Optimal Pension Funding Through Dynamic Simulations: the Case of Taiwan Public Employees Retirement System

Abstract

An approach combining stochastic simulations and dynamic optimization is constructed to decide the optimal funding policy of the defined benefit pension scheme. The results show a significant advantage and flexibility of this approach in projecting the optimal financial status over the traditional deterministic pension valuation. In this study, the optimal contributions are estimated through dynamic programming under the projected workforce and specified constraints. Taiwan public employees retirement system (Tai-PERS) is studied for illustration. This article outlines the procedure of building the proposed dynamic procedure and presents the empirical findings from this study.