By Michael Kamanyire Tukacungurwa
2015

This paper proposes a new framework of Debt Sustainability Analysis for Uganda using stochastic methods. The methodologies involve using a probabilistic approach of assessing Uganda’s public debt sustainability and how it fits into the public debt strategy framework. This approach carries a bigger advantage over the traditional DSAs since it enables us examine the probability that, given a stress scenario vis-à-vis different debt strategies, debt thresholds may be violated at some point during the projection period. The traditional DSA framework uses stress scenarios that are arbitrary and usually extreme, with small probability of occurrence. Therefore, this model tries to eliminate the arbitrariness of such scenarios by assessing their their probability of occurrence and likely impact of the debt. The methodology is divided into three stages: (i) a Debt issuance engine, (ii) a macroeconomic model, and (iii) a Monte Carlo Simulation tool. An enhanced version of the joint IMF/WB MTDS Analytical Tool is used to run stochastic simulations (Monte Carlo Simulations). The methodology is applied to assess the four debt strategies presented in the Uganda 2013 MTDS. The results show that Uganda’s debt remains sustainable even in the event of adverse macroeconomic conditions. The debt-to-GDP ratio trends well below the policy-dependent thresholds across all strategies while the Cost-at-Risk (CaR) and Cash flow-at-Risk (CfaR) showed volatility in strategies of domestic and commercial debt. The results also show that under all strategies, the expected nominal deficit-to-GDP is likely to rise sharply over and above the dispersion of possible outcomes in the short term before declining in the medium to long-term i.e. a high probability that the budget deficit will rise sharply but trending well below the mean in the short-term. The results further show that there is a higher risk of the gross financing need increasing the most under the strategy which is predominantly of commercial financing.

Keywords: Debt Sustainability Analysis, Public Debt Management, Stochastic Simulation
Models, Gross Financing Need