Forecasting Pension Fund Liabilities Using Economic and Demographic Factors in Zambia

Abstract

Purpose: The aim of the study was to analyze the forecasting pension fund liabilities using economic and demographic factors in Zambia.

Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.

Findings: Forecasting pension fund liabilities in Zambia highlight the critical influence of economic and demographic factors. Key indicators such as GDP growth, inflation, interest rates, population aging, and life expectancy significantly impact projections of future pension obligations. Accurate modeling integrating these variables is essential for informed decision-making by administrators and policymakers to ensure financial sustainability for retirees in Zambia.

Unique Contribution to Theory, Practice and Policy: Life cycle hypothesis (LCH), dependency ratio theory & asset liability management (ALM) may be used to anchor future studies on analyze the effect of organizational culture on knowledge sharing and retention among public sector employees in South Africa. Pension funds should adopt advanced asset liability management (ALM) strategies that align investment portfolios with long-term liabilities. Policymakers should establish regulatory frameworks that allow for flexibility in pension fund management, particularly in response to economic crises and demographic changes.