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While the relationship between volatility and risk is central to much of the financial literature it has not been incorporated systematically into assessment of sovereign debt sustainability. This paper attempts to fill this gap by studying how the probability distribution of sovereign debt to GDP ratios depends on the stochastic properties of underlying macroeconomic variables. Using right-hand tail of the distribution as a measure of the risk we are able to show how the volatility of the underlying variables as well as potential interactions between them influence country risk.

While the relationship between volatility and risk is central to much of the financial literature it has not been incorporated systematically into assessment of sovereign debt sustainability. This paper attempts to fill this gap by studying how the probability distribution of sovereign debt to GDP ratios depends on the stochastic properties of underlying variables such as the real interest rate, the real growth rate, and the primary budget deficit. Due to the highly non-linear relationship between these variables and the debt ratios, Monte-Carlo simulations have to be used to estimate the probability distribution at different horizons. Using the right-hand tail of the distribution as a measure of the risk, we are able to show how the volatility of the underlying variables as well as potential interactions between them influences country risk.Using estimates of volatility parameters of a sample of developed and emerging markets, we construct risk measures for each of them. We hypothesize that this risk measure should be positively correlated with the spread of sovereign bonds of the countries. Preliminary econometric tests suggest that this is indeed the case. Thus, while conventional analyses of the determinants of sovereign spreads have not focused on volatility dynamics, financial markets seem to have incorporated it in sovereign bond pricing.

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