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Meeting-ID: 280 519 2121
Passwort: 584190

Abstract:

Analyzing age-specific mortality, fertility, and migration patterns is a crucial task in statistical 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 heterogeneity between groups. To address these challenges, we develop a Bayesian factor model for the joint analysis of age-specific counts in many, potentially small, subpopulations. The proposed model uses smooth latent components to capture common age-specific patterns across subpopulations and encourages additional information sharing through a hierarchical prior. The model provides smoothed estimates of the latent demographic pattern in each subpopulation, allows testing for heterogeneity, and can be used to assess the impact of observed 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 shows that the model outperforms commonly used benchmark frameworks in both in-sample imputation and out-of-sample predictive exercises. Extensions to dynamic settings are discussed as well.