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Mortality and life expectancy forecast for (comparatively) high mortality countries.

Ahbab Mohammad Fazle Rabbi1, Stefano Mazzuco1

  • 1Department of Statistical Sciences, University of Padua, Via Cesare Battisti 241, Padua, 35121 Italy.

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Summary

Forecasting mortality in Central and Eastern European countries using standard models shows lower performance. New methods are needed for these high-mortality populations due to data limitations and diverging mortality trends.

Keywords:
Bayesian hierarchical modelCoherent forecastingLee–Carter methodMortality forecastMortality in Eastern Europe

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Area of Science:

  • Demography
  • Public Health
  • Statistical Modeling

Background:

  • The Lee-Carter method is a standard for mortality forecasting in countries with extensive, high-quality data.
  • However, its applicability is limited in regions with less data and higher mortality rates.

Purpose of the Study:

  • To compare various mortality forecasting models in Central and Eastern European (CEE) countries.
  • To address the challenges posed by higher mortality regimes and limited data quality in these regions.

Main Methods:

  • Utilized seven Lee-Carter variants and Bayesian Hierarchical Models for mortality forecasting.
  • Analyzed data from nine CEE countries with comparatively higher mortality rates.

Main Results:

  • Forecasting model performance was lower in CEE countries compared to low-mortality nations.
  • No single model outperformed others across all nine CEE countries.
  • Probabilistic forecasting offered improvements but wider prediction intervals; mortality divergence posed challenges.

Conclusions:

  • Existing mortality forecasting models, including Lee-Carter variants, are inadequate for high-mortality CEE countries.
  • There is a critical need to develop novel forecasting techniques tailored to the specific conditions of these countries.