The choice of sample size for mortality forecasting: a Bayesian learning approach

DOI10.1016/j.insmatheco.2015.03.024zbMath1348.91162OpenAlexW2065877807MaRDI QIDQ492650

Anja De Waegenaere, Bertrand Melenberg, Hong Li

Publication date: 20 August 2015

Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.insmatheco.2015.03.024

zbMATH Keywords

Gibbs samplingLee-Carter modelCairns-Blake-Dowd modellinear mortality modelsUS and Dutch data

Mathematics Subject Classification ID

Related Items (13)

Exchangeable mortality projection ⋮ THE LOCALLY LINEAR CAIRNS–BLAKE–DOWD MODEL: A NOTE ON DELTA–NUGA HEDGING OF LONGEVITY RISK ⋮ The impact of multiple structural changes on mortality predictions ⋮ Modelling mortality: A bayesian factor-augmented var (favar) approach ⋮ Longevity risk and capital markets: the 2015--16 update ⋮ Bayesian Poisson log-bilinear models for mortality projections with multiple populations ⋮ Incorporating structural changes in mortality improvements for mortality forecasting ⋮ Forecasting mortality with international linkages: a global vector-autoregression approach ⋮ Redistribution of longevity risk: the effect of heterogeneous mortality beliefs ⋮ Longevity risk and capital markets: the 2019--20 update ⋮ Longevity Risk and Capital Markets: The 2017–2018 Update ⋮ Age-coherent extensions of the Lee–Carter model ⋮ Hierarchical Bayesian modeling of multi-country mortality rates

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