Articlehybrid2015

Bayesian Population Forecasting: Extending the Lee-Carter Method

Arkadiusz Wiśniowski · Peter W. F. Smith · Jakub Bijak · James Raymer · Jonathan J. Forster

102 citations0/0 files storedDemography

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Insurance, Mortality, Demography, Risk Management Census and Population Estimation demographic modeling and climate adaptation

Abstract

In this article, we develop a fully integrated and dynamic Bayesian approach to forecast populations by age and sex. The approach embeds the Lee-Carter type models for forecasting the age patterns, with associated measures of uncertainty, of fertility, mortality, immigration, and emigration within a cohort projection model. The methodology may be adapted to handle different data types and sources of information. To illustrate, we analyze time series data for the United Kingdom and forecast the components of population change to the year 2024. We also compare the results obtained from different forecast models for age-specific fertility, mortality, and migration. In doing so, we demonstrate the flexibility and advantages of adopting the Bayesian approach for population forecasting and highlight areas where this work could be extended.

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References

1992Modeling and Forecasting U. S. Mortality 2002Demography, Measuring and Modeling Population Processes 1983Regional Model Life Tables and Stable Populations 2006A cohort-based extension to the Lee–Carter model for mortality reduction factors 2006Robust forecasting of mortality and fertility rates: A functional data approach 1967Regional Model Life Tables and Stable Populations.2005Coherent mortality forecasts for a group of populations: An extension of the lee-carter method 1980The age pattern of mortality

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