A Proposed Methodology for Modelling the Solvency of a National Pension Scheme

Abstract

The main aim of this study is to fit a model for predicting pension liability. The study proposed a stochastic population model to determine the status of a pension scheme. By categorizing the members of the Social Security and National Insurance Trust (SSNIT) pension scheme of Ghana into five groups, the birth and death process with emigration and the pure death process coupled with assumption of the Yule’s process, were combined to successfully formulate a model for forecasting the surplus of SSNIT to be used as a proxy for assessing the solvency status of the scheme. The reliability of the proposed model was corroborated by very high coverage probabilities of the estimates of expected surpluses produced.  The study demonstrated how easy it is to use the proposed model to carry out sensitivity analysis which allows the exploration of various scenarios leading to formulation and implementation of policies to enhance the solvency of the scheme. One major advantage of the proposed model is that, it uses more information (variables) compared to others proposed elsewhere for the same purpose. This contributes to the precision of estimates from the model. A key finding of the study is that SSNIT would have still been solvent had she increased pension by 50%.