The role of climate risk in shaping longevity dynamics: Extending stochastic mortality models

This paper investigates the impact of climate risk on mortality dynamics across different populations. We introduce extensions of the Lee–Carter model that integrate climate risk data, specifically Annual Temperature Anomalies levels, to improve mortality projections. A three-stage calibration strategy, based on the Ordinary Least Squares estimator, is proposed to estimate the model parameters. Numerical experiments, conducted on a sample of 42 populations, demonstrate that incorporating climate risk information enhances forecasting accuracy. Additionally, further improvements in forecasting performance are observed when climate data is combined with economic indicators such as GDP. • An extended Lee–Carter model integrates climate and economic indicators for mortality forecasting. • A three-stage OLS calibration strategy is introduced for parameter estimation. • Evidence on 42 populations shows temperature anomalies improve accuracy in forecasting mortality rates. • Combining climate risk with GDP achieves the best predictive performance.