub-national level. We develop a machine learning-based model to disaggregate age-specific population projections based on the Shared Socioeconomic Pathways (SSPs) to the sub-national NUTS-2 level for 34 European countries. Our focus on Europe is driven by its high degree of spatial variability, both in terms of climatic conditions and population structure, as well as the rapid pace of climate change and population aging there. 2025-09-23 published WP-25-003 3738 public working_paper Laxenburg, Austria Socioeconomic Pathways, Adaptation and Resilience to Changing CLimate in Europe (SPARCCLE, HE 101081369) yes info:eu-repo/grantAgreement/EC/HE/101081369/EU//SPARCCLE info:eu-repo/semantics/book info:eu-repo/semantics/openAccess