Serial Sovereign Defaults and Debt Restructurings
Tamon Asonuma ()
No 2016/066, IMF Working Papers from International Monetary Fund
Emerging countries that have defaulted on their debt repayment obligations in the past are more likely to default again in the future than are non-defaulters even with the same external debt-to-GDP ratio. These countries actually have repeated defaults or restructurings in short periods. This paper explains these stylized facts within a dynamic stochastic general equilibrium framework by explicitly modeling renegotiations between a defaulting country and its creditors. The quantitative analysis of the model reveals that the equilibrium probability of default for a given debt-to-GDP level is weakly increasing with the number of past defaults. The model also accords with an additional fact: lower recovery rates (high NPV haircuts) are associated with increases in spreads at renegotiation.
Keywords: WP; credit history; rate of return; utility function; Serial Default; Sovereign Default; Debt Restructuring; Past Credit History; Haircuts; Recovery rates; Risk Premia; recovery rate; default probability; defaulted debt; GDP ratio; credit history ht; Debt renegotiation; Credit; Asset prices; Sovereign debt restructuring; Global (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10) Track citations by RSS feed
Downloads: (external link)
Our link check indicates that this URL is bad, the error code is: 403 Forbidden
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:imf:imfwpa:2016/066
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in IMF Working Papers from International Monetary Fund International Monetary Fund, Washington, DC USA. Contact information at EDIRC.
Bibliographic data for series maintained by Akshay Modi ().