Sovereign Default Forecasting in the Era of the COVID-19 Crisis

Tamás Kristóf ()

JRFM, 2021, vol. 14, issue 10, 1-24

Abstract: The COVID-19 crisis has revealed the economic vulnerability of various countries and, thus, has instigated the systematic exploration and forecasting of sovereign default risks. Multivariate statistical and stochastic process-based sovereign default risk forecasting has a 50-year developmental history. This article describes a continuous, non-homogeneous Markov chain method as the basis for a COVID-19-related sovereign default risk forecast model. It demonstrates the estimation of sovereign probabilities of default (PDs) over a five-year horizon period with the developed model reflecting the impact of the COVID-19 crisis. The COVID-19-adopted Markov model estimates PDs for most countries, including those that are advanced with AAA and AA ratings, to suggest that no sovereign nation’s economy is secure from the financial impact of the COVID-19 pandemic. The dynamics of the estimated PDs are indicative of contemporary evidence as experienced in the recent financial crisis. The empirical results of this article have policy implications for foreign investors, sovereign lenders, export finance institutions, foreign trade experts, risk management professionals, and policymakers in the field of finance. The developed model can be used to timely recognize potential problems with sovereign entities in the current COVID-19 crisis and to take appropriate mitigating actions.

Keywords: credit risk; country risk; forecasting; Markov chain; probability of default (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
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