Debt Sustainability Assessments: The state of the art

15-11-2018

The approach to Debt Sustainability Assessments (DSAs) has substantially evolved after the global crisis, consistent with the goal of improving detection of high and low frequency risks. DSAs cover an increasing number of indicators, systematically look into implicit and contingent liabilities, and use statistical methods to quantify “tail events”. They also operationalize debt limits, by adopting thresholds for debt and payment flows to single out enhanced vulnerability. While these developments mark true progress, this paper focuses on liquidity risk, contagion risk and the identification of debt limits as critical areas limiting DSA effectiveness, explains why DSA should embed potentially available official support and how an incomplete lending architecture is a hurdle for DSA. The paper concludes with a comparative assessment of current standard DSAs, suggests directions for further improvement and discusses the correct use of DSAs in light of the strengths and weaknesses inherent in the underlying methodologies..

The approach to Debt Sustainability Assessments (DSAs) has substantially evolved after the global crisis, consistent with the goal of improving detection of high and low frequency risks. DSAs cover an increasing number of indicators, systematically look into implicit and contingent liabilities, and use statistical methods to quantify “tail events”. They also operationalize debt limits, by adopting thresholds for debt and payment flows to single out enhanced vulnerability. While these developments mark true progress, this paper focuses on liquidity risk, contagion risk and the identification of debt limits as critical areas limiting DSA effectiveness, explains why DSA should embed potentially available official support and how an incomplete lending architecture is a hurdle for DSA. The paper concludes with a comparative assessment of current standard DSAs, suggests directions for further improvement and discusses the correct use of DSAs in light of the strengths and weaknesses inherent in the underlying methodologies..