Abstract

Many mortality forecasting approaches extrapolate past trends. Their predictions of the future development can be quite precise as long as turning points and/or age-shifts of mortality decline are not present. To account even for such mortality dynamics, we propose a model that combines recently developed ideas in a single framework. It (1) uses rates of mortality improvement to model the aging of mortality decline, and it (2) optionally combines the mortality trends of multiple countries to catch anticipated turning points. We use simulation-based Bayesian inference to estimate and run this model that also provides prediction intervals to quantify forecast uncertainty. Validating mortality forecasts for British and Danish women from 1991 to 2011 suggest that our model can forecast regular and irregular mortality developments and that it can perform at least as well as other widely accepted approaches like, for instance, the Lee-Carter model or the UN Bayesian approach. Moreover, prospective mortality forecasts from 2012 to 2050 suggest gradual increases for British and Danish life expectancy at birth.

Highlights

  • Few activities of demographers receive as much attention from society as population forecasts

  • Many mortality forecasting approaches extrapolate past trends

  • The model should be adjustable to different forecast conditions such as a rapid or slow convergence of mortality between a country of interest (COI) and Reference country (RC)

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Summary

Introduction

Few activities of demographers receive as much attention from society as population forecasts. Many areas of public policy are affected by the increasing number of the elderly in a population as a result of improved chances of survival (Preston and Stokes 2012). Financing old-age pensions and health care and the provision of long-term care are only the tip of the iceberg. Private companies require reliable estimates for future mortality. Pension funds represent the most obvious example (OECD 2011; Soneji and King 2012)

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