Bayesian multiregional population forecasting: England

Arkadiusz Wisniowski, University of Manchester
James Raymer, Australian National University

In this paper, we extend the well-known multiregional population projection model developed by Andrei Rogers and colleagues to be fully probabilistic. Multiregional models provide a general and flexible platform for modelling and analysing population change over time. They allow the combination of all the main components of population change by age with various transitions that population groups may experience throughout their life course. What distinguishes these models from ordinary projections is that they include transition matrices of interregional migration by age. This information is an important component of subnational population change yet models for forecasting the patterns for use in population projections are largely non-existent. National statistical offices tend to rely on simple deterministic assumptions regarding net migration or gross flows of in-migration and out-migration. These models do not take into account the linkages between origins and destinations and often have to be adjusted to ensure zero net migration and the same totals for in-migration and out-migration. In this paper, we focus on the full matrix of flows to avoid this problem. To deal with the large number of possible flows, we develop a Bayesian hierarchical model to forecast age-specific interregional migration in England, and then include this information with probabilistic forecasts of regional births, deaths, immigration and emigration. The results demonstrate the differences that arise from different models specifications and the promise of the general approach.