Dynamic Optimisation of Public Pension Systems

Abstract This paper presents a dynamic optimisation algorithm for public pension systems, developed by using Bellman’s principle of optimality. The algorithm minimises a weighted objective function over a limited time frame (2024–2036), where decisions are optimised annually for seven variables: retirement age (men and women), contribution rate, national average wage, early retirement rate, active pensioner share, and employment rate. The system is controlled by deterministic demographic forecasts and policy-dependent limitations. The paper presents the algorithm underlying the model, which produces an ideal decision path that minimises deviations from a policy baseline for 2024. The structure of the model can be adapted to pay-as-you-go pension systems under demographic pressure in other countries.