Determinants of sovereign defaults

Abstract

Highlights Political uncertainty/worsening international monetary conditions promote default  Export (import) growth reduces (increases) the probability of default  Higher debt/GDP ratio, and inflation is linked to higher probability of default  A previous banking crisis is related to higher chances of sovereign defaults  Higher US treasury rates would initiate sovereign defaults and hinders to come out AbstractWe study major sovereign defaults from 1970 to 2010 using an advanced duration analysis method. Descriptive analysis of the data indicates a cyclical nature of these defaults over a longer period. Regression results highlight the importance of the international monetary conditions as the volatilities of US treasury bills rates and USDdenominated LIBOR exert significant impacts on defaults. Political uncertainty increases the probability of default. Export (import) growth reduces (increases) the probability of default. Similarly, a 1% increase in inflation would increase the probability of defaults by 7%. Higher debt/GDP ratio is also linked to higher probability of default. A 1% increase in external debt would lead to a five to 7% increase in the probability of default. Higher GDP per capita reduces the probability of default. A previous banking crisis is linked to higher chances of sovereign defaults. Further analysis of entry into (out of) sovereign defaults indicates that higher US treasury rates would initiate sovereign defaults and would make it difficult for countries to come out of default.The same is true for central government debt/GDP, higher current account deficit and exchange rate volatility. JEL classificationF34, F37, F38, F44, F62

Impact of Covid-19 on corporate solvency and possible policy responses in the EU

“…The relation between long term solvency and revenues is long-established and recent studies like ( Cui & Kaas, 2020 ; Duan, Kim, Kim, & Shin, 2018 ; Ghulam & Derber, 2018 ) have validated this link. To stress-test the solvency vis-à-vis a drop in sales, we follow De Vito & Gómez (2020) to devise the sensitivities.…”

Elements of Sovereign-Debt Default in the MENA Region

“…Inflation and interest rate are surely determinants of sovereign debt. According to Ghulam and Derber (2018), a high inflation rate entails high-interest rate or vice versa. High inflation will devaluate the local currency.…”

“…Furthermore, a negative relationship with the real GDP growth, and foreign exchange reserve to debt ratio. Ghulam and Derber (2018) used panel data over 70 countries to study major sovereign defaults over the period 1970-2010. Their key findings were; Political instability, rise in inflation, interest rates, current account deficit, and increase in debt/GDP ratio increase the probability of default.…”

Penalized maximum likelihood estimation of logit-based early warning systems

“…These definitions are borrowed from the empirical literature on poverty traps, where poverty dynamics are modeled as a Markov process Jenkins, 2002, 2004) and have the same rationale of the approach adopted by Ghulam and Derber (2018) in the context of duration models for sovereign defaults.…”

“…I also consider a dynamic formulation of EWS by including the lagged dependent variable among the set of covariates, which has been shown to substantially enhance the model predictive performance (Antunes et al, 2018). Adding to this framework and similarly to Ghulam and Derber (2018), I show that a dynamic binary choice model in this context allows for the prediction of two separate probabilities which can be of interest to policymakers: the crisis entry rate, that is the probability of a crisis a time t given that the country was not in a crisis state at time t − 1, and the crisis persistence rate, which is the probability of that a country faces a prolonged state of financial distress at time t conditional on that country already having faced a crisis at time t − 1 I compare both in and out of sample forecasts for EWS estimated by different methods and evaluate their performance in classifying crisis events by plotting Receiver Operating Characteristics (ROC) curves and comparing the related Areas Under ROC (AUROC), as customary in this literature. I also consider predictions based on the F-score, which it is argued to be more suitable for the forecasting of rare events (Davis and Goadrich, 2006).…”