Flexible Bayesian modelling of age-specific counts in many demographic subpopulations
提出一个贝叶斯模型，用于联合分析多个（可能很小的）人口子群体的年龄别死亡率、生育率和迁移模式，通过平滑潜在因子捕捉共同模式，并利用分层先验共享信息，适用于小样本和异质性群体。
Abstract Analysing age-specific mortality, fertility, and migration patterns is a crucial task in demography with significant policy relevance. In practice, such analysis is challenging when studying a large number of subpopulations, due to small observation counts within groups and increasing demographic heterogeneity between groups. This article proposes a Bayesian model for the joint analysis of age-specific counts in many, potentially small, demographic subpopulations. The model utilizes smooth latent factors to capture common age-specific patterns across subpopulations and facilitates additional information sharing through a hierarchical prior. It provides smoothed estimates of the latent age pattern in each subpopulation, allows testing for heterogeneity, and can be used to assess the impact of covariates on the demographic process. An in-depth case study of age-specific immigration flows to Austria, disaggregated by sex and 155 countries of origin, is discussed. Comparative analysis demonstrates that the model outperforms commonly used benchmark frameworks in both in-sample imputation and out-of-sample predictive exercises.