{"title":"多区域人口预测:一种统一的概率方法来模拟变化的组成部分。","authors":"Arkadiusz Wiśniowski, James Raymer","doi":"10.1007/s10680-025-09729-7","DOIUrl":null,"url":null,"abstract":"<p><p>In this article, we extend the multiregional cohort-component population projection model developed by Andrei Rogers and colleagues in the 1960s and 1970s to be fully probabilistic. The projections are based on forecasts of age-, sex- and region-specific fertility, mortality, interregional migration, immigration and emigration. The approach is unified by forecasting each demographic component of change by using a combination of log-linear models with bilinear terms. This research contributes to the literature by providing a flexible statistical modelling framework capable of incorporating the high dimensionality of the demographic components over time. The models also account for correlations across age, sex, regions and time. The result is a consistent and robust modelling platform for forecasting subnational populations with measures of uncertainty. We apply the model to forecast population for eight states and territories in Australia.</p>","PeriodicalId":51496,"journal":{"name":"European Journal of Population-Revue Europeenne De Demographie","volume":"41 1","pages":"11"},"PeriodicalIF":1.9000,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985746/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multiregional Population Forecasting: A Unifying Probabilistic Approach for Modelling the Components of Change.\",\"authors\":\"Arkadiusz Wiśniowski, James Raymer\",\"doi\":\"10.1007/s10680-025-09729-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this article, we extend the multiregional cohort-component population projection model developed by Andrei Rogers and colleagues in the 1960s and 1970s to be fully probabilistic. The projections are based on forecasts of age-, sex- and region-specific fertility, mortality, interregional migration, immigration and emigration. The approach is unified by forecasting each demographic component of change by using a combination of log-linear models with bilinear terms. This research contributes to the literature by providing a flexible statistical modelling framework capable of incorporating the high dimensionality of the demographic components over time. The models also account for correlations across age, sex, regions and time. The result is a consistent and robust modelling platform for forecasting subnational populations with measures of uncertainty. We apply the model to forecast population for eight states and territories in Australia.</p>\",\"PeriodicalId\":51496,\"journal\":{\"name\":\"European Journal of Population-Revue Europeenne De Demographie\",\"volume\":\"41 1\",\"pages\":\"11\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985746/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Population-Revue Europeenne De Demographie\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1007/s10680-025-09729-7\",\"RegionNum\":2,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"DEMOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Population-Revue Europeenne De Demographie","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1007/s10680-025-09729-7","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
Multiregional Population Forecasting: A Unifying Probabilistic Approach for Modelling the Components of Change.
In this article, we extend the multiregional cohort-component population projection model developed by Andrei Rogers and colleagues in the 1960s and 1970s to be fully probabilistic. The projections are based on forecasts of age-, sex- and region-specific fertility, mortality, interregional migration, immigration and emigration. The approach is unified by forecasting each demographic component of change by using a combination of log-linear models with bilinear terms. This research contributes to the literature by providing a flexible statistical modelling framework capable of incorporating the high dimensionality of the demographic components over time. The models also account for correlations across age, sex, regions and time. The result is a consistent and robust modelling platform for forecasting subnational populations with measures of uncertainty. We apply the model to forecast population for eight states and territories in Australia.
期刊介绍:
European Journal of Population addresses a broad public of researchers, policy makers and others concerned with population processes and their consequences. Its aim is to improve understanding of population phenomena by giving priority to work that contributes to the development of theory and method, and that spans the boundaries between demography and such disciplines as sociology, anthropology, economics, geography, history, political science, epidemiology and other sciences contributing to public health. The Journal is open to authors from all over the world, and its articles cover European and non-European countries (specifically including developing countries) alike.