Forecasting German mortality using panel data procedures

Reliable forecasts of life expectancies are of importance for the financial stability of social security systems and the life insurance industry. A discrete-time stochastic process and a continuous-time stochastic process are proposed to model the dynamics of German mortality rates from which life expectancies are calculated. More precisely, a panel data model is utilized, which distinguishes between a common time effect and a common age effect. The model is easy to fit, yields interpretable parameters, and allows for a simple analysis of the forecast error. The main applications of the model are the forecast of mortality rates—and the resulting life expectancies—and the pricing of mortality derivatives.

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