Journal Article

Probabilistic population forecasts for small regions

Engelhardt, Henriette, Goes, Julius

2026

Overview

Age-specific population forecasts for small areas or subnational regions are a valuable tool for local governments. However, typical population projection methods based on the cohort-component approach are difficult to apply on a smaller subnational scale. We introduce Bayesian methods suitable for obtaining reliable age-specific population forecasts for small regions using the cohort-component method. Our approach improves fertility forecasting by extending the Lee--Carter model with an age-region interaction term. We propose to forecast net-migration counts using skewed error terms, and introduce a Dirichlet regression to model migration age patterns as well as age proportions of fertility. We run our model to produce age-specific population forecasts for a set of 13 heterogeneous regions in Bavaria, Germany. We compare our method with other standard approaches and find that it produces superior out-of-sample forecasts according to both point measures and scoring rules. The findings suggest that the proposed Bayesian methods offer good predictive accuracy and are suitable in obtaining precise forecasts of age-specific population for smaller geographical regions.

• Publisher: Max Planck Institute for Demographic Research
• Subject: Analysis / Bayesian modelling / Bayesian statistical decision theory / cohort-component method / Forecasts and trends / Methods / Population forecasting / Rural population / Statistics