{"title":"评估汉密尔顿-佩里模型在小区域人口预测中的替代实施:以澳大利亚为例","authors":"Tom Wilson, Irina Grossman","doi":"10.1007/s40980-021-00103-9","DOIUrl":null,"url":null,"abstract":"<p>Small area population forecasts are widely used across the public and private sectors, with many users requiring forecasts broken down by sex and age group. The preparation of small area age-sex population forecasts across a whole country or State with a multiregional cohort-component model is usually a time-consuming and expensive task. It involves the purchase of large datasets, considerable amounts of complex data preparation and assumption-setting, and substantial amounts of staff time. A quicker and lower-cost alternative is to use a reduced form cohort projection model, such as the Hamilton-Perry model. This paper presents an evaluation of various implementations of the Hamilton-Perry model, including an alternative version employing a combination of Cohort Change Ratios and Cohort Change Differences. It also evaluates the effects on forecast accuracy of smoothing the age profiles of Cohort Change Ratios and Differences, and constraining to independent population forecasts. Population ‘forecasts’ were created for small areas of Australia over the horizon 2006–16 and compared against population estimates. The most accurate implementation is found to be the Hamilton-Perry model using a combination of Cohort Change Ratios and Cohort Change Differences, smoothed age profiles, and with constraining to independent forecasts.</p>","PeriodicalId":43022,"journal":{"name":"Spatial Demography","volume":"21 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Evaluating Alternative Implementations of the Hamilton-Perry Model for Small Area Population Forecasts: the Case of Australia\",\"authors\":\"Tom Wilson, Irina Grossman\",\"doi\":\"10.1007/s40980-021-00103-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Small area population forecasts are widely used across the public and private sectors, with many users requiring forecasts broken down by sex and age group. The preparation of small area age-sex population forecasts across a whole country or State with a multiregional cohort-component model is usually a time-consuming and expensive task. It involves the purchase of large datasets, considerable amounts of complex data preparation and assumption-setting, and substantial amounts of staff time. A quicker and lower-cost alternative is to use a reduced form cohort projection model, such as the Hamilton-Perry model. This paper presents an evaluation of various implementations of the Hamilton-Perry model, including an alternative version employing a combination of Cohort Change Ratios and Cohort Change Differences. It also evaluates the effects on forecast accuracy of smoothing the age profiles of Cohort Change Ratios and Differences, and constraining to independent population forecasts. Population ‘forecasts’ were created for small areas of Australia over the horizon 2006–16 and compared against population estimates. The most accurate implementation is found to be the Hamilton-Perry model using a combination of Cohort Change Ratios and Cohort Change Differences, smoothed age profiles, and with constraining to independent forecasts.</p>\",\"PeriodicalId\":43022,\"journal\":{\"name\":\"Spatial Demography\",\"volume\":\"21 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2022-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spatial Demography\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40980-021-00103-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"DEMOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spatial Demography","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40980-021-00103-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
Evaluating Alternative Implementations of the Hamilton-Perry Model for Small Area Population Forecasts: the Case of Australia
Small area population forecasts are widely used across the public and private sectors, with many users requiring forecasts broken down by sex and age group. The preparation of small area age-sex population forecasts across a whole country or State with a multiregional cohort-component model is usually a time-consuming and expensive task. It involves the purchase of large datasets, considerable amounts of complex data preparation and assumption-setting, and substantial amounts of staff time. A quicker and lower-cost alternative is to use a reduced form cohort projection model, such as the Hamilton-Perry model. This paper presents an evaluation of various implementations of the Hamilton-Perry model, including an alternative version employing a combination of Cohort Change Ratios and Cohort Change Differences. It also evaluates the effects on forecast accuracy of smoothing the age profiles of Cohort Change Ratios and Differences, and constraining to independent population forecasts. Population ‘forecasts’ were created for small areas of Australia over the horizon 2006–16 and compared against population estimates. The most accurate implementation is found to be the Hamilton-Perry model using a combination of Cohort Change Ratios and Cohort Change Differences, smoothed age profiles, and with constraining to independent forecasts.
期刊介绍:
Spatial Demography focuses on understanding the spatial and spatiotemporal dimension of demographic processes. More specifically, the journal is interested in submissions that include the innovative use and adoption of spatial concepts, geospatial data, spatial technologies, and spatial analytic methods that further our understanding of demographic and policy-related related questions. The journal publishes both substantive and methodological papers from across the discipline of demography and its related fields (including economics, geography, sociology, anthropology, environmental science) and in applications ranging from local to global scale. In addition to research articles the journal will consider for publication review essays, book reviews, and reports/reviews on data, software, and instructional resources.