Asset Liability Management for Tanzania Pension Funds

Abstract

This thesis presents a long-term asset liability management for Tanzania pension funds. As an application, the largest pension fund in Tanzania is considered. This is a pay-as-you-go pension fund where the contributions are used to pay current benefits. The Pension plan analyzed is a final salary defined benefit. Two kinds of pension benefit are considered, a commuted (at retirement) and a monthly (old age) pension. A decision factor in the analysis is the increased life expectancy of the members of the pension fund. The presentation is divided into two parts. First is a long-term projection of the fund using a fixed and relatively low return on asset value. Basing on the number of members in 2015, a 50 years projection of members and retirees is done. The corresponding amount of contributions, asset values, benefit payouts, and liabilities are also projected. The evaluation of some possible reforms of the fund is done. Then, the growth of asset values using different asset returns is studied. The projection shows that the fund will not be fully sustainable in a long future due to the increase in life expectancy of its members. The contributions will not cover the benefit payouts and the asset value will not fully cover liabilities. Evaluation of some reforms of the fund shows that they cannot guarantee a long-term sustainability. Higher returns on asset value will improve the asset to liability ratio, but contributions are still insufficient to cover benefit payouts. Second is a management based on stochastic programming. This approach allocates investment in 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 includes some features from Tanzania pension system. In contrast with most asset liability management models for pension funds by stochastic programming, liabilities are modeled by number of years of life expectancy. Scenario trees are generated by using Monte Carlo simulation. Two models according to different investment guidelines are built. First is using the existing investment guidelines and First, I would like to express my deepest gratitude to my supervisors Prof. Torbjörn Larsson and Ass. Prof. Martin Singull for their valuable guidance, encouragement and insightful ideas. Thank you Torbjörn, thank you Martin. I have learned a lot from you, You have not only benefited me but my country. I would like to express my appreciation to my home supervisor Prof. Allen Mushi for his encouragement and advice during my studies. I would like to thank ISP through EUMP for giving me this opportunity to attend studies here at Linköping University. Your generous and kind to support Africa especially Tanzania is appreciated. My deep gratitude goes to all members of the department of Mathematics at Linköping University, for their constant help. I thank my fellow PhD students at the department of mathematics for making life easier during my studies. Also to all members of optimization group. You have contributed a lot in my studies. ...