Model selection and forecasting in stress tests can be facilitated using machine learning techniques. These techniques have proved robust in other fields for dealing with the curse of dimensionality, a situation often encountered in applied stress testing. Lasso regressions, in particular, are...

This paper introduces the quantile regression- based Distance-to-Default to Probability of Default (DD-PD) mapping, which links individual firms' DD to their real world PD. Since changes in the DD depend on a handful of parameters, the mapping easily accommodates shocks arising from quantitative...

We study the impact of the COVID-19 recession on capital structure of publicly listed U.S. firms. Our estimates suggest leverage (Net Debt/Asset) decreased by 5.3 percentage points from the pre-shock mean of 19.6 percent, while debt maturity increased moderately. This de-leveraging effect is...

In an environment characterized by weak contractual enforcement, sovereign lenders can enhance the likelihood of repayment by making their claims more difficult to restructure ex post. We show however, that competition for repayment among lenders may result in a sovereign debt that is...

This paper presents a general equilibrium model of interenterprise arrears, characterized by n-stage production technology with random productivity shocks. The model shows that large interenterprise arrears in transition economies may reflect substantial business risks in those countries and...

This paper outlines a procedure for calculating the cash value of “menu items” in debt restructuring proposals, including par and non-par exchanges, with enhancements consisting of either interest or principal guarantees. It is argued that under certain plausible assumptions interest and...

We produce a social unrest risk index for 125 countries covering a period of 1996 to 2020. The risk of social unrest is based on the probability of unrest in the following year derived from a machine learning model drawing on over 340 indicators covering a wide range of macro-financial,...

We analyze the causes of the apparent bias towards optimism in growth forecasts underpinning the design of IMF-supported programs, which has been documented in the literature. We find that financial variables observable to forecasters are strong predictors of growth forecast errors. The greater...