Learning individual reproductive behaviour from aggregate fertility rates via neural posterior estimation
Permanyer, Iñaki (Centre d'Estudis Demogràfics)
Ciganda, Daniel (Max Planck Institute for Demographic Research (Alemanya))
Macke, Jakob H. (University of Tübingen)
Campón, Ignacio (Max Planck Institute for Demographic Research (Alemanya))
Centre d'Estudis Demogràfics

Date:	2026
Description:	20 pàg.
Abstract:	Age-specific fertility rates (ASFRs) provide the most extensive record of reproductive change, but their aggregate nature obscures the individual-level behavioural mechanisms that drive fertility trends. To bridge this micro-macro divide, we introduce a simulation-based Bayesian framework that couples a demographically interpretable, individual-level simulation model of the reproductive process with sequential neural posterior estimation (SNPE). We show that this framework successfully recovers core behavioural parameters governing contemporary fertility, including preferences for family size, reproductive timing, and contraceptive failure, using only ASFRs. The framework's effectiveness is validated on cohorts from four countries with diverse fertility regimes. Most compellingly, the model, estimated solely on aggregate data, successfully predicts out-of-sample distributions of individual-level outcomes, including age at first sex, desired family size, and birth intervals. Because our framework yields complete synthetic life histories, it significantly reduces the data requirements for building microsimulation models and enables behaviourally explicit demographic forecasts.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Age-specific fertility rates ; Individual-level modelling ; Microsimulation ; Reproductive behaviour ; Simulation-based inference
Published in:	Journal of the Royal Statistical Society Series A: Statistics in Society, 20 March 2026, ISSN 1467-985X

DOI: 10.1093/jrsssa/qnag045

20 p, 7.0 MB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Social and Legal Sciences > Centre for Demographic Studies (CED-CERCA)
Articles > Research articles
Articles > Published articles