Asset liability management for Tanzania pension funds by stochastic programming

Abstract

We present a long-term model of asset liability management for Tanzania pension funds. The pension system is pay-as-you-go where contributions are used to pay current benefits. The pension plan is a final salary defined benefit. Two kinds of pension benefits, a commuted (at retirement) and a monthly (old age) pension are considered. A decisive factor for a long-term asset liability management is that, Tanzania pension funds face an increase of their members' life expectancy, which will cause the retirees to contributors dependence ratio to increase. We present a stochastic programming approach which allocates assets with the best return to raise the asset value closer to the level of liabilities. The model is based on work by Kouwenberg in 2001, with features from Tanzania pension system. In contrast to most asset liability management models for pension funds by stochastic programming, liabilities are modeled by using number of years of life expectancy for monthly benefit. Scenario trees are generated by using Monte Carlo simulation. Numerical results suggest that, in order to improve the long-term sustainability of the Tanzania pension fund system, it is necessary to make reforms concerning the contribution rate, investment guidelines and formulate target funding ratios to characterize the pension funds' solvency situation.

Assessment of the new investment limits for assets of Social Security Regimes for Public Servants established by Resolution CMN 3,922/2010

“…The latest-generation models have started to use techniques such as the decision support system (DSS) in conjunction with SLP, to deal with large numbers of variables, restrictions, and scenarios (Dutta et al, 2019;Rao et al, 2018). An interesting application of ALM models using SLP was developed by Andongwisye et al (2018), in which a pay-as-you-go social security system was assessed for its long-term equilibrium.…”