Verfügbarkeit: Predicting Sovereign Debt Crises

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 & Poor''s, or if it has access to nonconcessional IMF financing in excess of 100 percent of quota. By means of logit and binary re...

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1. Verfasser:	Schimmelpfennig, Axel (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Washington, D.C International Monetary Fund 2003
Schriftenreihe:	IMF Working Papers Working Paper No. 03/221
Online-Zugang:	UBW01 UEI01 LCO01 SBR01 UER01 SBG01 UBG01 FAN01 UBT01 FKE01 UBY01 UBA01 FLA01 UBM01 UPA01 UBR01 FHA01 FNU01 BSB01 TUM01 URL des Erstveröffentlichers
Zusammenfassung:	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 & 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
Beschreibung:	1 Online-Ressource (41 p)
ISBN:	1451875258 9781451875256

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spelling	Schimmelpfennig, Axel Verfasser aut Predicting Sovereign Debt Crises Schimmelpfennig, Axel Washington, D.C International Monetary Fund 2003 1 Online-Ressource (41 p) txt rdacontent c rdamedia cr rdacarrier IMF Working Papers Working Paper No. 03/221 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 & 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 Online-Ausg Manasse, Paolo Sonstige oth Roubini, Nouriel Sonstige oth http://elibrary.imf.org/view/IMF001/05383-9781451875256/05383-9781451875256/05383-9781451875256.xml Verlag URL des Erstveröffentlichers Volltext
spellingShingle	Schimmelpfennig, Axel Predicting Sovereign Debt Crises
title	Predicting Sovereign Debt Crises
title_auth	Predicting Sovereign Debt Crises
title_exact_search	Predicting Sovereign Debt Crises
title_exact_search_txtP	Predicting Sovereign Debt Crises
title_full	Predicting Sovereign Debt Crises Schimmelpfennig, Axel
title_fullStr	Predicting Sovereign Debt Crises Schimmelpfennig, Axel
title_full_unstemmed	Predicting Sovereign Debt Crises Schimmelpfennig, Axel
title_short	Predicting Sovereign Debt Crises
title_sort	predicting sovereign debt crises
url	http://elibrary.imf.org/view/IMF001/05383-9781451875256/05383-9781451875256/05383-9781451875256.xml
work_keys_str_mv	AT schimmelpfennigaxel predictingsovereigndebtcrises AT manassepaolo predictingsovereigndebtcrises AT roubininouriel predictingsovereigndebtcrises

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