{"title":"Bayesian Projection of Extant Refugee and Asylum Seeker Populations.","authors":"Herbert P Susmann, Adrian E Raftery","doi":"10.1215/00703370-12338328","DOIUrl":null,"url":null,"abstract":"<p><p>Estimates of future migration patterns are of broad interest in demography. Forced migration, including refugee and asylum seekers, plays an important role in overall migration patterns but is notoriously difficult to forecast. Focusing on refugees and asylum seekers, we propose a modeling pipeline based on Bayesian hierarchical time-series modeling for projecting refugee population official statistics by country of origin using data from the United Nations High Commissioner for Refugees. Our approach is based on a conceptual model of refugee and asylum seeker populations following growth and decline phases, separated by a peak. The growth and decline phases are modeled by logistic growth and decline through an interrupted logistic process model. We evaluate our method through a set of validation exercises that show it has good performance for forecasts at 1-, 5-, and 10-year horizons, and we present projections for 35 countries of origin of large refugee and asylum seeker populations.</p>","PeriodicalId":48394,"journal":{"name":"Demography","volume":" ","pages":"1899-1915"},"PeriodicalIF":3.5000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Demography","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1215/00703370-12338328","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
引用次数: 0
Abstract
Estimates of future migration patterns are of broad interest in demography. Forced migration, including refugee and asylum seekers, plays an important role in overall migration patterns but is notoriously difficult to forecast. Focusing on refugees and asylum seekers, we propose a modeling pipeline based on Bayesian hierarchical time-series modeling for projecting refugee population official statistics by country of origin using data from the United Nations High Commissioner for Refugees. Our approach is based on a conceptual model of refugee and asylum seeker populations following growth and decline phases, separated by a peak. The growth and decline phases are modeled by logistic growth and decline through an interrupted logistic process model. We evaluate our method through a set of validation exercises that show it has good performance for forecasts at 1-, 5-, and 10-year horizons, and we present projections for 35 countries of origin of large refugee and asylum seeker populations.
期刊介绍：
Since its founding in 1964, the journal Demography has mirrored the vitality, diversity, high intellectual standard and wide impact of the field on which it reports. Demography presents the highest quality original research of scholars in a broad range of disciplines, including anthropology, biology, economics, geography, history, psychology, public health, sociology, and statistics. The journal encompasses a wide variety of methodological approaches to population research. Its geographic focus is global, with articles addressing demographic matters from around the planet. Its temporal scope is broad, as represented by research that explores demographic phenomena spanning the ages from the past to the present, and reaching toward the future. Authors whose work is published in Demography benefit from the wide audience of population scientists their research will reach. Also in 2011 Demography remains the most cited journal among population studies and demographic periodicals. Published bimonthly, Demography is the flagship journal of the Population Association of America, reaching the membership of one of the largest professional demographic associations in the world.
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