Predictive Modeling of Ghana’s Private Sector Pensions Asset under Management Contribution Using ARIMA Model

This study applies an ARIMA (1,1,0) model to analyze the Private Sector Pension Assets Under Management (AUM) in Ghana. The model’s parameters and performance metrics were evaluated using SARIMAX results and the Dickey-Fuller Test for stationarity. The SARIMAX model demonstrated a significant autoregressive term (ar. L1 = 0.9693) and acceptable performance metrics (MAE = 5.99, RMSE = 13.89, MAPE = 23.97%), indicating a strong influence of past values on current AUM. The diagnostic tests suggested that residuals were not autocorrelated and approximately normally distributed. The Dickey-Fuller Test further confirmed the stationarity of the time series, with a test statistic of -5.3314 and a p-value of 4.7116e-06, allowing us to reject the null hypothesis of a unit root. Overall, the ARIMA (1,1,0) model provides a reliable framework for forecasting and analyzing the Private Sector Pension AUM in Ghana, supported by robust statistical validation.