Predicting Sovereign Debt Crises /
We develop an early-warning model of sovereign debt crises. A country is defined to be in a debt crisis if it is classified as being in default by Standard and Poor's, or if it has access to nonconcessional IMF financing in excess of 100 percent of quota. By means of logit and binary recursive...
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| Andre forfattere: | , |
| Format: | Tidsskrift |
| Sprog: | English |
| Udgivet: |
Washington, D.C. :
International Monetary Fund,
2003.
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| Serier: | IMF Working Papers; Working Paper ;
No. 2003/221 |
| Online adgang: | Full text available on IMF |
| Summary: | We develop an early-warning model of sovereign debt crises. A country is defined to be in a debt crisis if it is classified as being in default by Standard and Poor's, or if it has access to nonconcessional IMF financing in excess of 100 percent of quota. By means of logit and binary recursive tree analysis, we identify macroeconomic variables reflecting solvency and liquidity factors that predict a debt-crisis episode one year in advance. The logit model predicts 74 percent of all crises entries while sending few false alarms, and the recursive tree 89 percent while sending more false alarms. |
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| Emne beskrivelse: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| Fysisk beskrivelse: | 1 online resource (41 pages) |
| Format: | Mode of access: Internet |
| ISSN: | 1018-5941 |
| Adgang: | Electronic access restricted to authorized BRAC University faculty, staff and students |