Debt-to-pay-debt syndrome in Uganda

This study investigates debt-to-pay-debt syndrome in Uganda from 1980 to 2022 using a quantitative approach with ARIMA modelling to evaluate public debt sustainability. Balanced time series data from the World Bank is analysed with public debt (% of GDP) as the dependent variable, incorporating autoregressive (AR) and moving average (MA) components as independent variables. Parameter estimation is conducted using Maximum Likelihood Estimation (MLE), with diagnostic tests ensuring model robustness. Results show that the AR(1) coefficient (0.350489), is positive and statistically significant, meaning that 35% of the current year’s debt is used to service the previous year’s debt. This finding confirms the persistence of the debt-to-pay-debt cycle in Uganda. The estimated ARIMA (1, 1, 11) model is both covariance stationary and invertible, making it reliable for forecasting public debt trends over the next decade. Forecasts suggest that the debt-to-pay-debt pattern will continue unless corrective measures are taken. The study recommends implementing comprehensive debt management policies to reduce reliance on new borrowing. This includes enforcing stricter fiscal rules and promoting revenue diversification through emerging sectors such as digital economies, agricultural value addition, mineral resources, and oil and gas.