This paper extends the probabilistic debt sustainability analysis (DSA) developed by Celasun, Debrun, and Ostry (2006) to account explicitly for parameter estimation errors in the debt projection algorithm. This extension highlights public debt projection uncertainty resulting from both the intrinsic volatility of debt determinants and the inaccuracy of the parameter estimates of econometric models employed in the projections. The revised algorithm is applied to conduct a debt sustainability analysis of Uruguay. As part of this exercise, a restricted vector autoregression and a country-specific fiscal reaction function are employed. The resulting increase in the variance of the debt projections that account for the uncertainty of parameter estimates in the forecast is smaller than may have been anticipated, as the improved specification of the underlying econometric model reduces the variance of debt projections. Hence, more precise estimates of economic fundamentals and fiscal policy reaction allow for a feasible debt forecast with a more accurate depiction of its inherent forecast uncertainty.
This paper modifies several assumptions in the probabilistic approach to fiscal sustainability proposed by Celasun, Debrun, and Ostry (2007). First, we allow for structural breaks in the vector autoregression model for the macroeconomic variables. Second, in the Monte-Carlo simulations, we draw directly from the empirical distribution of the shocks instead of drawing from a normal distribution, thus allowing for asymmetries and thick tails. Third, we circumvent the use of a fiscal reaction function by focusing attention instead on debt-stabilizing balances, to produce more “agnostic” debt projections. The paper illustrates how these methodological modifications have significant impacts on the results for specific country cases.