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European Jornal of Population

You can read the paper, 鈥淢ultiregional Population Forecasting: A Unifying Probabilistic Approach for Modelling the Components of Change鈥�, on.

Regional population forecasts are important for planning and understanding how populations are changing and redistributing. To forecast regional population changes, one must have a mechanism to capture different sources of population growth. In low fertility and developed societies, the main factors driving population redistribution are internal migration and immigration, for which both tend to concentrate people towards large metropolitan areas. 

In this article, we extend the multiregional cohort-component population projection model developed by Andrei Rogers and colleagues in the 1960s and 1970s to be fully probabilistic, by using Bayesian inference. We apply the model to forecast population for eight states and territories in Australia. 

The projections are based on forecasts of age-, sex- and region-specific fertility, mortality, interregional migration, immigration and emigration. The approach is unified by forecasting each demographic component of change by using a combination of log-linear models with bilinear terms. 

This research contributes to the literature by providing a flexible statistical modelling framework capable of incorporating the high dimensionality of the demographic components over time.