Bayesian Forecasting of Mortality Rates by Using Latent Gaussian Models

Abstract

We provide forecasts for mortality rates by using two different approaches. First we employ dynamic non‐linear logistic models based on the Heligman–Pollard formula. Second, we assume that the dynamics of the mortality rates can be modelled through a Gaussian Markov random field. We use efficient Bayesian methods to estimate the parameters and the latent states of the models proposed. Both methodologies are tested with past data and are used to forecast mortality rates both for large (UK and Wales) and small (New Zealand) populations up to 21 years ahead. We demonstrate that predictions for individual survivor functions and other posterior summaries of demographic and actuarial interest are readily obtained. Our results are compared with other competing forecasting methods.

Bayesian Prediction of Jumps in Large Panels of Time Series Data

“…In the supplementary material we present results from simulation studies used to test our methodology. Further specifics of the data analysis, such as parameter estimates for the log-volatility processes, can be also found in the supplementary material as well as in Alexopoulos (2017).…”

Introduction

“…Shang (2015) and Shang and Hyndman (2017) evaluate interval forecasts for age-specific mortality rates in various countries, and use interval scores to select the best among several methods of forecasting mortality. Alexopoulos et al (2018) employ interval scores to prediction intervals of age-specific mortality of England & Wales and New Zealand, and evaluate the predictive performance of five different mortality prediction models. All four papers use holdout samples to evaluate the probabilistic demographic forecasts.…”

Bayesian Probabilistic Population Projections for France

“…Shang (2015) and Shang & Hyndman (2017) evaluated interval forecasts for age-specific mortality rates of various countries, and used interval scores to select the best among several methods of mortality forecasting. Alexopoulos et al (2018) employed interval scores to prediction intervals of age-specific mortality of England and Wales and New Zealand, and evaluated the predictive performance of five different mortality prediction models. All four papers use holdout samples to evaluate the probabilistic demographic forecasts.…”