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Multiregional Population Forecasting: A Unifying Probabilistic Approach for Modelling the Components of Change.

Arkadiusz Wiśniowski1, James Raymer2

  • 1Social Statistics Department, University of Manchester, Oxford Rd, Manchester, M13 9PL, UK. a.wisniowski@manchester.ac.uk.

European Journal of Population = Revue Europeenne De Demographie
|April 10, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a probabilistic population projection model for subnational populations. The enhanced model forecasts demographic changes with uncertainty, improving accuracy for regional population planning.

Keywords:
AustraliaBayesian inferenceDemographic forecastingMultiregional demographyProjections

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Area of Science:

  • Demography
  • Population Studies
  • Statistical Modeling

Background:

  • The multiregional cohort-component model is a foundational tool for population projection.
  • Existing models often lack probabilistic forecasting and struggle with high dimensionality.
  • Accurate subnational population forecasts are crucial for policy and resource allocation.

Purpose of the Study:

  • To extend the Rogers multiregional cohort-component model into a fully probabilistic framework.
  • To develop a flexible statistical modeling approach for demographic components.
  • To provide robust population forecasts with measures of uncertainty for subnational regions.

Main Methods:

  • Forecasting age-, sex-, and region-specific fertility, mortality, and migration components.
  • Utilizing a combination of log-linear and bilinear models for demographic component forecasting.
  • Accounting for correlations across age, sex, regions, and time in the model.

Main Results:

  • A unified and flexible statistical modeling framework for population projection.
  • Incorporation of high dimensionality and interdependencies among demographic components.
  • Development of a robust platform for subnational population forecasting with uncertainty.

Conclusions:

  • The probabilistic extension provides a consistent and robust method for subnational population forecasting.
  • The model effectively handles the complexity of demographic components over time.
  • This approach offers valuable insights for policy-making and resource management in regions like Australia.