使用贝叶斯模型预测新西兰按年龄、性别和地区的国际入境和出境人数

John R. Bryant, Kirsten Nissen
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引用次数: 0

摘要

新西兰统计局在国家以下一级编制定期人口预测。与其他统计机构一样,新西兰统计局目前使用确定性方法进行次国家预测。然而,我们目前正在开发另一种更具统计学意义的方法。在本文中,我们描述了两个贝叶斯层次模型,用于估计和预测国际移民迁入和迁出率,按年龄、性别和领土当局分类。该模型使用1991-2013年的国际入境和出境数据,并对2014-2039年进行预测。特别注意的是,该模型的能力,以估计迁移率的小人口域。建模方法在详细的人口统计水平上提供了连贯和综合的不确定性度量。给出了估算和预测迁移率的例子。最后,我们讨论了数据和模型的挑战和局限性,以及未来发展的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Bayesian Models To Forecast International Arrivals And Departures By Age, Sex, And Region In New Zealand
Statistics New Zealand prepares regular population projections at the subnational level. Like other statistical agencies, Statistics NZ currently uses a deterministic approach to subnational projections. However, we are currently developing an alternative, more statistical, approach. In this paper, we describe two Bayesian hierarchical models for estimating and forecasting international in-migration and out-migration rates, disaggregated by age, sex, and territorial authority. The model uses international arrivals and departures data for 1991-2013, and produces forecasts for 2014-2039. Special attention is given to the ability of the model to estimate migration rates for small population domains. The modelled approach provides a coherent and integrated measure of uncertainty at the detailed demographic level. Examples of estimated and forecasted migration rates are presented. We conclude with a discussion of the challenges and limitations of the data and model, and directions for future developments.
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